How to work with this metadata capture sheet

1 Start to fill column R of capture_file_metadata from top and move down respectively to the right where the R field is grey and there is a yellow field to the right.

2 Only yellowish cells are meant for filling. You will get a little pop-up window with more explanations when you click on the yellow cell.

3 Gray cells must not be filled by you, they are either not relevant for the described resource or they are filled automatically, taking content from other (yellowish) cells.You may observe that gray cells turn into yellowish cells. That can happen when a value in another field that the gray field is dependent on is filled with a value that requires information here.

4 white cells are either blank or give you additional information. They are protected.

5The yellowish fields to the right might have headings.It looks like this:

optional heoptional heoptional heoptional headline of entry4Metadata field

6 When you fill yellowish field to the right, fill them consecutively starting from left to right as you find it written: "author1","author2", "author3" etc. in rightern direction.

7 As you are used with Excel, it is possible to replicate cell content to the right by drag&drop touching the little box in the right-bottom-corner of a selection. This can speed up the filling process.

8 In case you don’t have an ORCID number, your worldwide identifier, please make sure you register and give also the name of the Institution you are working for.Registration can be done here:

9

required have to fillreq. if appl. have to fill, but is not in all cases applicablerecommended should filloptional can fill

10 It is very useful if you know and enter the Project number as stored in ProMIS, IITA's Project Administration Database. If you enter it at cell S13, you get information of the Project name in Project countries in ProMIS does not have for all projects the countries.Project donors in ProMIS does not have for all project the donor information.If you want to copy-paste the displayed ProMIS information, mind that you need to "paste Values", not just the normal paste or the use of the keys "CTRL" and "V".

11 The field AC95 gives you the opportunity to specify how big the rectangle around the area covered should be. Such "bounding boxes" are not only used for mapping but also for searching.For example, your dataset speaks about a trial conducted on a trial site field with the measurements 200x80m. The bounding box around the centerpoint of your trial site would then be at least 0.2km big.

12 Useful links:Link to AGROVOC term search:Link to CABI term search: http://www.cabi.org/cabthesaurus/mtwdk.exe?searchstring=&k=default&w=semiarid+zone&l=60&s=1&t=3&n=15&x=0&tt=0Link to Agro-Ecological zones:Link to scientists ORCID no.search:link to IITA flickr: https://www.flickr.com/photos/iita-media-library/ link to IITA YouTube: https://www.youtube.com/user/IITAPUBLISHINGlink to IITA SlideShare:

Wherever multiple answers need to be put with in a field using a declared separator, you will see yellow field to the right of that field.

https://orcid.org/register

You can identify in column Q if a cell MUST be filled, is RECOMMENDED to fill or is OPTIONAL to fill by the color of the cell to its left.Sometimes, field have to be filled when applicable.

http://aims.fao.org/standards/agrovoc/functionalities/search

http://csi.maps.arcgis.com/home/webmap/viewer.html?webmap=32442d6dc80c4bb0b95e30e6cfbf2570https://orcid.org/orcid-search/search

https://www.slideshare.net/IITA-CO

link to IITA CKAN:link to IITA CG Space: https://cgspace.cgiar.org/handle/10568/68616link to CGIAR OA/OD website: https://sites.google.com/a/cgxchange.org/oad-support-pack/homelink to IITA OA SharePoint site:link to IITA funder Policies: http://www.sherpa.ac.uk/juliet/index.php

13 Make use of the notes-field for everything that you want to state outside the standardized metadata fields.Are there any additional information necessary to make impact or to increase our visibility?

14

Definitions: in case you are unsure about definitions or descriptions of terms, you can check the "key"-tab that collects all terms.The most left author is always the primary author.You can have a maximum of 3 primary authors.

Additional lookup references

source: Field Option

contributorType ContactPerson

contributorType DataCollector

contributorType DataCurator

contributorType

contributorType Distributor

http://www.data.iita.org

http://testsp.iita.org/R4D/OpenAccess/_layouts/15/start.aspx#/

Metadata on column level (see sheet "capture_column_metadata) are of enormous help to make data understandable and re-usable. However, as of now, it is strongly recommended but not yet mandatory to fill it.

DataCite Metadata Working Group. (2016).

DataCite Metadata Schema Documentation for the Publication and Citation of Research Data. Version 4.0. DataCite e.V. http://doi.org/10.5438/0012

DataManager

contributorType Editor

contributorType Funder

contributorType HostingInstitution

contributorType Producer

contributorType ProjectLeader

contributorType ProjectManager

contributorType

contributorType RegistrationAgency

contributorType RegistrationAuthority

contributorType RelatedPerson

contributorType Researcher

contributorType ResearchGroup

contributorType RightsHolder

ProjectMember

contributorType Sponsor

contributorType

contributorType WorkPackageLeader

contributorType Other

Codelist "Relation Type" relationType IsCitedByrelationType CitesrelationType IsSupplementTorelationType IsSupplementedByrelationType IsContinuedByrelationType Continues

relationType HasMetadata

relationType IsMetadataFor

relationType IsNewVersionOfrelationType IsPreviousVersionO

relationType IsPartOf

relationType IsReferencedBy

relationType References

relationType IsDocumentedByrelationType DocumentsrelationType IsCompiledBy

relationType Compiles

Supervisor

A is the dataset described (submitted).B is a related resource.

relationType IsVariantFormOfrelationType IsOriginalFormOf

relationType IsIdenticalTorelationType IsReviewedByrelationType ReviewsrelationType IsDerivedFromrelationType IsSourceOf

Example column level metadata: Geospatial Coordinate fields

Latitude (D Longitude (DD)heading abbrev. name as in file recommended Lat Lat

heading full name recommended Latitude (DD) Latitude (DD)

heading content type recommended condition condition

property/object described

optional

sample/aggregation level recommended plot plot

unit of measurement if anyrecommended

Method recommended GPS GPS

Mode of Data Collection (DDI)

recommended

Scale optional ratioscaled ratioscaled

Data type (text, date, numeric, code) optional Numeric Numeric

if numeric: numeric type (DDI) recommended Double Double

Source or Referenced authority list

optional

Analysis Unit (code list)optional

other Analysis Unit (free text) optionalResponse Unit optional Self Self

Metadata registry ID optional 135 136

Notes

optional

centerpoint of described object

centerpoint of described object

decimal degrees

decimal degrees

Physical measurements and tests

Physical measurements and tests

spatial reference system: WGS84

spatial reference system: WGS85

Geographic Unit

Geographic Unit

auto-filled through ODK

auto-filled through ODK

Start to fill column R of capture_file_metadata from top and move down respectively to the right where the R field is grey and there is a yellow field to the right.

You will get a little pop-up window with more explanations when you click on the yellow cell.

Gray cells must not be filled by you, they are either not relevant for the described resource or they are filled automatically, taking content from other (yellowish) cells.You may observe that gray cells turn into yellowish cells. That can happen when a value in another field that the gray field is dependent on is filled with a value that requires information here.

optional headline of entry4

When you fill yellowish field to the right, fill them consecutively starting from left to right as you find it written: "author1","author2", "author3" etc. in rightern direction.

As you are used with Excel, it is possible to replicate cell content to the right by drag&drop touching the little box in the right-bottom-corner of a selection. This can speed up the filling process.

In case you don’t have an ORCID number, your worldwide identifier, please make sure you register and give also the name of the Institution you are working for.

It is very useful if you know and enter the Project number as stored in ProMIS, IITA's Project Administration Database. If you enter it at cell S13, you get information of the

ProMIS does not have for all projects the countries.ProMIS does not have for all project the donor information.

If you want to copy-paste the displayed ProMIS information, mind that you need to "paste Values", not just the normal paste or the use of the keys "CTRL" and "V".

The field AC95 gives you the opportunity to specify how big the rectangle around the area covered should be. Such "bounding boxes" are not only used for mapping but also for searching.For example, your dataset speaks about a trial conducted on a trial site field with the measurements 200x80m. The bounding box around the centerpoint of your trial site would then be at least 0.2km big.

http://www.cabi.org/cabthesaurus/mtwdk.exe?searchstring=&k=default&w=semiarid+zone&l=60&s=1&t=3&n=15&x=0&tt=0

need to be put with in a field using a declared separator, you will see yellow field to the right of that field.

to fill or is OPTIONAL to fill by the color of the cell to its left.

http://aims.fao.org/standards/agrovoc/functionalities/search

http://csi.maps.arcgis.com/home/webmap/viewer.html?webmap=32442d6dc80c4bb0b95e30e6cfbf2570

https://sites.google.com/a/cgxchange.org/oad-support-pack/home

Make use of the notes-field for everything that you want to state outside the standardized metadata fields.

Definitions: in case you are unsure about definitions or descriptions of terms, you can check the "key"-tab that collects all terms.

Description

http://testsp.iita.org/R4D/OpenAccess/_layouts/15/start.aspx#/

Metadata on column level (see sheet "capture_column_metadata) are of enormous help to make data understandable and re-usable. However, as of now, it is strongly recommended but not yet mandatory to fill it.

Person with knowledge of how to access, troubleshoot, or otherwise field issues related to the resource

Person/institution responsible for finding, gathering/collecting data under the guidelines of the author(s) or Principal Investigator (PI)

Person tasked with reviewing, enhancing, cleaning, or standardizing metadata and the associated data submitted for storage, use, and maintenance within a data center or repository

Person (or organization with a staff of data managers, such as a data centre) responsible for maintaining the finished resource.

Institution tasked with responsibility to generate/disseminate copies of the resource in either electronic or print form.

A person who oversees the details related to the publication format of the resource.

Institution that provided financial support for the development of the resource.

Typically, the organization allowing the resource to be available on the internet through the provision of its hardware/software/operating support.

Typically a person or organization responsible for the artistry and form of a media product.

Person officially designated as head of project team or sub project team instrumental in the ‐work necessary to development of the resource.

Person officially designated as manager of a project. Project may consist of one or many project teams and sub teams. ‐Person on the membership list of a designated project/project team.

Institution/organization officially appointed by a Registration Authority to handle specific tasks within a defined area of responsibility.

A standards setting body from which Registration ‐Agencies obtain official recognition and guidance.

A person without a specifically defined role in the development of the resource, but who is someone the author wishes to recognize.

A person involved in analyzing data or the results of an experiment or formal study. May indicate an intern or assistant to one of the authors who helped with research but who was not so “key” as to be listed as an author.

Typically refers to a group of individuals with a lab, department, or division; the group has a particular, defined focus of activity.

Person or institution owning or managing property rights, including intellectual property rights over the resource.

indicates that B includes A in a citationindicates that A includes B in a citationindicates that A is a supplement to Bindicates that B is a supplement to Aindicates A is continued by the work Bindicates A is a continuation of the work B

indicates resource A has additional metadata B

indicates additional metadata A for a resource B

indicates A is a previous edition of B

indicates A is used as a source of information by B

indicates B is used as a source of information for A

indicates B is documentation about/explaining Aindicates A is documentation about/Bindicates B is used to compile or create A

Person or organization that issued a contract or under the auspices of which a work has been written, printed, published, developed, etc.

Designated administrator over one or more groups/teams working to produce a resource or over one or more steps of a development process.

A Work Package is a recognized data product, not all of which is included in publication. The package, instead, may include notes, discarded documents, etc. The Work Package Leader is responsible for ensuring the comprehensive contents, versioning, and availability of the Work Package during the development of the resource.

Any person or institution making a significant contribution to the development and/or maintenance of the resource, but whose contribution does not “fit” other controlled vocabulary for contributorType.

indicates A is a new edition of B, where the new edition has been modified or updated

indicates A is a portion of B may be used for elements of a series

indicates B is the result of a compile or creation event using A

indicates A is the original form of B

indicates that A is reviewed by Bindicates that A is a review of Bindicates B is a source upon which A is basedindicates A is a source upon which B is based

indicates A is a variant or different form of B, e.g. calculated or calibrated form or different packaging

indicates that A is identical to B, for use when there is a need to register two separate instances of the same resource

Start to fill column R of capture_file_metadata from top and move down respectively to the right where the R field is grey and there is a yellow field to the right.

Gray cells must not be filled by you, they are either not relevant for the described resource or they are filled automatically, taking content from other (yellowish) cells.You may observe that gray cells turn into yellowish cells. That can happen when a value in another field that the gray field is dependent on is filled with a value that requires information here.

When you fill yellowish field to the right, fill them consecutively starting from left to right as you find it written: "author1","author2", "author3" etc. in rightern direction.

As you are used with Excel, it is possible to replicate cell content to the right by drag&drop touching the little box in the right-bottom-corner of a selection. This can speed up the filling process.

In case you don’t have an ORCID number, your worldwide identifier, please make sure you register and give also the name of the Institution you are working for.

It is very useful if you know and enter the Project number as stored in ProMIS, IITA's Project Administration Database. If you enter it at cell S13, you get information of the

If you want to copy-paste the displayed ProMIS information, mind that you need to "paste Values", not just the normal paste or the use of the keys "CTRL" and "V".

The field AC95 gives you the opportunity to specify how big the rectangle around the area covered should be. Such "bounding boxes" are not only used for mapping but also for searching.For example, your dataset speaks about a trial conducted on a trial site field with the measurements 200x80m. The bounding box around the centerpoint of your trial site would then be at least 0.2km big.

http://www.cabi.org/cabthesaurus/mtwdk.exe?searchstring=&k=default&w=semiarid+zone&l=60&s=1&t=3&n=15&x=0&tt=0

Usage Notes

Works stored in more than one archive/repository may credit each as a distributor.

Metadata on column level (see sheet "capture_column_metadata) are of enormous help to make data understandable and re-usable. However, as of now, it is strongly recommended but not yet mandatory to fill it.

May also be “Point of Contact” in organization that controls access to the resource, if that organization is different from Publisher, Distributor, Data Manager

May also use when crediting survey conductors, interviewers, event or condition observers, person responsible for monitoring key instrument data.

While the “DataManager” is concerned with digital maintenance, the DataCurator’s role encompasses quality assurance focused on content and metadata. This includes checking whether the submitted dataset is complete, with all files and components as described by submitter, whether the metadata is standardized to appropriate systems and schema, whether specialized metadata is needed to add value and ensure access acrossdisciplines, and determining how the metadata might map to search engines, database products, and automated feeds.

The work done by this person or organization ensures that the resource is periodically “refreshed”in terms of software/hardware support, is kept available or is protected from unauthorized access, is stored in accordance with industry standards, and is handled in accordance with the records management requirements applicable to it.

Note: if the Editor is to be credited in place of multiple creators, the Editor’s name may be supplied as Creator, with “(Ed.)” appended to the name.

Recommended for discovery. Includes organizations that providefunding via regular budget allocations, through grants or awards

May also be used for an organization that stores the data offline. Often a data centre (if that data centre is not the “publisher” of the resource.)

In the data industry, this may be a company “producing” DVDs that package data for future dissemination by a distributor.

The Project Leader is not “removed” from the work that resulted in the resource; he or she remains intimately involved throughout the life of the particular project team.

The manager of a project normally has more administrative responsibility than actual work involvement.

This vocabulary may or may not indicate the quality, quantity, or substance of the person’s involvement.

DataCite is a Registration Agency for the International DOI Foundation (IDF). One of DataCite’stasks is to assign DOI prefixes to the allocating agents who then assign the full, specific character string to data clients, provide metadata back to the DataCite registry, etc.

The IDF serves as the Registration Authority for the International Standards Organization (ISO) in the area/domain of Digital Object Identifiers.

This person could be an author’s intellectual mentor, a person providing intellectual leadership in the discipline or subject domain, etc.

Should be a person, not an institution. Note that a person involved in the gathering of data would fall under the contributorType “DataCollector.” The researcher may find additional data online andcorrelate it to the data collected for the experiment or study, for example.

May operate at a narrower level of scope; may or may not hold less administrative responsibility than a project team.

<no usage notes given><no usage notes given><no usage notes given><no usage notes given><no usage notes given><no usage notes given>

<no usage notes given>

<no usage notes given>

any older version of this dataset.<no usage notes given>

<no usage notes given>

for example the journal article that is underpinned by this dataset.

for example a weather data that is used in the file

for example a laboratory or field protocol/manual.<no usage notes given><no usage notes given>

<no usage notes given>

Includes organizations that provide in kind support, through donation, provision of ‐people or a facility or instrumentation necessary for the development of the resource, etc.

Could be a photographer, artist, orwriter whose contribution helped to publicize the resource (as opposed to creating it), a reviewer of the resource, someone providing administrative services to the author (such as depositing updates into an online repository, analysing usage, etc.), or one of many other roles.

<no usage notes given><no usage notes given>

for example a review or quality check report on the dataset<no usage notes given><no usage notes given>for example a sheet of data aggregated from the data in the described file.

for example if the same resource is stored in another OA repository, like Cassavabase.

SN metadata field metadata valueType information required

7 File format required application/msexcelTitles required

9 official title of the dataset required

10 short/abbreviated title of dataset optional n/a

11 The title in another language optional none

Project data required12 Project name required

13 lead institute of the project requiredrequired

14 Funder or sponsor of project required

15 recommended

Applicable Open Access Policy recommended CGIAR Open Access Policy

16 Authorship required17 authors surname required

18 authors first name required

19 authors middle name recommended

20

auto filled

21

req. if appl.

22 Address of author optional

23 CGIAR Center of author if appl. req. if appl.

24 Partner-Organization of author req. if appl.

25 CGIAR Research Program of authoreq. if appl.

26 primary author yes/no recommended

27 Contact email in case of questionsrecommended

28 Contributions req. if appl.

29 Contributors surname req. if appl.

30 Contributors first name req. if appl.

31 Contributors middle name recommended

32 Contributors full name auto filled

33 Contributors ORCID no. recommended

34 Contributor type (DataCite) optional

35 CGIAR Center of Contrib. if appl. req. if appl.

24 Partner-Organiz. of contributor req. if appl.

36 CGIAR Research Program if appl. req. if appl.

37 req. if appl.

38 req. if appl.

39 optional

Publishing

40 creation date required 2017-02-2541 Embargo end date (IITA) required

42 Self-published by IITA? req. if appl. yes

43 Publisher auto filled International Institute of Tropical Agriculture

obligatory level

Creator(s) of the item, usually author(s), full name

Creators ORCID number if applicable (https://orcid.org)

Partner-Organization as ContributorTranslator (syntax. Last name, First name, Suffix)

44 City of Publication auto filled Ibadan

45 Citation required

46 version of the dataset optional 1

47 required eng

48 language of item (freetext) optional

Content description required

49 Summary or abstract

recommended

50 req. if appl.51 Involved crops req. if appl.

54 optional

55 Involved species optional

56 required ||57 IITA research area term required

60 AGROVOC Keywords req. if appl.

req. if appl.61 keywords (free text) required

Geospatial description required62 Description of spatial coverage required

63 recommended

64 Regional coverage recommended

65 required66 Countries covered required

recommended

67 req. if appl.68 Subnational region req. if appl.

69

70 Places covered optional

71 auto filled

72 recommended

recommended

73 West-African AEZoning optional

75 IITA Station conductg. data collectoptional

76 IITA Hub optional

79 Point longitude coord. in Dec. Degrrequired 3.916667

80 Point latitude coord. in Dec. Degrerequired 7.391167

81 Point coordinate pair auto filled 3.9166667,7.391166782 recommended

83 recommended

84 Start date of data collection required

85 End date of data collection required

86 Time period covered (text) optional

87 Innovation(s) / new technologies optional

88 Protocols used optional

related docs, data, pictures, etc.

89 URL of the related item optional

Language of item (ISO code 639-2)

link to Agrovoc

Agro-Ecological Zone(s)(FAO) coveredlink to AEZ web-map

The spatial limits of a place (bounding box)

90 Identifier of related itee optional

91 Title of the related item such as a optional

92 relation type (this file to another) optional

93 IITA flickr Images related to the daoptional

94 dataset peer-reviewed? optional no

administrative metadata

95 License (default=CC-BY)required

CC-BY 4.0

96 access restrictions? req. if appl.

97 use restriction(s)? req. if appl.

98 permissions given by [email] required Not Applicable

99 Rights required CC-BY 4.0; permissions given by: Not Applicable

100 URL of license specifications auto filled https://creativecommons.org/licenses/by/4.0/legalcode

101 Usage conditions optional no warranty

104 Data origin optional n/a

105 Storage location within an archive optional

106 target audience optional

114

optional

116 Data Series within which the resourecommended

127 Notes recommended

Parent resource of the resource being described; collection of which the resource is a part.

cells for multiple value answers

default: MS Excel file (xls, xlsx) Microsoft Excel-files

default: n/a

default: none

PJ-001552 Next Generation Cassava Breeding

Proj.funder1 Proj.fund Proj.fund Proj.fund Proj.fund Proj.fund Proj.fund Proj.fund Proj.fund Proj.fund

Funder(s) as in ProMIS: CORNELL UNIVdefault: CGIAR Open Access Policy link to IITA funder Policies: http://www.sherpa.ac.uk/juliet/index.php

author2 author3 author4 author5 author6 author7 author8 author9 author10

yes no no

Contributor1 Contrb2 Contrb3 Contrb4 Contrb5 Contrb6 Contrb7 Contrb8 Contrb9 Contrb10

Partner1 Partner2 Partner3 Partner4 Partner5 Partner6 Partner7 Partner8 Partner9 Partner10

2/23/2018 <-- CGIAR Policy embargo end date (+12month)

<--check ProMIS Project No.!

author1 (primary)

Citation separator: ; Citation proposal: (2017) ; ; accessible through http://data.iita.org

default: 1

default: english (="eng")

crop1 crop2 crop3 crop4 crop5 crop6 crop7 crop8 crop9 all IITA mandate cropsno

species1 species2 species3 species4 species5 species6 species7 species8 species9 species10

term1 term2 term3 term4 term5 term6 term7 term8 term9 term10

Region1 Region2 Region3 Region4 Region5 Region6 Region7 Region8 Region9 Region10

Country1 Country2 Country3 Country4 Country5 Country6 Country7 Country8 Country9 Country1

country(s) as in ProMIS: Nigeria, Uganda, Subn.Region1 n.Region2n.Region3n.Region4n.Region5n.Region6n.Region7n.Region8n.Region9.Region10

Place1 Place2 Place3 Place4 Place5 Place6 Place7 Place8 Place9 Place10

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10

Central Western Eastern Southern

IITA Hub(s) Percentages as in ProMIS: 30 70 30 70East DMS-Converter: 3° 55' 0.0000'' East = 3.9166667 location lookup:North 7° 23' 47.0000'' North = 7.3911667

Degrees° Minutes' Seconds'' orientation Decimal Degrees (dd)Northern Southern Western Eastern

boundary coordinates: #VALUE! dd #VALUE! dd #VALUE! dd #VALUE! dd

related Item1 ted Item2ted Item3ted Item4ted Item5ted Item6ted Item7ted Item8ted Item9ed Item10

link to IITA flickr:

other restriction (please specify)

no no

no no no

default: not applicable Project Manager(s) as in ProMIS: Kulakow, Peter

no warranty other (please specify)

yes default: no warranty

https://www.flickr.com/photos/iita-media-library/

encrypted content

education. use only

no trans-lation

Separators

Proj.fund Proj.fund Proj.fund Proj.fund Proj.funder15

author11 author12 author13 author14 author15 Spt.1 SSSSSSSSSSSSSSpt.15

Contrb11 Contrb12 Contrb13 Contrb14 Contrb15

Partner11Partner12Partner13Partner14Partner15

all IITA mandate crops|

species11species12species13species14species15

term11 term12 term13 term14 term15

Region11 Region12 Region13 Region14 Region15

Country1 Country1 Country1 Country1 Country15

.Region11.Region12.Region13.Region14.Region15

Place11 Place12 Place13 Place14 Place15

AEZ11 AEZ12 AEZ13 AEZ14 AEZ15

location lookup: City longitude latitude

<temporarily unavailable>

Estimated spatial extend of the area the point is representingkm dd; factor: 0.009355

ed Item11ed Item12ed Item13ed Item14ed Item15

||

Spt.15

0 metadata field cells for multiple value answers1 heading1 heading2 heading32 heading abbrev. name as in file recommended

3 heading full name recommended

4 heading description recommended

5 heading content type optional6 property/object described recommended

7 sample/aggregation level recommended

8 unit of measurement if any recommended

9 Method recommended

10 Mode of Data Collection (DDI) optional11 Scale optional12 Data type (text, date, numeric, code) recommended

13 if numeric: numeric type (DDI) optional14 Source or Referenced authority list optional15 Analysis Unit (code list) optional16 other Analysis Unit (free text) optional17 Response Unit optional18 Metadata registry ID optional19 Notes optional

obligatory level

cells for multiple value answersheading4 heading5 heading6 heading7 heading8 heading9 heading10 heading11 heading12

heading13 heading14 heading15 heading16 heading17 heading18 heading19 heading20

heading21 heading22 heading23 heading24 heading25 heading26 heading27 heading28

Separatorsheading29 heading30

Separators

0 column authorized values1 Format Poster2 Format Brochure3 Format Booklet4 Format Research paper5 Format Book6 Format Technical report7 Format Manual8 Format Audio document9 Format Video document

10 Format E publication 11 Format Training other (e.g. ppts)12 Type of information Instruction13 Type of information Recommendation14 Type of information Good agronomic practice15 Type of information Good economic Practice16 Type of information Product information17 Type of information Explanatory18 Type of information Evaluative / comparative 19 Type of information Diagnostic20 Type of information Illustration21 Traget Audience Farmers22 Traget Audience Women farmers23 Traget Audience Youth and children 24 Traget Audience Agrodealers25 Traget Audience Extension and knowledge workers26 Traget Audience Technicians / practitioners27 Traget Audience Researchers28 Traget Audience Decision makers29 Traget Audience Unspecified30 ISFM component Straight N, P or K31 ISFM component Multinutrient32 ISFM component Rock phosphate33 ISFM component Briquettes & slow release34 ISFM component Secondary nutrients35 ISFM component Micronutrients36 ISFM component Unspecified37 ISFM component Crop residues38 ISFM component Compost39 ISFM component Manure40 ISFM component Green manure41 ISFM component Unspecified42 ISFM component N/A43 ISFM component Rhizobium inoculants44 ISFM component Nitrogen fixing free living45 ISFM component AMF46 ISFM component P-solubilizing micro-organisms47 ISFM component Plant growth promoters

48 ISFM component Other 49 ISFM component N/A50 ISFM component Better response to nutrients51 ISFM component Better adapted52 ISFM component Better resistance53 ISFM component Specific traits54 ISFM component N/A55 ISFM component Micronutrients56 ISFM component Mulching57 ISFM component Planting58 ISFM component Liming59 ISFM component Tillage60 ISFM component Water harvesting61 ISFM component Soil conservation62 ISFM component N/A63 Cropping system Sole64 Cropping system Intercropping65 Cropping system Crop rotation66 Cropping system Relay cropping67 Cropping system Other68 Cropping system N/A69 Ag Systems Fallow systems70 Ag Systems Agroforestry71 Ag Systems Conservation agric72 Ag Systems Organic agriculture73 Ag Systems Intergrated74 Ag Systems N/A75 dc.rights76 cg.coverage.region77 cg.coverage.region78 cg.coverage.region79 cg.coverage.region80 cg.coverage.region81 cg.coverage.country Benin82 cg.coverage.country Burkina Faso83 cg.coverage.country Côte D'ivoire84 cg.coverage.country Ghana85 cg.coverage.country Liberia86 cg.coverage.country Mali87 cg.coverage.country Nigeria88 cg.coverage.country Sierra Leone89 cg.coverage.country Togo90 cg.coverage.country ---------------91 cg.coverage.country Burundi92 cg.coverage.country Cameroon93 cg.coverage.country Democratic Republic of the Congo94 cg.coverage.country Rwanda95 cg.coverage.country ---------------

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1031 IITA_others brochures1032 IITA_others leaflet1033 IITA_others pamphlet1034 IITA_others Brief 1035 IITA Maps <no special subcollection>1036 IITA Audios and Videos <no special subcollection>1037 IITA Images <no special subcollection>1038 IITA Newsletters <no special subcollection>1039 IITA Websites <no special subcollection>1040 IITA Blogs, Websites, Wikis and Digital <no special subcollection>1041 IITA Press Releases <no special subcollection>1042 IITA Press Releases Magazine1043 IITA Press Releases Newspaper1044 IITA Press Releases Press interview1045 Regions Africa South of Sahara1046 Regions Central Africa1047 Regions East Africa1048 Regions Southern Africa1049 Regions West Africa1050 Regions tropical Africa1051 Regions Africa1052 Regions Asia1053 Regions Central America1054 Regions Sahel1055 Regions South America1056 Regions Sudano Sahelian Region1057 Regions ACP1058 Regions Least Developed Countries1059 Regions Low Income Food Deficit Countrie1060 Regions Net Food Importing Developing Co1061 Regions ECOWAS1062 Regions WAEMU1063 Regions CEMAC1064 Regions SADC countries1065 Regions COMESA1066 Regions Developing countries1067 Regions World1068 Regions European Union1069 Regions Annex I countries1070 Regions Non-Annex I countries1071 Regions Agrarian countries1072 Regions Developed countries1073 Regions Anglophone Africa1074 Regions Francophone Africa1075 Regions Portuguese speaking Africa1076 Regions Caribbean1077 Regions Europe1078 Regions Latin America

1079 Regions Middle East1080 Regions North Africa1081 Regions South Asia1082 Regions South East Asia1083 Regions Western Asia1084 Regions tropical America1085 Regions Southwestern Asia1086 Regions tropical Asia1087 Regions Americas1088 Regions LandLocked developing countries1089 Regions OECD countries1090 Regions Europe and Central Asia1091 Regions Middle East and North Africa1092 Regions MERCOSUR Region1093 Regions CARIFORUM Region1094 Regions IGAD Region1095 Regions Economic Cooperation Organizati1096 Regions Council of Arab Economic Unity1097 Regions ECCAS States1098 Regions Central American Agricultural Coun1099 Regions CEN-SAD States1100 Regions North of Sahara, regional1101 Regions North and Central America, region1102 Regions South and Central Asia, regional1103 Regions Arab countries1104 Regions Islamic countries1105 Regions East Asia and the Pacific1106 Regions Latin America and Caribbean1107 Regions tropical Oceania1108 cg.subject.iita Not Applicable1109 cg.subject.iita Banana1110 cg.subject.iita Plantain1111 cg.subject.iita Cassava1112 cg.subject.iita Cocoa1113 cg.subject.iita Cowpea1114 cg.subject.iita Grain Legumes1115 cg.subject.iita Maize1116 cg.subject.iita Soybean1117 cg.subject.iita Yam1118 cg.subject.iita Socioeconomy1119 cg.subject.iita Agribusiness1120 cg.subject.iita Markets1121 cg.subject.iita Policies And Institutions1122 cg.subject.iita Gender 1123 cg.subject.iita Impact Assessment1124 cg.subject.iita Smallholder Farmers1125 cg.subject.iita Baseline Survey1126 cg.subject.iita Livelihoods

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1223 IITA_Forestry Value Chains1224 IITA_ISFM <no further subdiv.>1225 IITA_Meteorology_and_Climatology <no further subdiv.>1226 IITA_Meteorology_and_Climatology Climate Change1227 IITA_Landuse <no further subdiv.>1228 IITA_Biodiversity <no further subdiv.>1229 IITA_Socioeconomy <no further subdiv.>1230 IITA_Socioeconomy Baseline Survey1231 IITA_Socioeconomy Livelihoods1232 IITA_Socioeconomy Crop Husbandry1233 IITA_Socioeconomy Smallholder Farmers1234 IITA_Socioeconomy Impact Assessment1235 IITA_Agribusiness <no further subdiv.>1236 IITA_Agribusiness Markets1237 IITA_Agribusiness Gender 1238 IITA_Agribusiness Domestic Trade1239 IITA_Agribusiness Handling, Transport, Storage and Protection of Agricultural Products1240 IITA_Policies and Institutions <no further subdiv.>1241 IITA_Food_Security <no further subdiv.>1242 IITA_Food_Systems <no further subdiv.>1243 IITA_Nutrition <no further subdiv.>1244 IITA_Biometrics <no further subdiv.>1245 IITA_Spatialanalysis <no further subdiv.>1246 IITA_KnowledgeManagement <no further subdiv.>1247 cg.subject.iita disease control1248 cg.subject.iita aflatoxin1249 cg.subject.iita soil surveys and mapping1250 cg.subject.iita <no further subdiv.>1251 West Africa Hub Ibadan (Headquarter)1252 West Africa Hub Ibadan (WA)1253 West Africa Hub Kano1254 West Africa Hub Abuja1255 West Africa Hub Cotonou1256 West Africa Hub Accra1257 West Africa Hub Tamale1258 Central Africa Hub Yaounde1259 Central Africa Hub Kinshasa1260 Central Africa Hub Bukavu1261 Central Africa Hub Bujumbura1262 Central Africa Hub Kigali1263 East Africa Hub Nairobi (CA)1264 East Africa Hub Nairobi (EA)1265 East Africa Hub Kampala1266 East Africa Hub Dar es Salaam1267 Southern Africa Hub Lusaka1268 Southern Africa Hub Lilongwe1269 Southern Africa Hub Nampula1270 IITA_Hub West Africa Hub

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1655 TimeZone UTC + 14:001656 TimeZone Other1657 DDI_DataType_simple Text1658 DDI_DataType_simple Date1659 DDI_DataType_simple Numeric1660 DDI_DataType_simple Codelist1661 Coordinates decimal places 1068951662 Coordinates decimal places 10689.51663 Coordinates decimal places 1068.951664 Coordinates decimal places 106.8951665 Coordinates decimal places 10.68951666 Coordinates decimal places 1.068951667 Coordinates decimal places 0.1068951668 Coordinates decimal places 0.01068951669 yesNo yes1670 yesNo no1671

qualifier label source

WAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC project

Extension and knowledge workers

Chemical/mineral Fertilizer Use WAHSC projectChemical/mineral Fertilizer Use WAHSC projectChemical/mineral Fertilizer Use WAHSC projectChemical/mineral Fertilizer Use WAHSC projectChemical/mineral Fertilizer Use WAHSC projectChemical/mineral Fertilizer Use WAHSC projectChemical/mineral Fertilizer Use WAHSC projectOrganic Resource Use WAHSC projectOrganic Resource Use WAHSC projectOrganic Resource Use WAHSC projectOrganic Resource Use WAHSC projectOrganic Resource Use WAHSC projectOrganic Resource Use WAHSC projectBiofertilizers WAHSC projectBiofertilizers WAHSC projectBiofertilizers WAHSC projectBiofertilizers WAHSC projectBiofertilizers WAHSC project

Biofertilizers WAHSC projectBiofertilizers WAHSC projectimproved seeds WAHSC projectimproved seeds WAHSC projectimproved seeds WAHSC projectimproved seeds WAHSC projectimproved seeds WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectLocal Adaptation WAHSC projectAnnual crops WAHSC projectAnnual crops WAHSC projectAnnual crops WAHSC projectAnnual crops WAHSC projectAnnual crops WAHSC projectAnnual crops WAHSC project

WAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC projectWAHSC project

BEN BENIN ISO 3166BFA BURKINA FASO ISO 3166CIV CÔTE D'IVOIRE ISO 3166GHA GHANA ISO 3166LBR LIBERIA ISO 3166MLI MALI ISO 3166NGA NIGERIA ISO 3166SLE SIERRA LEONE ISO 3166TGO TOGO ISO 3166

---------------BDI BURUNDI ISO 3166CMR CAMEROON ISO 3166COD DEMOCRATIC REPUBLIC OF THE CONGO ISO 3166RWA RWANDA ISO 3166

---------------

ETH ETHIOPIA ISO 3166KEN KENYA ISO 3166UGA UGANDA ISO 3166TZA UNITED REPUBLIC OF TANZANIA ISO 3166

---------------MWI MALAWI ISO 3166MOZ MOZAMBIQUE ISO 3166SWZ SWAZILAND ISO 3166ZMB ZAMBIA ISO 3166

---------------LAO LAO PEOPLE'S DEMOCRATIC REPUBLIC ISO 3166KHM CAMBODIA ISO 3166VNM VIET NAM ISO 3166NER NIGER ISO 3166MDG MADAGASCAR ISO 3166CAF CENTRAL AFRICAN REPUBLIC ISO 3166ZWE ZIMBABWE ISO 3166COG CONGO ISO 3166GMB GAMBIA ISO 3166SEN SENEGAL ISO 3166GNQ EQUATORIAL GUINEA ISO 3166GAB GABON ISO 3166GNB GUINEA-BISSAU ISO 3166GIN GUINEA ISO 3166

CGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR OfficeCGIAR Office

English World ISO 639-2French World ISO 639-2Spanish World ISO 639-2Portuguese Mozambique ISO 639-2Hausa Nigeria ISO 639-2Igbo Nigeria ISO 639-2Yoruba Nigeria ISO 639-2Fon Benin ISO 639-2

Dyula Burkina Faso ISO 639-2Mossi Burkina Faso ISO 639-2Akan Ghana ISO 639-2Nzima Ghana ISO 639-2Twi Ghana ISO 639-2Bambara Mali ISO 639-2Soninke Mali ISO 639-2Kanuri Niger ISO 639-2Songhai languages Niger ISO 639-2Creoles and pidgins, English based Nigeria ISO 639-2Edo Nigeria ISO 639-2Efik Nigeria ISO 639-2Tiv Nigeria ISO 639-2Ewe Togo ISO 639-2Bamileke languages Cameroon ISO 639-2Ewondo Cameroon ISO 639-2Duala Cameroon ISO 639-2kongo DR Congo ISO 639-2Luba-Katanga DR Congo ISO 639-2Luba-Lulua DR Congo ISO 639-2Mongo DR Congo ISO 639-2Kpelle Liberia ISO 639-2Wolof Senegal ISO 639-2Mandingo Senegal ISO 639-2Mende Sierra Leone ISO 639-2Arabic world ISO 639-2Uncoded languages world ISO 639-2Not applicable world ISO 639-2center CGIAR Officecenter IITA CGIAR Officecenter AfricaRice CGIAR Officecenter Bioversity International CGIAR Officecenter CIFOR CGIAR Officecenter ICARDA CGIAR Officecenter CIAT CGIAR Officecenter ICRISAT CGIAR Officecenter IFPRI CGIAR Officecenter ILRI CGIAR Officecenter CIMMYT CGIAR Officecenter CIP CGIAR Officecenter IRRI CGIAR Officecenter IWMI CGIAR Officecenter ICRAF CGIAR Officecenter WorldFish CGIAR Office

CGIAR OfficeCGIAR Research Program on Agriculture for Nutrition and Health (A4NH) CGIAR OfficeCGIAR Research Program on Aquatic Agricultural Systems (AAS) CGIAR OfficeCGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) CGIAR Office

CGIAR Research Program on Dryland Cereals (Dryland Cereals) CGIAR OfficeCGIAR Research Program on Dryland Systems (Dryland Systems) CGIAR OfficeCGIAR Research Program on Forests, Trees and Agroforestry (ForestsTreesAgroforestry) CGIAR OfficeCGIAR Research Program for Managing and Sustaining Crop Collections (Genebanks) CGIAR OfficeCGIAR Research Program on Grain Legumes (Grain Legumes) CGIAR OfficeCGIAR Research Program on Rice (GRiSP) CGIAR OfficeCGIAR Research Program on Integrated Systems for the Humid Tropics (Humidtropics) CGIAR OfficeCGIAR Research Program on Livestock and Fish (Livestock and Fish) CGIAR OfficeCGIAR Research Program on Maize (MAIZE) CGIAR OfficeCGIAR Research Program on Policies, Institutions and Markets (Policies, Institutions and Markets) CGIAR OfficeCGIAR Research Program on Roots, Tubers and Bananas (RTB) CGIAR OfficeCGIAR Research Program on Wheat (WHEAT) CGIAR OfficeCGIAR Research Program on Water, Land and Ecosystems (WLE) CGIAR Office

UnitNameDecimal DegreeDegreesAcreHectare

Square KilometerLocal Currency UnitLocal Currency Unit per kgLocal Currency Unit per tonLocal Currency Unit per acreLocal Currency Unit per hectarLocal Currency Unit per square kilometerUS DollarsUS Dollars per TonUS Dollars per TonUS Dollars per TonUS Dollars per TonUS Dollars per TonIntegerNumberPercentQuantilQuantils per AcreQuintalsRankRatioStringTextValue ListCostHouseholdsPeoplePeople per Square KilometerPersonsCasesCases/peopleCases/PersonCountCentimeterHundredth of an InchInchesMetersMeters per SecondMilesMillimetersMillimeters per YearTenth of a MillimeterAgeKilowatt hoursMegajoules per SquareMeterWatt-hours per Square MeterWatts per Square MeterMillibars

DecimalBillion Cubic MetersCubic metersLitreKnotsCelsiusFahrenheitDateDayHoursMinutesMonthsSeasonsSecondsTimeWeeksYearsGramsKilogramsKilograms per AcreKilograms per HectareKilograms per LiterKilograms per TonKilometersKilometers per HourKilotonnes of Oil EquivalentKilotonsMetric TonsMetric Tons per CapitaMicrograms per Cubic MeterTonsTons per AcreTons per HectareTons per Hectare per Hour of laborWeight

creativecommons.orgcreativecommons.orgcreativecommons.orgcreativecommons.orgcreativecommons.orgcreativecommons.orgcreativecommons.org

non-commercial educational use only

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Video recording RIS1 IATI Code list2 IATI Code list3 IATI Code list4 IATI Code list5 IATI Code list6 IATI Code list7 IATI Code list8 IATI Code list9 IATI Code list1 IATI Code list2 IATI Code list1 IATI Code list2 IATI Code list3 IATI Code list4 IATI Code list1 IATI Code list2 IATI Code listA1 IATI Code listA2 IATI Code listA3 IATI Code listA4 IATI Code listG1 IATI Code listG2 IATI Code list

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(:etal) DataCitePerson with knowledge of how to access, troubleshoot, or otherwise field issues related to DataCitePerson/institution responsible for finding, gathering/collecting data under the guidelines of tDataCitePerson tasked with reviewing, enhancing, cleaning, or standardizing metadata and the assocDataCitePerson (or organization with a staff of data managers, such as a data centre) responsible forDataCiteInstitution tasked with responsibility to generate/disseminate copies of the resource in eitheDataCiteA person who oversees the details related to the publication format of the resource. DataCiteInstitution that provided financial support for the development of the resource. DataCiteTypically, the organization allowing the resource to be available on the internet through th DataCiteTypically a person or organization responsible for the artistry and form of a media product. DataCitePerson officially designated as head of project team or sub project team instrumental in th‐ DataCite

Person officially designated as manager of a project. Project may consist of one or many pr DataCitePerson on the membership list of a designated project/project team. DataCiteInstitution/organization officially appointed by a Registration Authority to handle specific tasDataCiteA standards setting body from which Registration Agencies obtain official recognition and g‐ DataCiteA person without a specifically defined role in the development of the resource, but who is DataCiteA person involved in analyzing data or the results of an experiment or formal study. May indDataCiteTypically refers to a group of individuals with a lab, department, or division; the group has a pDataCitePerson or institution owning or managing property rights, including intellectual property rig DataCitePerson or organization that issued a contract or under the auspices of which a work has beenDataCiteDesignated administrator over one or more groups/teams working to produce a resource or DataCiteA Work Package is a recognized data product, not all of which is included in publication. T DataCiteAny person or institution making a significant contribution to the development and/or maintDataCiteindicates A is used as a source of information by B DataCiteindicates A is a portion of B may be used for elements of a series DataCiteindicates A is a source upon which B is based DataCiteindicates that A is a supplement to B DataCiteindicates B is documentation about/explaining A DataCiteindicates B is used as a source of information for A DataCiteindicates A is a continuation of the work B DataCiteindicates A is continued by the work B DataCiteindicates that B is a supplement to A DataCiteindicates that A includes B in a citation DataCiteindicates that B includes A in a citation DataCiteindicates B is a source upon which A is based DataCiteindicates that A is a review of B DataCiteindicates that A is reviewed by B DataCiteindicates A is documentation about/B DataCiteindicates that A is identical to B, for use when there is a need to register two separate inst DataCiteindicates B is the result of a compile or creation event using A DataCiteindicates B is used to compile or create A DataCiteindicates A is a previous edition of B DataCiteindicates A is a new edition of B, where the new edition has been modified or updated DataCiteindicates additional metadata A for a resource B DataCiteindicates resource A has additional metadata B DataCiteindicates A is the original form of B DataCiteindicates A is a variant or different form of B, e.g. calculated or calibrated form or different DataCiteDigital Object Identifier a character string used to uniquely identify an objecDataCiteInternational Standard Book Number a unique numeric book identifier. There are 2 formatDataCiteInternational Standard Serial Number a unique 8 digit number used to identify a print or e‐ DataCiteUniform Resource Locator a specific character string that constitutes a refe DataCiteno related identifier typehandle A handle is an abstract reference to a resource. DataCitePersistent Uniform Resource Locator A PURL has three parts: (1) a protocol, (2) a resolverDataCiteUniform Resource Name a unique and persistent identifier of an electronic DataCiteInternational Article Number European Article Number, now renamed International DataCiteElectronic International Standard Seria ISSN used to identify periodicals in electronic form DataCitelinking ISSN The linking ISSN or ISSN L enables collocation or li‐ DataCitePubMed identifier a unique number assigned to each PubMed record. DataCite

Astrophysics Data System bibliographic a standardized 19 character identifier according t DataCiteInternational Standard Text Code a unique “number” assigned to a textual work. An ISDataCiteArchival Resource Key URL designed to support long term access to informa‐ DataCitearXiv identifier arXiv identifier; arXiv.org is a repository of preprin DataCiteLife Science Identifiers a unique identifier for data in the Life Science domaDataCiteUniversal Product Code a barcode symbology used for tracking trade items iDataCitemandatory Mandatory properties must be provided. DataCiterecommended Recommended (R ) properties are optional, but st DataCiteoptional Optional (O) properties are optional and provide ricDataCite

optional and repeatable DataCiteoptional, but not repeatable DataCiterequired and repeatable DataCiterequired, but not repeatable DataCiteThe date that the publisher accepted the resource iDataCiteThe date the resource is made publicly available. MDataCiteThe specific, documented date at which the resource DataCiteThe date or date range in which the resource contenDataCiteThe date the resource itself was put together; this coDataCiteThe date that the resource is published or distributeDataCiteThe date the creator submits the resource to the pubDataCiteThe date of the last update to the resource, when t DataCiteThe date or date range during which the dataset or DataCitePerson with knowledge of how to access, troubleshooDataCitePerson/institution responsible for finding, gatheringDataCitePerson tasked with reviewing, enhancing, cleaning, DataCitePerson (or organization with a staff of data managerDataCiteInstitution tasked with responsibility to generate/diDataCiteA person who oversees the details related to the puDataCiteInstitution that provided financial support for the DataCiteTypically, the organization allowing the resource to DataCiteTypically a person or organization responsible for t DataCitePerson officially designated as head of project tea DataCitePerson officially designated as manager of a projec DataCitePerson on the membership list of a designated proj DataCiteInstitution/organization officially appointed by a RegDataCiteA standards setting body from which Registration Ag‐ DataCiteA person without a specifically defined role in the DataCiteA person involved in analyzing data or the results o DataCiteTypically refers to a group of individuals with a lab, DataCitePerson or institution owning or managing property riDataCitePerson or organization that issued a contract or undDataCiteDesignated administrator over one or more groups/DataCiteA Work Package is a recognized data product, not alDataCiteAlternative Title DataCiteSubtitle DataCiteTranslated Title DataCite

IITAInnovDBIITAInnovDB

IITAInnovDB1 IITAInnovDB2 IITAInnovDB3 IITAInnovDB4 IITAInnovDB5 IITAInnovDB

1 IITAInnovDB2 IITAInnovDB3 IITAInnovDB4 IITAInnovDB5 IITAInnovDB6 IITAInnovDBmsexcel *.xls *.xla Microsoft Excel-filesvnd.openxmlformats-officedocument.sp*.xlsx OpenOffice Calc files ("OpenOffice comma-separated-values *.csv comma separated datafilesplain *.txt plain textfilesxml *.xml XML-filestab-separated-values *.tsv tabulator-separated data filesoctet-stream *.bin *.exe *.com *.dll *.class executable-filesrtf *.rtf RTF-filesx-tar *.tar tar-archiving filesxml *.xml XML-fileszip *.zip ZIP-archiving fileshtml *.htm *.html *.shtml HTML-filesx-gtar *.gtar GNU tar-Archivdateiengzip *.gz GNU Zip-filespostscript *.ai *.eps *.ps PostScript-filesjavascript *.js JavaScript-filesmsword *.doc *.dot Microsoft Word-filespdf *.pdf PDF-filesxhtml+xml *.htm *.html *.shtml *.xhtml XHTML-filesx-javascript *.js (server) JavaScript-filesx-httpd-php *.php *.phtml PHP-filesother other other file typeA series of visual representations imparting an impression of motion when shown in succes DataCiteAn aggregation of resources of various types. If a collection exists of a single type, use the siDataCiteData encoded in a defined structure. DataCiteA non persistent, time based occurrence. ‐ ‐ DataCiteA visual representation other than text. DataCiteA resource requiring interaction from the user to be understood, executed, or experienced DataCiteAn abstract, conceptual, graphical, mathematical or visualization model that represents empDataCiteAn inanimate, three dimensional object or substance. ‐ DataCiteA system that provides one or more functions of value to the end user. ‐ DataCiteA computer program in source code (text) or compiled form. DataCiteA resource primarily intended to be heard. DataCiteA resource consisting primarily of words for reading. DataCiteA structured series of steps which can be executed to produce a final outcome, allowing useDataCiteIf selected, supply a value for ResourceType. DataCite

LGP >270 daysLGP >270 daysLGP 180-270 daysLGP 180-270 daysLGP 70-180 daysLGP 70-180 daysLGP <70 daysLGP <70 daysLGP 180-270 daysLGP 180-270 daysLGP 70-180 daysLGP 70-180 daysLGP <70 daysLGP <70 dayssz MARC codes for RDA carrier termssd MARC codes for RDA carrier termsss MARC codes for RDA carrier termsst MARC codes for RDA carrier termssg MARC codes for RDA carrier termsse MARC codes for RDA carrier termssi MARC codes for RDA carrier termssq MARC codes for RDA carrier termsck MARC codes for RDA carrier termscb MARC codes for RDA carrier termscd MARC codes for RDA carrier termscr MARC codes for RDA carrier termscz MARC codes for RDA carrier termsce MARC codes for RDA carrier termsca MARC codes for RDA carrier termscf MARC codes for RDA carrier termsch MARC codes for RDA carrier termsha MARC codes for RDA carrier termshe MARC codes for RDA carrier termshf MARC codes for RDA carrier termshb MARC codes for RDA carrier termshc MARC codes for RDA carrier termshd MARC codes for RDA carrier termshj MARC codes for RDA carrier termshh MARC codes for RDA carrier termshg MARC codes for RDA carrier termshz MARC codes for RDA carrier termspp MARC codes for RDA carrier termspz MARC codes for RDA carrier termsmr MARC codes for RDA carrier terms

www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/

mo MARC codes for RDA carrier termsgs MARC codes for RDA carrier termsmz MARC codes for RDA carrier termsgt MARC codes for RDA carrier termsmc MARC codes for RDA carrier termsmf MARC codes for RDA carrier termsgd MARC codes for RDA carrier termsgf MARC codes for RDA carrier termsgc MARC codes for RDA carrier termseh MARC codes for RDA carrier termses MARC codes for RDA carrier termsez MARC codes for RDA carrier termsnn MARC codes for RDA carrier termsnb MARC codes for RDA carrier termsnc MARC codes for RDA carrier termsnr MARC codes for RDA carrier termsnz MARC codes for RDA carrier termsno MARC codes for RDA carrier termsna MARC codes for RDA carrier termszu MARC codes for RDA carrier termsvd MARC codes for RDA carrier termsvz MARC codes for RDA carrier termsvc MARC codes for RDA carrier termsvf MARC codes for RDA carrier termsvr MARC codes for RDA carrier terms

MARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codesMARC codes

age Use for the chronological age of the group members (Library of Congressedu Use for the educational level of the group members Library of Congress

eth Library of Congressgdr Use for the gender of the group members. Library of Congresslng Use for the language associated with the group membLibrary of Congressnat Use for the demonym related to a country, sub-natioLibrary of Congressocc Use for the activity or avocation associated with theLibrary of Congressrel Use for the religion or denomination of the group mLibrary of Congress

A use copy of the resource is freely and openly acceRegistry of Digital MastersAccess is available only to authorized users. Access Registry of Digital MastersThe user’s ability to view or interact with the resou Registry of Digital MastersUsed when the digital resource is not available to t Registry of Digital MastersAccess restrictions are not known, are subject to chaRegistry of Digital Masters

MARC_computer_carrier MARC codesMARC_unmedieated_carrier MARC codesMARC_video_carrier MARC codesMARC_unspecified_carrier MARC codesMARC_audio_carrier MARC codesMARC_projected_image_carrier MARC codesMARC_stereographic_carrier MARC codes

0 ONIX List 150AA Audio recording – detail unspecified ONIX List 150AC Audio compact disc, in any recording format: use foONIX List 150AE Audio disc (excluding CD-Audio) ONIX List 150AI ONIX List 150AJ Audio recording downloadable online ONIX List 150BA Book – detail unspecified ONIX List 150DA Digital content delivered on a physical carrier (detaiONIX List 150DB ONIX List 150DC CD interactive: use for ‘green book’ discs ONIX List 150DI ONIX List 150DJ ONIX List 150DK ONIX List 150DL ONIX List 150DM ONIX List 150EA Digital content delivered electronically (delivery m ONIX List 150EB Digital content available both by download and by oONIX List 150EC Digital content accessed online only ONIX List 150ED Digital content delivered by download only ONIX List 150FC Photographic transparencies mounted for projectioONIX List 150PK Poster for retail sale – see also XF ONIX List 150PL Record book (eg ‘birthday book’, ‘baby book’): bindONIX List 150PN ONIX List 150BB Hardback or cased book ONIX List 150BC Paperback or other softback book ONIX List 150BD Loose-leaf book ONIX List 150BE Spiral, comb or coil bound book ONIX List 150BF Pamphlet or brochure, stapled; German ‘geheftet’. ONIX List 150BO Concertina-folded book or chart, designed to fold toONIX List 150BZ Other book format or binding not specified by BB t ONIX List 150

Use for the ethnic or cultural identification of the group members (e.g., Sinhalese, Seneca Indians). For ethnic and cultural groups that are also demonyms associated with a country, sub-national region or jurisdiction, or supra-national region, prefer Nationality/regional group.

CC ONIX List 150CZ Other cartographic format not specified by CB to CEONIX List 150DF AKA ‘floppy disc’ ONIX List 150DN Double-sided disc, one side Audio CD/CD-ROM, othONIX List 150DZ Other carrier of digital content not specified by DB ONIX List 150LA Digital product license (delivery method not encodeONIX List 150LB Digital product license delivered through the retail ONIX List 150LC Digital product license delivered by email or other ONIX List 150PA Miscellaneous printed material – detail unspecified ONIX List 150PZ Other printed item not specified by PB to PQ ONIX List 150VA Video – detail unspecified ONIX List 150VI DVD video: specify TV standard in List 175 ONIX List 150ZH General purpose tablet computer, typically with colONIX List 150PB May use product form detail codes P201 to P204 to ONIX List 150PC ONIX List 150PE Copymasters, photocopiable sheets ONIX List 150PO ONIX List 150PQ A book-sized (as opposed to poster-sized) sheet, usuaONIX List 150PR A book with all pages blank for the buyer’s own useONIX List 150PS May use product form detail codes P201 to P204 to ONIX List 150VZ Other video format not specified by VB to VP ONIX List 150XF Promotional poster for display, not for sale – see al ONIX List 150AZ Other audio format not specified by AB to AK ONIX List 150FD Transparencies for overhead projector ONIX List 150PD Cards, flash cards (eg for teaching reading) ONIX List 150PM Wallet or folder (containing loose sheets etc): it is ONIX List 150CA Sheet map – detail unspecified ONIX List 150CB ONIX List 150CD See Code List 80 for ‘rolled in tube’ ONIX List 150FA Film or transparency – detail unspecified ONIX List 150AB Audio cassette (analogue) ONIX List 150AG Sony MiniDisc format ONIX List 150AH Audio compact disc with part CD-ROM content, also ONIX List 150BG ONIX List 150FE ONIX List 150FF Continuous movie film as opposed to filmstrip ONIX List 150FZ Other film or transparency format not specified by ONIX List 150PF May use product form detail codes P201 to P204 to ONIX List 150VJ VHS videotape: specify TV standard in List 175 ONIX List 150VN High definition DVD disc, Toshiba HD DVD format ONIX List 150VO High definition DVD disc, Sony Blu-ray format ONIX List 150

1 An executable together with data on which it operaONIX List 1592 A sound recording ONIX List 1593 A still image ONIX List 1594 Readable text, with or without associated images e ONIX List 1595 Moving images, with or without accompanying sou ONIX List 1596 A website or other supporting resource delivering cONIX List 1597 Use only when no more detailed specification is pr ONIX List 81

9 Data files ONIX List 8110 Readable text of the main work: this value is requi ONIX List 8112 Maps and/or other cartographic content ONIX List 8114 E-publication is enhanced with a significant number ONIX List 8115 E-publication is enhanced with a significant numberONIX List 8118 Whether in a plate section / insert, or not ONIX List 8119 Including other ‘mechanical’ (ie non-photographic) iONIX List 8120 E-publication is enhanced with additional images o ONIX List 8133 Data set plus software ONIX List 81

4 Audio recording of other sound, eg birdsong ONIX List 816 Includes Film, video, animation etc. Use only when ONIX List 818 Largely ‘content free’ ONIX List 81

13 eg an interview, not a ‘reading’ or ‘performance’) ONIX List 8116 E-publication is enhanced with additional textual coONIX List 8122 Product is enhanced with audio recording of full or ONIX List 8124 eg animated diagrams, charts, graphs or other illustONIX List 8128 Other video content eg interview, not a reading or ONIX List 8130 E-publication is enhanced with video recording of f ONIX List 81

1234567

Mid Altitude Northern Guinea Savanna 89

10111213

BibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadataBibTeX metadata

A person involved in analyzing data or the results o DataCitePerson/institution responsible for finding, gatheringDataCitePerson tasked with reviewing, enhancing, cleaning, DataCite

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DataCiteDataCiteDataCiteDataCiteDataCiteDataCiteDataCiteDataCiteDataCiteDataCiteDataCiteDataCite

DataCiteDataCite

IITA Training materials and Manuals DataCiteIITA Websites, Blogs, Wikis and other digital communications DataCite

DataCiteIITA_text_collections DataCiteIITA_image_collections DataCiteIITA_AudiosVideos DataCiteSubcollection CG Spaceno_special_subcollection CG Spacedictionairies & encyclopedia entries CG SpaceConference proceedings CG SpaceAnnual reports and other periodical reports CG SpaceProject reports CG SpaceTechnical reports CG SpaceCase Study CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG SpaceQuestionnaires CG SpaceTemplates CG SpaceField and laboratory documents CG Spacechecklists CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG SpaceMagazine CG SpaceNewspaper CG SpacePress interview CG SpaceBrief CG Spacefactsheets CG Spaceflyers CG Spacebrochures CG Spaceleaflet CG Spacepamphlet CG Spaceno_special_subcollection CG SpaceIITA_Books_Bookchapters CG Spaceno_special_subcollection CG SpaceIITA_reports CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG SpaceIITA_working_papers CG Spaceno_special_subcollection CG Space

no_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG Spaceno_special_subcollection CG SpaceIITA_miscellaneous CG Space

dictionairies & encyclopedia entries CG SpaceCG Space

Annual reports and other periodical reports CG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG Space

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Annual reports and other periodical reports CG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG Space

CG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG SpaceCG Space

166 Africa South of Sahara AGROVOC1432 Central Africa AGROVOC2442 East Africa AGROVOC7265 Southern Africa AGROVOC8355 West Africa AGROVOC7970 tropical Africa AGROVOC165 Africa AGROVOC666 Asia AGROVOC1434 Central America AGROVOC6734 Sahel AGROVOC7253 South America AGROVOC32605 Sudano Sahelian Regionno match African, Caribbean and Pacific Group of Statesno match Least Developed Countriesno match Low Income Food Deficit Countriesno match Net Food Importing Developing Countriesno match Economic Community of West African States (ECOWAS) Regionno match West African Economic and Monetary Unionno match Central African Economic and Monetary Community35295 SADC countries AGROVOCno match COMESA Region2222 Developing countries AGROVOC24920 World AGROVOC34779 European Union AGROVOCno match Annex I countriesno match Non-Annex I countries194 Agrarian countries AGROVOC2221 Developed countries AGROVOC416 Anglophone Africa AGROVOC3084 Francophone Africa AGROVOC29175 Portuguese speaking Africa AGROVOC1320 Caribbean AGROVOC2724 Europe AGROVOC4221 Latin America AGROVOC

no match Middle East5218 North Africa AGROVOC29172 South Asia AGROVOC7260 South East Asia AGROVOC29174 Western Asia AGROVOC7971 tropical America AGROVOC29173 Southwestern Asia AGROVOC7972 tropical Asia AGROVOC335 Americas AGROVOCno match LandLocked developing countries36736 OECD countries AGROVOCno match Europe and Central Asiano match Middle East and North Africa34780 Southern Common Market AGROVOCno match Caribbean Forum of African, Caribbean and Pacific Statesno match Intergovernmental Authority on Developmentno match Economic Cooperation Organizationno match Council of Arab Economic Unityno match Economic Community of Central African Statesno match Central American Agricultural Councilno match Community of Sahel-Saharan Statesno match North of Sahara, regionalno match North and Central America, regionalno match South and Central Asia, regional564 Arab countries AGROVOC28485 Islamic countries AGROVOCno match East Asia and the Pacificno match Latin America and Caribbean7975 tropical Oceania AGROVOC

BANANA IITA mandate cropsPLANTAIN IITA mandate cropsCASSAVA IITA mandate cropsCOCOA IITA mandate cropsCOWPEA IITA mandate cropsGRAIN LEGUMES IITA mandate cropsMAIZE IITA mandate cropsSOYBEAN IITA mandate cropsYAM IITA mandate cropsSOCIOECONOMY IITA research areasAGRIBUSINESS IITA research areasMARKETS IITA research areasPOLICIES AND INSTITUTIONS IITA research areasGENDER IITA research areasIMPACT ASSESSMENT IITA research areasSMALLHOLDER FARMERS IITA research areasBASELINE SURVEY IITA research areasLIVELIHOODS IITA research areas

CROP HUSBANDRY IITA research areasDOMESTIC TRADE IITA research areas

Handling, Transport, Storage And Protection Of Agricultural Products HANDLING, TRANSPORT, STORAGE AND PROTECTIOIITA research areasBIODIVERSITY IITA research areasCLIMATE CHANGE IITA research areasCROP SYSTEMS IITA research areasFARM MANAGEMENT IITA research areasFARMING SYSTEMS IITA research areasLAND USE IITA research areasSOIL FERTILITY IITA research areasSOIL HEALTH IITA research areasSOIL INFORMATION IITA research areasVALUE CHAINS IITA research areasNATURAL RESOURCE MANAGEMENT IITA research areas

Integrated Soil Fertility Management INTEGRATED SOIL FERTILITY MANAGEMENT IITA research areasAGRONOMY IITA research areasFORESTRY IITA research areasMETEOROLOGY AND CLIMATOLOGY IITA research areasSOIL SURVEYS AND MAPPING IITA research areasAFLATOXIN IITA research areasDISEASE CONTROL IITA research areasPOST-HARVESTING TECHNOLOGY IITA research areasPLANT HEALTH IITA research areasPLANT PRODUCTION IITA research areasPESTS OF PLANTS IITA research areasPLANT DISEASES IITA research areasPLANT ECOLOGY IITA research areasWEEDS IITA research areasBIOFORTIFICATION IITA research areasPLANT GENETIC RESOURCES IITA research areasTISSUE CULTURE IITA research areasGENETIC IMPROVEMENT IITA research areasPLANT BREEDING IITA research areasBIOSCIENCE IITA research areasFOOD SCIENCE IITA research areasFOOD SECURITY IITA research areasFOOD SYSTEMS IITA research areasNUTRITION IITA research areasBIOMETRICS IITA research areasRESEARCH METHOD IITA research areasKNOWLEDGE MANAGEMENT IITA research areasCAPACITY DEVELOPMENT IITA research areas

IITA_Genetic_improvement GENETIC IMPROVEMENT IITA research areasIITA_Plant_Health_and_Plant_Prd PLANT HEALTH AND PLANT PRODUCTION IITA research areasIITA_NRM NATURAL RESOURCE MANAGEMENT IITA research areasIITA_Socioeconomy_and_Agribusiness SOCIOECONOMY AND AGRIBUSINESS IITA research areasIITA_Food_Science FOOD SCIENCE IITA research areasIITA_Research_Methods RESEARCH METHOD IITA research areas

IITA_Capacity_Development CAPACITY DEVELOPMENT IITA research areas<no further subdiv.> IITA research areasBioscience BIOSCIENCE IITA research areasPlant Breeding PLANT BREEDING IITA research areasPlant Genetic Resources PLANT GENETIC RESOURCES IITA research areasBiofortification BIOFORTIFICATION IITA research areas<no further subdivision> IITA research areasPlant Health PLANT HEALTH IITA research areasPlant Production PLANT PRODUCTION IITA research areas<no further subdiv.> IITA research areasISFM INTEGRATED SOIL FERTILITY MANAGEMENT IITA research areasAgronomy AGRONOMY IITA research areasForestry FORESTRY IITA research areasMeteorology and Climatology METEOROLOGY AND CLIMATOLOGY IITA research areasLanduse LAND USE IITA research areasBiodiversity BIODIVERSITY IITA research areas<no further subdiv.> IITA research areasSocioeconomy SOCIOECONOMY IITA research areasAgribusiness AGRIBUSINESS IITA research areasPolicies and Institutions POLICIES AND INSTITUTIONS IITA research areas<no further subdiv.> IITA research areasFood Security FOOD SECURITY IITA research areasFood Systems FOOD SYSTEMS IITA research areasNutrition NUTRITION IITA research areas<no further subdiv.> IITA research areasBiometrics BIOMETRICS IITA research areasSpatial Analysis SPATIAL ANALYSIS IITA research areas<no further subdiv.> IITA research areasKnowledge Management KNOWLEDGE MANAGEMENT IITA research areas

<NO FURTHER SUBDIV.> IITA research areasGENETIC RESOURCE CONSERVATION IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areasPESTS OF PLANTS IITA research areasPLANT DISEASES IITA research areasPLANT ECOLOGY IITA research areas<NO FURTHER SUBDIV.> IITA research areasPOST-HARVESTING TECHNOLOGY IITA research areasWEEDS IITA research areas<NO FURTHER SUBDIV.> IITA research areasSOIL FERTILITY IITA research areasSOIL HEALTH IITA research areasSOIL INFORMATION IITA research areas<NO FURTHER SUBDIV.> IITA research areasFARMING SYSTEMS IITA research areasCROP SYSTEMS IITA research areasFARM MANAGEMENT IITA research areas

VALUE CHAINS IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areasCLIMATE CHANGE IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areasBASELINE SURVEY IITA research areasLIVELIHOODS IITA research areasCROP HUSBANDRY IITA research areasSMALLHOLDER FARMERS IITA research areasIMPACT ASSESSMENT IITA research areas<NO FURTHER SUBDIV.> IITA research areasMARKETS IITA research areasGENDER IITA research areasDOMESTIC TRADE IITA research areas

Handling, Transport, Storage and Protection of Agricultural Products HANDLING, TRANSPORT, STORAGE AND PROTECTIOIITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areas<NO FURTHER SUBDIV.> IITA research areasDISEASE CONTROL IITA research areasAFLATOXIN IITA research areasSOIL SURVEYS AND MAPPING IITA research areas<NO FURTHER SUBDIV.> IITA research areas

IITA_stations_WA IBADAN (HEADQUARTER) IITA stationsIITA_stations_WA IBADAN (WA) IITA stationsIITA_stations_WA KANO IITA stationsIITA_stations_WA ABUJA IITA stationsIITA_stations_WA COTONOU IITA stationsIITA_stations_WA ACCRA IITA stationsIITA_stations_WA TAMALE IITA stationsIITA_stations_CA YAOUNDE IITA stationsIITA_stations_CA KINSHASA IITA stationsIITA_stations_CA BUKAVU IITA stationsIITA_stations_CA BUJUMBURA IITA stationsIITA_stations_CA KIGALI IITA stationsIITA_stations_EA NAIROBI (CA) IITA stationsIITA_stations_EA NAIROBI (EA) IITA stationsIITA_stations_EA KAMPALA IITA stationsIITA_stations_EA DAR ES SALAAM IITA stationsIITA_stations_SA LUSAKA IITA stationsIITA_stations_SA LILONGWE IITA stationsIITA_stations_SA NAMPULA IITA stations

WEST AFRICA HUB IITA hubs

CENTRAL AFRICA HUB IITA hubsEAST AFRICA HUB IITA hubsSOUTHERN AFRICA HUB IITA hubsCONFERENCE S. Oyinlola/F. OgunsolaSYMPOSIUM S. Oyinlola/F. OgunsolaMEETING S. Oyinlola/F. OgunsolaSEMINAR S. Oyinlola/F. OgunsolaTRAINING S. Oyinlola/F. OgunsolaWORKSHOP S. Oyinlola/F. OgunsolaPROJECT LAUNCH S. Oyinlola/F. OgunsolaNEW VARIETY LAUNCH S. Oyinlola/F. OgunsolaNEW TECHNOLOGY LAUNCH S. Oyinlola/F. OgunsolaRETREAT S. Oyinlola/F. OgunsolaAWARD S. Oyinlola/F. OgunsolaEXIHIBITION S. Oyinlola/F. OgunsolaFIELD VISIT S. Oyinlola/F. Ogunsola

unknownunknownunknownunknownIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryIITA metadata registryMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa RiceMarc Bernhard, Africa Rice

334 cropontology.org326 cropontology.org340 cropontology.org322 cropontology.org325 cropontology.org325 cropontology.org

336 cropontology.org343 cropontology.org337 cropontology.org320 cropontology.org331 cropontology.org321 cropontology.org332 cropontology.org338 cropontology.org328 cropontology.org339 cropontology.org327 cropontology.org335 cropontology.org341 cropontology.org330 cropontology.org324 cropontology.org345 cropontology.org342 cropontology.org323 cropontology.org350 cropontology.org

Trushar ShahTrushar ShahTrushar ShahTrushar ShahTrushar Shah

Mode Identifies the type of aggregation used to combine rDDIMedian Identifies the type of aggregation used to combine rDDIMaximum Identifies the type of aggregation used to combine rDDIMinimum Identifies the type of aggregation used to combine rDDIPercent Identifies the type of aggregation used to combine rDDICumulativePercent Identifies the type of aggregation used to combine rDDIPercentileRank Identifies the type of aggregation used to combine rDDIOther Identifies the type of aggregation used to combine rDDIIndividual Describes the entity being analyzed in the study or iDDIOrganization Describes the entity being analyzed in the study or iDDIFamily Describes the entity being analyzed in the study or iDDIFamily.HouseholdFamily Describes the entity being analyzed in the study or iDDIHousehold Describes the entity being analyzed in the study or iDDIHousingUnit Describes the entity being analyzed in the study or iDDIEventOrProcess Describes the entity being analyzed in the study or iDDIGeographicUnit Describes the entity being analyzed in the study or iDDIStudy IITAExperiment IITATrial IITAPlot IITAplant IITATimeUnit Describes the entity being analyzed in the study or iDDITextUnit Describes the entity being analyzed in the study or iDDIGroup Describes the entity being analyzed in the study or iDDI

Object Describes the entity being analyzed in the study or iDDIOther Describes the entity being analyzed in the study or iDDIASCII Standard set of characters upon which many characDDIISO88591 Standard set of characters upon which many characDDIISO88592 Standard set of characters upon which many characDDIISO88593 Standard set of characters upon which many characDDIISO88594 Standard set of characters upon which many characDDIISO88595 Standard set of characters upon which many characDDIISO88596 Standard set of characters upon which many characDDIISO88597 Standard set of characters upon which many characDDIISO88598 Standard set of characters upon which many characDDIISO88599 Standard set of characters upon which many characDDIISO885910 Standard set of characters upon which many characDDIISO885911 Standard set of characters upon which many characDDIISO885913 Standard set of characters upon which many characDDIISO885914 Standard set of characters upon which many characDDIISO885915 Standard set of characters upon which many characDDIISO885916 Standard set of characters upon which many characDDIMacOSRoman Standard set of characters upon which many characDDIUTF8 Standard set of characters upon which many characDDIUTF16 Standard set of characters upon which many characDDIUTF32 Standard set of characters upon which many characDDIWindows1251 Standard set of characters upon which many characDDIWindows1252 Standard set of characters upon which many characDDIWindows1253 Standard set of characters upon which many characDDIWindows1254 Standard set of characters upon which many characDDIWindows1255 Standard set of characters upon which many characDDIWindows1256 Standard set of characters upon which many characDDIWindows1257 Standard set of characters upon which many characDDIWindows1258 Standard set of characters upon which many characDDIUnspecified Standard set of characters upon which many characDDIOther Standard set of characters upon which many characDDIIdentical Describes the degree of similarity between two itemDDISome Describes the degree of similarity between two itemDDINone Describes the degree of similarity between two itemDDIString Identifies the type of data, which has a bearing on DDINormalizedString Identifies the type of data, which has a bearing on DDIBoolean Identifies the type of data, which has a bearing on DDIDecimal Identifies the type of data, which has a bearing on DDIInteger Identifies the type of data, which has a bearing on DDIPositiveInteger Identifies the type of data, which has a bearing on DDINegativeInteger Identifies the type of data, which has a bearing on DDINonNegativeInteger Identifies the type of data, which has a bearing on DDINonPositiveInteger Identifies the type of data, which has a bearing on DDILong Identifies the type of data, which has a bearing on DDIInt Identifies the type of data, which has a bearing on DDIShort Identifies the type of data, which has a bearing on DDIByte Identifies the type of data, which has a bearing on DDI

UnsignedLong Identifies the type of data, which has a bearing on DDIUnsignedInt Identifies the type of data, which has a bearing on DDIUnsignedShort Identifies the type of data, which has a bearing on DDIUnsignedByte Identifies the type of data, which has a bearing on DDIFloat Identifies the type of data, which has a bearing on DDIDouble Identifies the type of data, which has a bearing on DDIDateTime Identifies the type of data, which has a bearing on DDITime Identifies the type of data, which has a bearing on DDIDate Identifies the type of data, which has a bearing on DDIGYearMonth Identifies the type of data, which has a bearing on DDIGYear Identifies the type of data, which has a bearing on DDIGMonthDay Identifies the type of data, which has a bearing on DDIGDay Identifies the type of data, which has a bearing on DDIGMonth Identifies the type of data, which has a bearing on DDIDuration Identifies the type of data, which has a bearing on DDIHexBinary Identifies the type of data, which has a bearing on DDIBase64Binary Identifies the type of data, which has a bearing on DDIAnyURI Identifies the type of data, which has a bearing on DDIOther Identifies the type of data, which has a bearing on DDIMetadataEditing Specifies the event happening over the data life cycDDIMetadataTranslation Specifies the event happening over the data life cycDDIFinalReport Specifies the event happening over the data life cycDDIEvaluation Specifies the event happening over the data life cycDDIOriginalRelease Specifies the event happening over the data life cycDDIDeposit Specifies the event happening over the data life cycDDIPreservationPackageProduction Specifies the event happening over the data life cycDDIDisseminationPackageProduction Specifies the event happening over the data life cycDDIDisseminationPackageRelease Specifies the event happening over the data life cycDDIDataAnalysisReports Specifies the event happening over the data life cycDDINewVersionRelease Specifies the event happening over the data life cycDDIOther Specifies the event happening over the data life cycDDIInterview The procedure, technique, or mode of inquiry used tDDIInterview.FaceToFace The procedure, technique, or mode of inquiry used tDDIInterview.FaceToFace.CAPI The procedure, technique, or mode of inquiry used tDDIInterview.FaceToFace.PAPI The procedure, technique, or mode of inquiry used tDDIInterview.Telephone The procedure, technique, or mode of inquiry used tDDIInterview.Telephone.CATI The procedure, technique, or mode of inquiry used tDDIInterview.Email The procedure, technique, or mode of inquiry used tDDIInterview.WebBased The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.FixedFo The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.FixedFo The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.FixedFo The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.Fixed The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.FixedF The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.InteractiThe procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.InteractiThe procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.Interact The procedure, technique, or mode of inquiry used tDDI

SelfAdministeredQuestionnaire.Interact The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.Interact The procedure, technique, or mode of inquiry used tDDISelfAdministeredQuestionnaire.Interact The procedure, technique, or mode of inquiry used tDDIFocusGroup The procedure, technique, or mode of inquiry used tDDIFocusGroup.FaceToFace The procedure, technique, or mode of inquiry used tDDIFocusGroup.Telephone The procedure, technique, or mode of inquiry used tDDIFocusGroup.Online The procedure, technique, or mode of inquiry used tDDISelfAdministeredWritingsAndDiaries The procedure, technique, or mode of inquiry used tDDISelfAdministeredWritingsAndDiaries.EmaThe procedure, technique, or mode of inquiry used tDDISelfAdministeredWritingsAndDiaries.PapThe procedure, technique, or mode of inquiry used tDDISelfAdministeredWritingsAndDiaries.W The procedure, technique, or mode of inquiry used tDDIObservation The procedure, technique, or mode of inquiry used tDDIObservation.Field The procedure, technique, or mode of inquiry used tDDIObservation.Field.Participant The procedure, technique, or mode of inquiry used tDDIObservation.Field.Nonparticipant The procedure, technique, or mode of inquiry used tDDIObservation.Laboratory The procedure, technique, or mode of inquiry used tDDIObservation.Laboratory.Participant The procedure, technique, or mode of inquiry used tDDIObservation.Laboratory.Nonparticipant The procedure, technique, or mode of inquiry used tDDIObservation.ComputerBased The procedure, technique, or mode of inquiry used tDDIExperiment The procedure, technique, or mode of inquiry used tDDIExperiment.Laboratory The procedure, technique, or mode of inquiry used tDDIExperiment.FieldIntervention The procedure, technique, or mode of inquiry used tDDIExperiment.WebBased The procedure, technique, or mode of inquiry used tDDIRecording The procedure, technique, or mode of inquiry used tDDIContentCoding The procedure, technique, or mode of inquiry used tDDITranscription The procedure, technique, or mode of inquiry used tDDICompilationSynthesis The procedure, technique, or mode of inquiry used tDDISummary The procedure, technique, or mode of inquiry used tDDIAggregation The procedure, technique, or mode of inquiry used tDDISimulation The procedure, technique, or mode of inquiry used tDDIMeasurementsAndTests The procedure, technique, or mode of inquiry used tDDIMeasurementsAndTests.Educational The procedure, technique, or mode of inquiry used tDDIMeasurementsAndTests.Physical The procedure, technique, or mode of inquiry used tDDIMeasurementsAndTests.Psychological The procedure, technique, or mode of inquiry used tDDIOther The procedure, technique, or mode of inquiry used tDDIInteger Specifies the type of numeric data. DDIInt Specifies the type of numeric data. DDILong Specifies the type of numeric data. DDIShort Specifies the type of numeric data. DDIDecimal Specifies the type of numeric data. DDIFloat Specifies the type of numeric data. DDIDouble Specifies the type of numeric data. DDICount Specifies the type of numeric data. DDIIncremental Specifies the type of numeric data. DDIOther Specifies the type of numeric data. DDISelf Indicates the entity that provided the information caDDIInformant Indicates the entity that provided the information caDDIProxy Indicates the entity that provided the information caDDI

Interviewer Indicates the entity that provided the information caDDIOther Indicates the entity that provided the information caDDIAcaStat Indicates the statistical software package used in t DDIADaMSoft Indicates the statistical software package used in t DDIAnalyseIt Indicates the statistical software package used in t DDIAuguri Indicates the statistical software package used in t DDIBioStat Indicates the statistical software package used in t DDIBMDP Indicates the statistical software package used in t DDIBrightStat Indicates the statistical software package used in t DDIDataplot Indicates the statistical software package used in t DDIDBase Indicates the statistical software package used in t DDIDIF Indicates the statistical software package used in t DDIEasyReg Indicates the statistical software package used in t DDIEpiInfo Indicates the statistical software package used in t DDIEViews Indicates the statistical software package used in t DDIGAUSS Indicates the statistical software package used in t DDIGoldenHelix Indicates the statistical software package used in t DDIGraphPadPrism Indicates the statistical software package used in t DDIGretl Indicates the statistical software package used in t DDIJMP Indicates the statistical software package used in t DDILimdep Indicates the statistical software package used in t DDIMacAnova Indicates the statistical software package used in t DDIMaple Indicates the statistical software package used in t DDIMathematica Indicates the statistical software package used in t DDIMatLab Indicates the statistical software package used in t DDIMedCalc Indicates the statistical software package used in t DDIMinitab Indicates the statistical software package used in t DDIModelQED Indicates the statistical software package used in t DDINCSS Indicates the statistical software package used in t DDINSDStat Indicates the statistical software package used in t DDIOpenEpi Indicates the statistical software package used in t DDIOrigin Indicates the statistical software package used in t DDIPartek Indicates the statistical software package used in t DDIPrimer Indicates the statistical software package used in t DDIPSPP Indicates the statistical software package used in t DDIRCommander Indicates the statistical software package used in t DDIR Indicates the statistical software package used in t DDIRATS Indicates the statistical software package used in t DDIRKWard Indicates the statistical software package used in t DDISalStat Indicates the statistical software package used in t DDISAS Indicates the statistical software package used in t DDIShazam Indicates the statistical software package used in t DDISOCR Indicates the statistical software package used in t DDISPlus Indicates the statistical software package used in t DDISPSS Indicates the statistical software package used in t DDIStata Indicates the statistical software package used in t DDIStatistica Indicates the statistical software package used in t DDISUDAAN Indicates the statistical software package used in t DDI

TSP Indicates the statistical software package used in t DDIOther Indicates the statistical software package used in t DDIArithmeticMean Specifies the type of summary statistic. Summary statDDIGeometricMean Specifies the type of summary statistic. Summary statDDIHarmonicMean Specifies the type of summary statistic. Summary statDDITrimmedMean Specifies the type of summary statistic. Summary statDDIStandardErrorOfMean Specifies the type of summary statistic. Summary statDDIMode Specifies the type of summary statistic. Summary statDDIMedian Specifies the type of summary statistic. Summary statDDIValidCases Specifies the type of summary statistic. Summary statDDIInvalidCases Specifies the type of summary statistic. Summary statDDIMinimum Specifies the type of summary statistic. Summary statDDIMaximum Specifies the type of summary statistic. Summary statDDIRange Specifies the type of summary statistic. Summary statDDISum Specifies the type of summary statistic. Summary statDDIVariance Specifies the type of summary statistic. Summary statDDIStandardDeviation Specifies the type of summary statistic. Summary statDDICoefficientOfVariation Specifies the type of summary statistic. Summary statDDIAverageAbsoluteDeviation Specifies the type of summary statistic. Summary statDDIMedianAbsoluteDeviation Specifies the type of summary statistic. Summary statDDIFirstQuartile Specifies the type of summary statistic. Summary statDDISecond Quartile Specifies the type of summary statistic. Summary statDDIThirdQuartile Specifies the type of summary statistic. Summary statDDIInterquartileRange Specifies the type of summary statistic. Summary statDDIFirstQuintile Specifies the type of summary statistic. Summary statDDISecondQuintile Specifies the type of summary statistic. Summary statDDIThirdQuintile Specifies the type of summary statistic. Summary statDDIFourthQuintile Specifies the type of summary statistic. Summary statDDIInterquintileRange Specifies the type of summary statistic. Summary statDDIFirstDecile Specifies the type of summary statistic. Summary statDDISecondDecile Specifies the type of summary statistic. Summary statDDIThirdDecile Specifies the type of summary statistic. Summary statDDIFourthDecile Specifies the type of summary statistic. Summary statDDIFifthDecile Specifies the type of summary statistic. Summary statDDISixthDecile Specifies the type of summary statistic. Summary statDDISeventhDecile Specifies the type of summary statistic. Summary statDDIEighthDecile Specifies the type of summary statistic. Summary statDDINinthDecile Specifies the type of summary statistic. Summary statDDIInterdecileRange Specifies the type of summary statistic. Summary statDDIOtherPercentile Specifies the type of summary statistic. Summary statDDIBeta1 Specifies the type of summary statistic. Summary statDDIBeta2 Specifies the type of summary statistic. Summary statDDIShapiroWilk Specifies the type of summary statistic. Summary statDDIPercentageOfValidCases Specifies the type of summary statistic. Summary statDDIPercentageOfInvalidCases Specifies the type of summary statistic. Summary statDDIOther Specifies the type of summary statistic. Summary statDDILongitudinal Describes the time dimension of the data collectionDDILongitudinal.CohortEventBased Describes the time dimension of the data collectionDDI

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0.5 geo0.5 geo

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MARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.2 info productMARC codes for RDA carrier terms 0.2 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 0.3 info productMARC codes for RDA carrier terms 0.3 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.5 info product

www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/www.fao.org/nr/gaez/en/

MARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.5 info productMARC codes for RDA carrier terms 0.3 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0.1 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 0 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 0.6 info productMARC codes for RDA carrier terms 0.6 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 1 info productMARC codes for RDA carrier terms 0.6 info productMARC codes for RDA carrier terms 0.6 info productMARC codes for RDA carrier terms 0.1 info product

1 info product1 info product1 info product1 info product

0.9 info product0.9 info product0.9 info product0.8 info product0.8 info product0.7 info product0.2 info product0.2 info product0.1 info product0.1 info product

0 info product1 info product1 info product

0.6 info product0.1 info product0.1 info product

0 info productLibrary of Congress 1 info productLibrary of Congress 1 info product

Library of Congress 0.8 info productLibrary of Congress 1 info productLibrary of Congress 0.8 info productLibrary of Congress 0.6 info productLibrary of Congress 0.8 info productLibrary of Congress 0.2 info productRegistry of Digital Masters info productRegistry of Digital Masters info productRegistry of Digital Masters info productRegistry of Digital Masters info productRegistry of Digital Masters info product

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0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.7 info product0.6 info product0.6 info product0.6 info product0.6 info product0.6 info product0.6 info product0.6 info product0.6 info product0.6 info product0.5 info product0.5 info product0.5 info product0.5 info product0.4 info product0.4 info product0.4 info product0.3 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product0.2 info product

1 info product1 info product1 info product1 info product1 info product1 info product1 info product

1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product

0.8 info product0.8 info product0.8 info product0.8 info product0.8 info product0.8 info product0.8 info product0.8 info product0.8 info product

1 geo1 geo1 geo1 geo1 geo1 geo1 geo1 geo

0.8 geo0.6 geo0.6 geo0.5 geo0.5 geo

1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product

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1 agent Supervision0.9 agent0.9 agent Data curation

0.9 agent Writing – review & editing0.9 agent Funding acquisition0.9 agent Conceptualization0.9 agent0.9 agent0.9 agent Project administration0.8 agent0.8 agent Supervision0.8 agent0.8 agent0.8 agent Resources0.7 agent Resources0.7 agent0.5 agent0.4 agent0.2 agent

0 agent0 agent0 agent

0.8 agent0.8 agent0.8 agent0.8 agent0.8 agent0.8 agent0.6 agent0.6 agent0.6 agent0.6 agent0.6 agent0.6 agent0.4 agent0.4 agent

RIS documentation 0.2 info productRIS documentation 0.2 info productRIS documentation 0.2 info product

1 info product1 info product

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0.99 info product0.98 info product0.97 info product0.96 info product0.95 info product0.94 info product0.93 info product0.92 info product

0.92 info product0.91 info product0.91 info product0.91 info product0.91 info product

1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product

1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product

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1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product

1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 info product1 geo1 geo1 geo1 geo1 geo1 geo

0.9 geo0.9 geo0.9 geo0.9 geo0.9 geo0.9 geo

0.85 geo0.85 geo0.85 geo0.85 geo0.85 geo0.85 geo0.85 geo0.85 geo0.85 geo0.85 geo

0.8 geo0.8 geo0.8 geo0.8 geo0.8 geo0.8 geo

0.75 geo0.75 geo0.75 geo

0.7 geo0.7 geo0.7 geo

0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo0.7 geo

1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA mandate crops 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4D

IITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4D

1 1 R4D2 1 R4D3 1 R4D4 1 R4D5 1 R4D6 1 R4D

7 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4D

1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4D

IITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4DIITA research areas 1 R4D

0.99 Nigeria agent1 Nigeria agent1 Nigeria agent1 Nigeria agent1 Benin agent1 Ghana agent1 Ghana agent1 Cameroon agent1 Democratic Republiagent1 Democratic Republiagent1 Burundi agent1 Rwanda agent

0.99 Kenya agent1 Kenya agent1 Uganda agent1 United Republic ofagent1 Zambia agent1 Malawi agent1 Mozambique agent1 agent

1 agent1 agent1 agent

S. Oyinlola/F. Ogunsola 1 temporalS. Oyinlola/F. Ogunsola 0.9 temporalS. Oyinlola/F. Ogunsola 1 temporalS. Oyinlola/F. Ogunsola 1 temporalS. Oyinlola/F. Ogunsola 1 temporalS. Oyinlola/F. Ogunsola 0.8 temporalS. Oyinlola/F. Ogunsola 0.8 temporalS. Oyinlola/F. Ogunsola 0.8 temporalS. Oyinlola/F. Ogunsola 0.8 temporalS. Oyinlola/F. Ogunsola 0.7 temporalS. Oyinlola/F. Ogunsola 0.6 temporalS. Oyinlola/F. Ogunsola 0.9 temporalS. Oyinlola/F. Ogunsola 0.8 temporal

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0.8

IITA metadata registry 0.8 explains the content of the data (actual scientific metadata)IITA metadata registry 0.8 refers to metadata that describe the technical handling of dataIITA metadata registry 0.8 relates to the origin of the data, and ranges from the human to the highly technical. Where did the data come from? Why was it collected? Who collected it, when and where? What instruments/technologies were used to collect the data, and how were they set up? What has been done to the data since it was collected?IITA metadata registry 0.8 provides information about access and usage rules.Who is allowed to view, edit or otherwise modify the data, or the metadata, and under what conditions? Who has some kind of authority over the data? Who has the authority to change the rules? Are there costs associated with access? Who has accessed the data, and what have they in turn done with it? Under what licence is the data being made available?IITA metadata registry 0.8 used to record and facilitate relationships between or within digital resources. How is the data set up? What formats, and versions of formats, are used? How is the database configured? How does it relate to other data?IITA metadata registry 0.8 includes information to help build a sense of trust in the data, and allow for the data to be used long into the future. Is the data authentic, authoritative, and original? Has there been any restructuring, e.g. due to software and file-formats changing? What software has been used to access the data in the past?IITA metadata registry 0.8 metadata collected from or about the users themselves (e.g. user annotations, number of people accessing a particular resource)IITA metadata registry 0.8 provides fundamental information for a person or a computer to read the data. How is the data set up? What formats, and versions of formats, are used? How is the database configured? How does it relate to other data?IITA metadata registry 0.8 If individual values of a certain information (usually organized In a column) are described by the metadata fieldIITA metadata registry 0.8 If information about the entity (usually organized In a table) are described by the metadata fieldIITA metadata registry 0.8 If information about interconnected tables (usually organized In a relational database) are described by the metadata fieldMarc Bernhard, Africa Rice 0.8 The adoption rate will be MUCH higher on large farmsMarc Bernhard, Africa Rice 0.8 The adoption rate will be MUCH higher when it can be applied on a large scale (e.g. cost will decrease drastically when applied at large scale)Marc Bernhard, Africa Rice 0.8 The farmers do not trust the solution since it is new to themMarc Bernhard, Africa Rice 0.8 Farmers are reluctant because the investment could be lost due to other factors such as rainfall, pests, diseases and timely access to critical inputsMarc Bernhard, Africa Rice 0.8 Literacy will have a big impact on adoption ratesMarc Bernhard, Africa Rice 0.8 Practical training will have a decisive impact on adoption ratesMarc Bernhard, Africa Rice 0.8 Labor availability will have a big impact on adoption ratesMarc Bernhard, Africa Rice 0.8 Access to financial services will have a big impact on adoption ratesMarc Bernhard, Africa Rice 0.8 Land ownership is an important prerequisite to benefit from technologyMarc Bernhard, Africa Rice 0.8 Accessibility inputs will have a great influence on the adoption of technologyMarc Bernhard, Africa Rice 0.8 Availability of professional services (veterinarians, mechanics, welders, ..) is an important prerequisite for high adoption rates.

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0.8

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0.8

0.8

0.6

0.6

0.6

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0.6

0.6

0.6

0.6

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0.5

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0.2

1

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element version 1.reusable The value that appears most often in a set of valueselement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusable The number of parts out of 100. In mathematics, a percentage is a number of ratio expressed as a fraction of 100. Percentages are used to express how large one quantity is relative to another quantity.element version 1.reusable The total of a frequency and all frequencies below it in a frequency distribution; the "running total" of frequencies [the maximum value is 100%].element version 1.reusable The percentile rank of a item is the percentage of items in its frequency distribution which are lower [cannot reach 100%].element version 1.reusable Use when the aggregation method is known, but not found in the list.element version 1.reusable Any individual person, irrespective of demographic characteristics, professional, social or legal status, or affiliation.element version 1.reusable Any kind of formal administrative and functional structure - includes associations, institutions, agencies, businesses, political parties, schools, etc.element version 1.reusable Two or more people related by blood, marriage (including step-relations), adoption or fostering and who may or may not live together (National Community Services Data Dictionary, Vers 3, AIHW, 2004). For example, used when researching the extent to which people provide support and assistance for their relatives.element version 1.reusable A more specific term, refers only to related people who live in the same household at a point in time. If not known whether the analysis unit is "Family" or "Household family", use "Family".element version 1.reusable A person or a group of persons who share the same dwelling unit and common living arrangements. These common living arrangements may include pooling some, or all, of their income and wealth, and consuming certain types of goods and services collectively, mainly housing and food (Eurostat).element version 1.reusable U.S. Census: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from the outside of the building or through a common hall.element version 1.reusable Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.element version 1.reusable Any entity that can be spatially defined as a geographic area, with either natural (physical) or administrative boundaries.

element version 1.reusable Any period of time: year, week, month, day, or bimonthly or quarterly periods, etc.element version 1.reusable Books, articles, any written piece/entity.element version 1.reusable Two or more individuals assembled together or having some unifying relationship.

The middle value in a series of values arranged sequentially from smallest to largest. The highest value attained or recorded. The lowest value attained or recorded.

element version 1.reusable Anything material, but inanimate, that has an independent existence and may be perceived by the senses. Examples: objects of art (paintings, sculptures, etc.) or weapons, or vehicles, etc.element version 1.reusable Use if the unit of analysis is known, but not found in the list.element version 1.physicaldatap The official name is US-ASCII but use the format: ASCII. The ISO code for ASCII is ISO 14962.element version 1.physicaldatap For ISO standards, use format: ISO-n-n in Caption and ISOnn in Code. ISO standards are also known as Latin, for example, ISO-8859-1 as Latin1.element version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldatap For Unicode Transformation Formats, use format: UTF-n in Caption and UTFn in Code.element version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldatap For MS-Windows character sets, use format: Windows-n in Caption and Windowsn in Code.element version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldataproductelement version 1.physicaldatap Use if the character set is not known, for example for some proprietary data files.element version 1.physicaldatap Use if the character set is known, but not found in the list.element version 1.comparison Use when the compared items have identical content. For variables, for example, all the elements of a variable description (name, label, question text, category values and codes, universe, concept) will be identical in form.element version 1.comparison Use when the compared items have similar but not identical content. For variables, for example, some of the elements of a variable description (name, label, question text, category values and codes, universe, concept) will be identical in form, while others will be different.element version 1.comparison Normally not used, as it would not be expected to compare items that have nothing in common. This term was necessary to complete the commonality range, and may be used in special cases, as determined by user needs (for instance, when comparability was expected, but not found).element version 1.reusable Finite sequences of characters. A character is an atomic unit of welement version 1.reusable Type of string in which any occurrence of whitespace (ielement version 1.reusable True or false. Can be represented by 1 and 0 correspondingly. element version 1.reusable A subset of real numbers, which can be represented by aelement version 1.reusable Whole numbers, the infinite set of integers, no minimum or maximum value. element version 1.reusable Whole numbers greater than 0. element version 1.reusable Whole numbers less than 0. element version 1.reusable Whole numbers greater than -1. element version 1.reusable Whole numbers less than 1. element version 1.reusable Whole numbers in the range -9223372036854775808 .. 9223372036854775807element version 1.reusable Whole numbers in the range -2147483648 .. 2147483647. element version 1.reusable Whole numbers in the range -32768 .. 32767. element version 1.reusable Whole numbers in the range -128 .. 127.

element version 1.reusable Whole numbers in the range 0 .. 18446744073709551element version 1.reusable Whole numbers in the range 0 .. 4294967295.element version 1.reusable Whole numbers in the range 0 .. 65535.element version 1.reusable Whole numbers in the range 0 .. 255 (system dependeelement version 1.reusableelement version 1.reusableelement version 1.reusable Integer-valued year, month, day, hour and minute, plelement version 1.reusable Left-truncated dateTime, e.g., 13:20:00-05:00 (1:20 pm for Eastern Standelement version 1.reusable Integer-valued year, month, day, and time zone hour and minuteselement version 1.reusable Integer-valued year and month, e.g., 2004-11. element version 1.reusable Integer-valued year, e.g., 2005. element version 1.reusable Integer-valued month and day, e.g., 12-31. element version 1.reusable Integer-valued day, e.g., 24. element version 1.reusable Integer-valued month, e.g., 03. element version 1.reusable A duration of time. The value space of "duration" is aelement version 1.reusable Even-lengthed sequence of hexadecimal digits representing an N × 8-bit integer.element version 1.reusable Sequence of multiples of four base64 digits, where each 4-tuple represents a 24-bit integer. Each digit (a-z, A-Z, 0-9, +, /) represents a 6-bit integer between 0 and 63. element version 1.reusable A Uniform Resource Identifier such as ftp, http or mailto, e.g., httelement version 1.reusable Use if the data type is known, but not found in the listelement version 1.reusable Amending the metadata to reflect changes in the data or to improve or enhance documentation.element version 1.reusable Translating the metadata into another language.element version 1.reusable Complete account on how the study was conducted through all its stages, often required by funders or other administrative bodies.element version 1.reusable Analysis of how the study, in all its stages, was managed and/or conducted, including the outcome of methodological, technical, and business decisions. May serve as a basis for changes or improvements in planning future iterations of the data collection, or entirely new projects.element version 1.reusable First release of data and/or metadata to other individuals and/or agencies than the study producers.element version 1.reusable Handing over the data and available metadata (Submission Information Package in OAIS terms) to a data archive or repository for preservation, possible further processing, and dissemination.element version 1.reusable Producing a preservation package of the data for archiving purposes (Archival Information Package in OAIS terms).element version 1.reusable Producing a dissemination package for distribution of the data (Dissemination Information Package in OAIS terms).element version 1.reusable Publishing or otherwise making the dissemination package available to users.element version 1.reusable Reports describing how the data were analyzed, as well as the resulting findings. These may take the form of conference posters or presentations, journal articles or online publications, books, book chapters, etc.element version 1.reusable Publishing or otherwise making a new version of the data and/or metadata available to users.element version 1.reusable Use if the event type is known, but not found in the list. element version 1.data collectionA pre-planned communication between two (or more) people - the interviewer(s) and the interviewee(s) - in which information is obtained by the interviewer(s) from the interviewee(s). If group interaction is part of the method, use “Focus group”. element version 1.data collectionData collection method in which a live interviewer conducts a personal interview, presenting questions and entering the responses. Use this broader term if not CAPI or PAPI, or if not known whether CAPI /PAPI or not.element version 1.data collectionComputer-assisted personal interviewing. Data collection method in which the interviewer reads questions to the respondents from a computer's screen and keys in the answers. The administration of the interview is managed by a specifically designed program. element version 1.data collectionPaper-and-pencil interviewing. The interviewer uses a traditional paper questionnaire to read the questions and enter the answers. element version 1.data collectionInterview administered on the telephone. Use this broader term if not CATI, or if not known whether CATI or not. element version 1.data collectionComputer-assisted telephone interviewing. The interviewer asks questions as directed by a computer, responses are keyed directly into the computer and the administration of the interview is managed by a specifically designed program. element version 1.data collectionInterviews conducted via e-mail, usually consisting of several e-mail messages that allow the discussion to continue beyond the first set of questions and answers, or the first e-mail exchange. element version 1.data collectionAn interview conducted via the Internet. Examples include interviews conducted within online forums or using web-based audio-visual technology enabling the interviewer(s) and interviewee(s) to communicate in real time. element version 1.data collectionData collection method in which the respondent reads, or listens to the questions, and enters the responses by him/herself; no live interviewer is present, or participates in the questionnaire administration. If possible, use a narrower term.element version 1.data collectionThe questionnaire is not interactive and remains the same regardless of the responses given to prior questions. Use the broader term if the method is not described by any of the narrower terms. For example, for PDF and diskette questionnaires. element version 1.data collectionQuestions are presented to the respondent in the text body of an e-mail, not as an attached electronic questionnaire or as a link to a web-based questionnaire. element version 1.data collectionSelf-administered survey using a traditional paper questionnaire delivered and/or collected by mail (postal services), by fax, or in person by either interviewer, or respondent. element version 1.data collectionThe questions and answers are incorporated in SMS (text messages) or MMS (messages including multimedia content) sent to, and from mobile phones. element version 1.data collectionData are collected using a Web questionnaire that is fixed (not interactive).element version 1.data collectionSelf-administered questionnaire in which the question sequence is not fixed, being managed by computer software. Some of the questions, as well as the order in which they are asked, are contingent to responses given to previous questions. element version 1.data collectionComputer-assisted self-interview. Data collection method in which the respondents enter their own answers directly into a computer (desktop, laptop, Palm/PDA, etc.). The administration of the questionnaire is managed by a specifically designed program, but there is no real-time data transfer, as in the case of CAWI: the answers are stored on the computer used for the interview. Use CASI if not known whether VCASI, ACASI, or TACASI. element version 1.data collectionVideo computer-assisted self-interview. Earliest method of computer-assisted self-interviewing, in which respondents view the questions on a computer screen and typically enter answers using the computer keyboard, mouse, or touchscreen. (Thomas Harmon, et al. “Impact of T-ACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280)

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for float. Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double.

element version 1.data collectionAudio computer-assisted self-interview. Data are collected by using a recorded voice into a computer-assisted self-interview. The text of each question and its answer alternatives are displayed on the computer screen, while a pre-recorded interviewer’s voice reads these to the respondent, who listens privately through headphones. Respondents answer by selecting the appropriate response on the keyboard or directly on the computer screen. Sometimes referred to as audio-visual CASI (AVCASI). (adapted from https://syrp.org/images/ACASI_Insert_Singles.pdf) element version 1.data collectionTelephone audio computer-assisted self-interview. TACASI adds telephone capabilities to a standard audio-CASI system, thereby allowing ACASI interviews to be conducted over the telephone, with the telephone’s touchtone keypad serving as the input device. (Thomas Harmon, et al. “Impact of TACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280) element version 1.data collectionComputer-assisted Web interview. The administration of the questionnaire completion is managed by a specifically designed program. Questions can be tailored to previous question responses, enabling routing plans. Answers are stored directly on the main database which is accessible through the Web, using a password-secured webpage.element version 1.data collectionA group discussion on a particular topic, organized for research purposes. The individuals are selected with relevance to the topic, and interaction among the participants is used as part of the method. element version 1.data collectionThe focus group participants meet in person to conduct the discussion. element version 1.data collectionThe focus group discussion is conducted over the telephone. element version 1.data collectionThe focus group discussion is conducted over the Internet in an interactive manner. element version 1.data collectionNarratives, stories, diaries and other personal written texts.element version 1.data collectionNarratives, stories, diaries and other written texts submitted by e-mail messages. element version 1.data collectionNarratives, stories, diaries and other written texts created and collected in paper form. element version 1.data collectionNarratives, stories, diaries and other written texts gathered from Internet sources, e.g. websites, blogs, discussion forums.element version 1.data collectionResearch method that involves collecting data as they occur (for example, observing behaviors, events, etc.), without attempting to manipulate any of the independent variables. element version 1.data collectionObservation that is conducted in a natural environment. element version 1.data collectionType of field observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation.element version 1.data collectionObservation that is conducted in a natural, non-controlled setting without any interaction between the researcher and his/her subjects. element version 1.data collectionObservation that is conducted in a controlled, artificially created setting. Example: Observation of children’s play in a laboratory playroom. element version 1.data collectionType of laboratory observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation. Example: Observation of children’s play in a laboratory playroom with the researcher taking part in the play. element version 1.data collectionType of laboratory observation that is conducted without any interaction between the researcher and his/her subjects.element version 1.data collectionType of observation in which data regarding computer usage are being collected by software (like cookies, etc.) that is built into, or applied to local, or online computer programs. Information may be collected about the ways in which users interact with the programs, how much time they spend on a page, how they use specific sections of applications, how they navigate from page to page or from one application to another, etc.element version 1.data collectionResearch method involving the manipulation of some or all of the independent variables included in the hypotheses. element version 1.data collectionAn experiment conducted in a controlled, artificially created physical setting, in which a researcher manipulates one or several independent variables and measures its/their effect on the dependent variable.element version 1.data collectionAn experiment conducted in a natural, uncontrolled setting, in which the researcher manipulates one or several independent variables. Intervention/clinical studies are one example of field experiments. element version 1.data collectionAn experiment conducted in the virtual setting of the World Wide Web, in which experimental materials are programmed to implement artificial situations or events to be investigated in a distributed environment.(Reips, U.-D. (2002). Theory and techniques of Web experimenting. In B. Batinic, U.-D. Reips, & M. Bosnjak (Eds.), Online Social Sciences. Seattle: Hogrefe & Huber. Available: http://www.websm.org/uploadi/editor/Reips_2002_Theory_and_techniques.pdf [07 June 2013]) element version 1.data collectionRegistering by mechanical or electronic means, in a form that allows the information to be retrieved and/or reproduced. For example, images or sounds on disc or magnetic tape. element version 1.data collectionAs a mode of secondary data collection, content coding applies coding techniques to transform qualitative data (textual, video, audio or still-image) originally produced for other purposes into quantitative data (expressed in unit-by-variable matrices) in accordance with pre-defined categorization schemes. Example: coded party manifesto data like the "European Parliament Election Study 2009, Manifesto Study" (doi:10.4232/1.10204)"element version 1.data collectionCapturing information in writing from a different source, or from a different medium, alphabet, or form of notation, like scientific formulae, or musical notes. For transcribed interviews or observations, it is recommended to document the primary mode of collection, using one of the interview or observation terms. element version 1.data collectionCollecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.element version 1.data collectionPresentation of information in a condensed form, by reducing it to its main points. Example: Abstracts of interviews or reports are published and used as data rather than the full-length interviews or reports. element version 1.data collectionStatistics that relate to broad classes, groups, or categories. The data are averaged, totaled, or otherwise derived from individual-level data, and it is no longer possible to distinguish the characteristics of individuals within those classes, groups, or categories. For example, the number and age group of the unemployed in specific geographic regions, or national level statistics on the occurrence of specific offences, originally derived from the statistics of individual police districts. element version 1.data collectionModeling or imitative representation of real-world processes, events, or systems, often using computer programs. For example, a program modeling household consumption responses to indirect tax changes; or a dataset on hypothetical patients and their drug exposure, background conditions, and known adverse events. element version 1.data collectionAssessing specific properties (or characteristics) of beings, things, phenomena, (and/ or processes) by applying pre-established standards and/or specialized instruments or techniques. element version 1.data collectionAssessment of knowledge, skills, aptitude, or educational achievement by means of specialized measures or tests.element version 1.data collectionAssessment of physical properties of living beings, objects, materials, or natural phenomena. For example, blood pressure, heart rate, body weight and height, as well as time, distance, mass, temperature, force, power, speed, GPS data on physical movement and other physical parameters or variables, like geospatial data. element version 1.data collectionAssessment of personality traits or psychological/behavioral responses by means of specialized measures or tests. For example, objective tests like self-report measures with a restricted response format, or projective methods allowing free responses, including word association, sentence or story completion, vignettes, cartoon test, thematic apperception tests, role play, drawing tests, inkblot tests, choice ordering exercises, etc. element version 1.data collectionUse if the mode of data collection is known, but not found in the list.element version 1.reusable Whole numbers, the infinite set of integers, no minimum or maximum value. An integer datatype corresponding to the W3C XML Schema's xs:integer datatype.element version 1.reusable Whole numbers in the range -2147483648 .. 2147483647. An integer datatype corresponding to the W3C XML Schema's xs:int datatype.element version 1.reusable Whole numbers in the range -9223372036854775808 .. 9223372036854775807. A numeric datatype corresponding to the W3C XML Schema's xs:long datatype.element version 1.reusable Whole numbers in the range -32768 .. 32767. A numeric datatype corresponding to the W3C XML Schema's xs:short datatype.element version 1.reusable A subset of real numbers, which can be represented by a finite-length sequence of decimal digits (0-9) separated by a period as a decimal indicator. An optional leading sign is allowed. If the sign is omitted, "+" is assumed. Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero(es) can be omitted. For example: -1.23, 12678967.543233, +100000.00, 210. A numeric datatype corresponding to the W3C XML Schema's xs:decimal datatype.element version 1.reusableelement version 1.reusable Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.element version 1.reusable Ordinal number of objects in a finite set, discrete. A simple incrementing Integer type. When using in DDI-L, the "isSequence" facet must be set to true, and the "interval" facet must be set to "1".element version 1.reusable A value that increases continuously and infinitely by a given amount. Use of this term in DDI-L indicates that the value increases by the amount provided in the "interval" facet; the "isSequence" facet will be set to "true".element version 1.reusable Use if the numeric type is known, but not found in the list.element version 1.datacollectionUnit of response is same as unit of observation/analysis.element version 1.datacollectionUnit of response is different than the unit of observation as part of the study design, and the identity of the response unit is also pre-determined by the study design. Such studies are actually called "informant surveys" and they involve, for instance, obtaining information about a community from certain select members who hold specific information, like church leaders, business owners or leaders, physicians, school teachers, civic leaders, etc. Or, if a business or organization is the unit of observation, information may be sought at different administrative/professional levels, etc.element version 1.datacollectionUnit of response is different than the unit of analysis because the sampled unit is unavailable/unable to participate. Proxies may be allowed by the study design, but their identity is not specifically designated (for example, anyone in the household can provide information about another household member, or any available student can provide information about another student, etc.).

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for float. A numeric datatype corresponding to the W3C XML Schema's xs:float datatype.

element version 1.datacollectionData are entered directly by the interviewer, as a result of his/her own observations, and not by eliciting answers to a question.element version 1.datacollectionUse if the response unit is known, but not found in the list. element version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusable Data interchange format suitable for use in Excelelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusableelement version 1.reusable

element version 1.reusableelement version 1.reusable Use if the software package is known, but not found in the list. element version 1.physicalinstanMathematical average of a set of values. The mean is calculated by adding up two or more values and dividing the total by their number. In social/political science, it is usually the sum of the measurements divided by the number of subjects, or cases.element version 1.physicalinstanAverage value of all data if extracting the nth root of the product of all (n) values. Rarely used in social sciences.element version 1.physicalinstanAverage value of all data if calculating the reciprocal of the arithmetic mean of the reciprocal of values. Rarely used in social sciences.element version 1.physicalinstanThe (arithmetic) mean calculated after discarding given parts of observations at the high and low end (e.g., interquartile mean when the lowest 25% and the highest 25% are discarded, and the mean of the remaining values is calculated).element version 1.physicalinstanThe Standard Error for the mean value.element version 1.physicalinstanThe most frequently observed data value (Statistics Canada).element version 1.physicalinstanThe values below which, and above which, half of the values in a distribution fall (50th percentile).element version 1.physicalinstanCases with observations which are considered to be valid, i.e., providing substantial information and to be included for calculation.element version 1.physicalinstanCases which are considered/defined as "missing" (e.g., not ascertained, not applicable, etc.), usually excluded from calculation.element version 1.physicalinstanThe lowest valid value in a variable.element version 1.physicalinstanThe highest valid value in a variable.element version 1.physicalinstanThe range of valid values, i.e., all values that fall between the lowest and highest valid values.element version 1.physicalinstanThe sum or total of the values, across all valid cases.element version 1.physicalinstanThe variance is the mean square deviation of the variable around the average value. It reflects the dispersion of a frequency distribution around its mean (OECD Glossary of Statistics).element version 1.physicalinstanThe positive square root of the variance. The most widely used measure of dispersion of a frequency distribution.element version 1.physicalinstanStandard deviation divided by the mean.element version 1.physicalinstanThe average of the absolute differences between each value and the overall mean. Measure of statistical dispersion around the mean, alternative to Standard Deviation.element version 1.physicalinstanThe median absolute deviation from the median. Measure of statistical dispersion around the median.element version 1.physicalinstanThe first of three values which separate the total frequency of a distribution into four equal parts.element version 1.physicalinstanThe second of three values which separate the total frequency of a distribution into four equal parts (= median).element version 1.physicalinstanThe third of three values which separate the total frequency of a distribution into four equal parts.element version 1.physicalinstanThe range between the first and third quartile values.element version 1.physicalinstanThe first of four values which separate the total frequency of a distribution into five equal parts.element version 1.physicalinstanThe second of four values which separate the total frequency of a distribution into five equal parts.element version 1.physicalinstanThe third of four values which separate the total frequency of a distribution into five equal parts.element version 1.physicalinstanThe fourth of four values which separate the total frequency of a distribution into five equal parts.element version 1.physicalinstanThe range between the first and fourth quintile values.element version 1.physicalinstanThe first of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe second of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe third of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe fourth of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe fifth of nine values which separate the total frequency of a distribution into ten equal parts (= median).element version 1.physicalinstanThe sixth of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe seventh of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe eighth of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe ninth of nine values which separate the total frequency of a distribution into ten equal parts.element version 1.physicalinstanThe range between the first and ninth decile values.element version 1.physicalinstanA percentile not covered by any of the other percentile terms.element version 1.physicalinstanA measure for the asymmetry of a probability distribution of a variable.element version 1.physicalinstanA measure for the "peakedness" of a probability distribution of a variable.element version 1.physicalinstanNormality test statistics.element version 1.physicalinstanIndicates the percentage of valid cases of the total number of cases.element version 1.physicalinstanIndicates the percentage of invalid cases of the total number of cases.element version 1.physicalinstanUse if the summary statistic type is known, but not found in the list.element version 1.data collectionData collected repeatedly over time to study change in a population.element version 1.data collectionData collected over time about a group of individuals that are connected in some way or have shared some significant experience within a given period. Examples: birth, disease, education, employment, family formation, participation in an event.

element version 1.data collectionStudies different samples/different groups of people from the same population at several points in time, using the same set of questions/variables. Conclusions are drawn for the population. Examples: public opinion polls, elections studies, etc.element version 1.data collectionData collected over time from, or about, the same sample of respondents.element version 1.data collectionReports from the panel are collected on a regular basis.element version 1.data collectionMeasurements are taken only when information is needed.element version 1.data collectionData collected repeatedly over time to study change in observations. These are typically "objective" measurements of phenomena that can be observed externally, as opposed to attitudes/opinions or feelings. Examples may include economic/financial indicators, natural/meteorological phenomena, vital statistics, etc.element version 1.data collectionPhenomena are measured at every instant in time. Examples: lie detectors, electrocardiograms, etc.element version 1.data collectionMeasurements are taken at (usually regularly) spaced intervals. Examples: macroeconomics (weekly share prices, monthly profits, sales); meteorology (hourly temperature); measurements of individuals (blood pressure, weight, height); sociology (crime figures, employment figures), etc.element version 1.data collectionCross-sectional data is data collected by observing subjects at the same point in time, or without regard to differences in time. Analysis of cross-sectional data usually consists in comparing the differences among subjects, but is not focused on studying change over time (adapted from Wikipedia).element version 1.data collectionData collected at one point in time to complete information collected in a previous cross-sectional study; the decision to collect follow-up data is not included in the study design.element version 1.data collectionUse if the time method is known, but not found in the list.element version 1.reusable Baker Island, Howland Island (both uninhabited)element version 1.reusable Samoa Standard Time (SST)element version 1.reusable Hawaii Standard Time (HST)element version 1.reusable Marquesas Time (MART)element version 1.reusable Alaska Standard Time (AKST)element version 1.reusable Pacific Standard Time (PST)element version 1.reusable Mountain Standard Time (North America) (MST)element version 1.reusable Central Standard Time (North and Central Americas) (CST)element version 1.reusable Eastern Standard Time (North and Central Americas, Caribbean) (EST)element version 1.reusable Venezuelan Standard Time (VET)element version 1.reusable Atlantic Standard Time (North America, Caribbean) (AST)element version 1.reusable Newfoundland Standard Time (NST)element version 1.reusable West Greenland Time (WGT)element version 1.reusable Fernando de Noronha Time (FNT)element version 1.reusable Central African Time (CAT)element version 1.reusable Universal Coordinated Time (UTC) / Greenwich Mean Time (GMT)element version 1.reusable European Central Time (ECT)element version 1.reusable Eastern European Time (EET), (Arabic) Egypt Standard Time (ART)element version 1.reusable Eastern African Time (EAT)element version 1.reusable Middle East Time (MET)element version 1.reusable Near East Time (NET)element version 1.reusable Afganistan Time (AFT)element version 1.reusable Pakistan Lahore Time (PLT)element version 1.reusable India Standard Time (IST)element version 1.reusable Nepal Time (NPT)element version 1.reusable Bangladesh Standard Time (BST)element version 1.reusable Cocos Islands Time (CCT)element version 1.reusable Vietnam Standard Time (VST)element version 1.reusable China Taiwan Time (CTT)element version 1.reusable Japan Standard Time (JST)element version 1.reusable Australia Central Time (ACT)element version 1.reusable Australia Eastern Time (AET)element version 1.reusable Lord Howe Standard Time (LHST)element version 1.reusable Solomon Standard Time (SST)element version 1.reusable Norfolk Time (Australia) (NFT)element version 1.reusable New Zealand Standard Time (NZST)element version 1.reusable Chatham Island Standard Time (CHAST)element version 1.reusable West Samoa Time (WST)

element version 1.reusable Line Islands Time (LINT)element version 1.reusable Use if Time Zone is known, but not found in the list; enter new code in the same format used in this list, i.e., ±xx:xx as an offset from UTC.

1 degree equals 106895m0.9354974507694466532578698723046 degrees equals 100000mN/S or E/W at equator: 1113.2; E/W at 23N/S: 1024.7N/S or E/W at equator: 111.32; E/W at 23N/S: 102.47N/S or E/W at equator: 11.132; E/W at 23N/S: 10.247N/S or E/W at equator: 1.1132; E/W at 23N/S: 1.0247N/S or E/W at equator: 0.11132; E/W at 23N/S: 0.10247N/S or E/W at equator: 0.011132; E/W at 23N/S: 0.010247

Level1 Level2 Level3 Level4 Level5

Formal analysisMethodology

Writing – review & editingWriting – original draft

Project administration Software

ValidationVisualization

Investigation

explains the content of the data (actual scientific metadata)refers to metadata that describe the technical handling of datarelates to the origin of the data, and ranges from the human to the highly technical. Where did the data come from? Why was it collected? Who collected it, when and where? What instruments/technologies were used to collect the data, and how were they set up? What has been done to the data since it was collected?provides information about access and usage rules.Who is allowed to view, edit or otherwise modify the data, or the metadata, and under what conditions? Who has some kind of authority over the data? Who has the authority to change the rules? Are there costs associated with access? Who has accessed the data, and what have they in turn done with it? Under what licence is the data being made available?used to record and facilitate relationships between or within digital resources. How is the data set up? What formats, and versions of formats, are used? How is the database configured? How does it relate to other data?includes information to help build a sense of trust in the data, and allow for the data to be used long into the future. Is the data authentic, authoritative, and original? Has there been any restructuring, e.g. due to software and file-formats changing? What software has been used to access the data in the past?metadata collected from or about the users themselves (e.g. user annotations, number of people accessing a particular resource)provides fundamental information for a person or a computer to read the data. How is the data set up? What formats, and versions of formats, are used? How is the database configured? How does it relate to other data?If individual values of a certain information (usually organized In a column) are described by the metadata fieldIf information about the entity (usually organized In a table) are described by the metadata fieldIf information about interconnected tables (usually organized In a relational database) are described by the metadata fieldThe adoption rate will be MUCH higher on large farmsThe adoption rate will be MUCH higher when it can be applied on a large scale (e.g. cost will decrease drastically when applied at large scale)The farmers do not trust the solution since it is new to themFarmers are reluctant because the investment could be lost due to other factors such as rainfall, pests, diseases and timely access to critical inputs

Practical training will have a decisive impact on adoption ratesLabor availability will have a big impact on adoption ratesAccess to financial services will have a big impact on adoption ratesLand ownership is an important prerequisite to benefit from technologyAccessibility inputs will have a great influence on the adoption of technologyAvailability of professional services (veterinarians, mechanics, welders, ..) is an important prerequisite for high adoption rates.

The number of parts out of 100. In mathematics, a percentage is a number of ratio expressed as a fraction of 100. Percentages are used to express how large one quantity is relative to another quantity.The total of a frequency and all frequencies below it in a frequency distribution; the "running total" of frequencies [the maximum value is 100%].The percentile rank of a item is the percentage of items in its frequency distribution which are lower [cannot reach 100%].Use when the aggregation method is known, but not found in the list.Any individual person, irrespective of demographic characteristics, professional, social or legal status, or affiliation.Any kind of formal administrative and functional structure - includes associations, institutions, agencies, businesses, political parties, schools, etc.Two or more people related by blood, marriage (including step-relations), adoption or fostering and who may or may not live together (National Community Services Data Dictionary, Vers 3, AIHW, 2004). For example, used when researching the extent to which people provide support and assistance for their relatives.A more specific term, refers only to related people who live in the same household at a point in time. If not known whether the analysis unit is "Family" or "Household family", use "Family".A person or a group of persons who share the same dwelling unit and common living arrangements. These common living arrangements may include pooling some, or all, of their income and wealth, and consuming certain types of goods and services collectively, mainly housing and food (Eurostat).U.S. Census: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from the outside of the building or through a common hall.Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.Any entity that can be spatially defined as a geographic area, with either natural (physical) or administrative boundaries.

Any period of time: year, week, month, day, or bimonthly or quarterly periods, etc.

Two or more individuals assembled together or having some unifying relationship.

The middle value in a series of values arranged sequentially from smallest to largest.

Anything material, but inanimate, that has an independent existence and may be perceived by the senses. Examples: objects of art (paintings, sculptures, etc.) or weapons, or vehicles, etc.Use if the unit of analysis is known, but not found in the list.The official name is US-ASCII but use the format: ASCII. The ISO code for ASCII is ISO 14962.For ISO standards, use format: ISO-n-n in Caption and ISOnn in Code. ISO standards are also known as Latin, for example, ISO-8859-1 as Latin1.

For Unicode Transformation Formats, use format: UTF-n in Caption and UTFn in Code.

For MS-Windows character sets, use format: Windows-n in Caption and Windowsn in Code.

Use if the character set is not known, for example for some proprietary data files.Use if the character set is known, but not found in the list.Use when the compared items have identical content. For variables, for example, all the elements of a variable description (name, label, question text, category values and codes, universe, concept) will be identical in form.Use when the compared items have similar but not identical content. For variables, for example, some of the elements of a variable description (name, label, question text, category values and codes, universe, concept) will be identical in form, while others will be different.Normally not used, as it would not be expected to compare items that have nothing in common. This term was necessary to complete the commonality range, and may be used in special cases, as determined by user needs (for instance, when comparability was expected, but not found).

TextTextNumericNumericNumericNumericNumericNumericNumericNumericNumericNumericNumeric

NumericNumericNumericNumericNumericNumericDateDateDateDateDateDateDateDateDate

Even-lengthed sequence of hexadecimal digits representing an N × 8-bit integer.Sequence of multiples of four base64 digits, where each 4-tuple represents a 24-bit integer. Each digit (a-z, A-Z, 0-9, +, /) represents a 6-bit integer between 0 and 63.

URIOther

Amending the metadata to reflect changes in the data or to improve or enhance documentation.

Complete account on how the study was conducted through all its stages, often required by funders or other administrative bodies.Analysis of how the study, in all its stages, was managed and/or conducted, including the outcome of methodological, technical, and business decisions. May serve as a basis for changes or improvements in planning future iterations of the data collection, or entirely new projects.First release of data and/or metadata to other individuals and/or agencies than the study producers.Handing over the data and available metadata (Submission Information Package in OAIS terms) to a data archive or repository for preservation, possible further processing, and dissemination.Producing a preservation package of the data for archiving purposes (Archival Information Package in OAIS terms).Producing a dissemination package for distribution of the data (Dissemination Information Package in OAIS terms).Publishing or otherwise making the dissemination package available to users.Reports describing how the data were analyzed, as well as the resulting findings. These may take the form of conference posters or presentations, journal articles or online publications, books, book chapters, etc.Publishing or otherwise making a new version of the data and/or metadata available to users.Use if the event type is known, but not found in the list. A pre-planned communication between two (or more) people - the interviewer(s) and the interviewee(s) - in which information is obtained by the interviewer(s) from the interviewee(s). If group interaction is part of the method, use “Focus group”. Data collection method in which a live interviewer conducts a personal interview, presenting questions and entering the responses. Use this broader term if not CAPI or PAPI, or if not known whether CAPI /PAPI or not.Computer-assisted personal interviewing. Data collection method in which the interviewer reads questions to the respondents from a computer's screen and keys in the answers. The administration of the interview is managed by a specifically designed program. Paper-and-pencil interviewing. The interviewer uses a traditional paper questionnaire to read the questions and enter the answers. Interview administered on the telephone. Use this broader term if not CATI, or if not known whether CATI or not. Computer-assisted telephone interviewing. The interviewer asks questions as directed by a computer, responses are keyed directly into the computer and the administration of the interview is managed by a specifically designed program. Interviews conducted via e-mail, usually consisting of several e-mail messages that allow the discussion to continue beyond the first set of questions and answers, or the first e-mail exchange. An interview conducted via the Internet. Examples include interviews conducted within online forums or using web-based audio-visual technology enabling the interviewer(s) and interviewee(s) to communicate in real time. Data collection method in which the respondent reads, or listens to the questions, and enters the responses by him/herself; no live interviewer is present, or participates in the questionnaire administration. If possible, use a narrower term.The questionnaire is not interactive and remains the same regardless of the responses given to prior questions. Use the broader term if the method is not described by any of the narrower terms. For example, for PDF and diskette questionnaires. Questions are presented to the respondent in the text body of an e-mail, not as an attached electronic questionnaire or as a link to a web-based questionnaire. Self-administered survey using a traditional paper questionnaire delivered and/or collected by mail (postal services), by fax, or in person by either interviewer, or respondent. The questions and answers are incorporated in SMS (text messages) or MMS (messages including multimedia content) sent to, and from mobile phones. Data are collected using a Web questionnaire that is fixed (not interactive).Self-administered questionnaire in which the question sequence is not fixed, being managed by computer software. Some of the questions, as well as the order in which they are asked, are contingent to responses given to previous questions. Computer-assisted self-interview. Data collection method in which the respondents enter their own answers directly into a computer (desktop, laptop, Palm/PDA, etc.). The administration of the questionnaire is managed by a specifically designed program, but there is no real-time data transfer, as in the case of CAWI: the answers are stored on the computer used for the interview. Use CASI if not known whether VCASI, ACASI, or TACASI. Video computer-assisted self-interview. Earliest method of computer-assisted self-interviewing, in which respondents view the questions on a computer screen and typically enter answers using the computer keyboard, mouse, or touchscreen. (Thomas Harmon, et al. “Impact of T-ACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280)

Audio computer-assisted self-interview. Data are collected by using a recorded voice into a computer-assisted self-interview. The text of each question and its answer alternatives are displayed on the computer screen, while a pre-recorded interviewer’s voice reads these to the respondent, who listens privately through headphones. Respondents answer by selecting the appropriate response on the keyboard or directly on the computer screen. Sometimes referred to as audio-visual CASI (AVCASI). (adapted from https://syrp.org/images/ACASI_Insert_Singles.pdf) Telephone audio computer-assisted self-interview. TACASI adds telephone capabilities to a standard audio-CASI system, thereby allowing ACASI interviews to be conducted over the telephone, with the telephone’s touchtone keypad serving as the input device. (Thomas Harmon, et al. “Impact of TACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280) Computer-assisted Web interview. The administration of the questionnaire completion is managed by a specifically designed program. Questions can be tailored to previous question responses, enabling routing plans. Answers are stored directly on the main database which is accessible through the Web, using a password-secured webpage.A group discussion on a particular topic, organized for research purposes. The individuals are selected with relevance to the topic, and interaction among the participants is used as part of the method. The focus group participants meet in person to conduct the discussion. The focus group discussion is conducted over the telephone. The focus group discussion is conducted over the Internet in an interactive manner. Narratives, stories, diaries and other personal written texts.Narratives, stories, diaries and other written texts submitted by e-mail messages. Narratives, stories, diaries and other written texts created and collected in paper form. Narratives, stories, diaries and other written texts gathered from Internet sources, e.g. websites, blogs, discussion forums.Research method that involves collecting data as they occur (for example, observing behaviors, events, etc.), without attempting to manipulate any of the independent variables. Observation that is conducted in a natural environment. Type of field observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation.Observation that is conducted in a natural, non-controlled setting without any interaction between the researcher and his/her subjects. Observation that is conducted in a controlled, artificially created setting. Example: Observation of children’s play in a laboratory playroom. Type of laboratory observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation. Example: Observation of children’s play in a laboratory playroom with the researcher taking part in the play. Type of laboratory observation that is conducted without any interaction between the researcher and his/her subjects.Type of observation in which data regarding computer usage are being collected by software (like cookies, etc.) that is built into, or applied to local, or online computer programs. Information may be collected about the ways in which users interact with the programs, how much time they spend on a page, how they use specific sections of applications, how they navigate from page to page or from one application to another, etc.Research method involving the manipulation of some or all of the independent variables included in the hypotheses. An experiment conducted in a controlled, artificially created physical setting, in which a researcher manipulates one or several independent variables and measures its/their effect on the dependent variable.An experiment conducted in a natural, uncontrolled setting, in which the researcher manipulates one or several independent variables. Intervention/clinical studies are one example of field experiments. An experiment conducted in the virtual setting of the World Wide Web, in which experimental materials are programmed to implement artificial situations or events to be investigated in a distributed environment.(Reips, U.-D. (2002). Theory and techniques of Web experimenting. In B. Batinic, U.-D. Reips, & M. Bosnjak (Eds.), Online Social Sciences. Seattle: Hogrefe & Huber. Available: http://www.websm.org/uploadi/editor/Reips_2002_Theory_and_techniques.pdf [07 June 2013]) Registering by mechanical or electronic means, in a form that allows the information to be retrieved and/or reproduced. For example, images or sounds on disc or magnetic tape. As a mode of secondary data collection, content coding applies coding techniques to transform qualitative data (textual, video, audio or still-image) originally produced for other purposes into quantitative data (expressed in unit-by-variable matrices) in accordance with pre-defined categorization schemes. Example: coded party manifesto data like the "European Parliament Election Study 2009, Manifesto Study" (doi:10.4232/1.10204)"Capturing information in writing from a different source, or from a different medium, alphabet, or form of notation, like scientific formulae, or musical notes. For transcribed interviews or observations, it is recommended to document the primary mode of collection, using one of the interview or observation terms. Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.Presentation of information in a condensed form, by reducing it to its main points. Example: Abstracts of interviews or reports are published and used as data rather than the full-length interviews or reports. Statistics that relate to broad classes, groups, or categories. The data are averaged, totaled, or otherwise derived from individual-level data, and it is no longer possible to distinguish the characteristics of individuals within those classes, groups, or categories. For example, the number and age group of the unemployed in specific geographic regions, or national level statistics on the occurrence of specific offences, originally derived from the statistics of individual police districts. Modeling or imitative representation of real-world processes, events, or systems, often using computer programs. For example, a program modeling household consumption responses to indirect tax changes; or a dataset on hypothetical patients and their drug exposure, background conditions, and known adverse events. Assessing specific properties (or characteristics) of beings, things, phenomena, (and/ or processes) by applying pre-established standards and/or specialized instruments or techniques. Assessment of knowledge, skills, aptitude, or educational achievement by means of specialized measures or tests.Assessment of physical properties of living beings, objects, materials, or natural phenomena. For example, blood pressure, heart rate, body weight and height, as well as time, distance, mass, temperature, force, power, speed, GPS data on physical movement and other physical parameters or variables, like geospatial data. Assessment of personality traits or psychological/behavioral responses by means of specialized measures or tests. For example, objective tests like self-report measures with a restricted response format, or projective methods allowing free responses, including word association, sentence or story completion, vignettes, cartoon test, thematic apperception tests, role play, drawing tests, inkblot tests, choice ordering exercises, etc. Use if the mode of data collection is known, but not found in the list.Whole numbers, the infinite set of integers, no minimum or maximum value. An integer datatype corresponding to the W3C XML Schema's xs:integer datatype.Whole numbers in the range -2147483648 .. 2147483647. An integer datatype corresponding to the W3C XML Schema's xs:int datatype.Whole numbers in the range -9223372036854775808 .. 9223372036854775807. A numeric datatype corresponding to the W3C XML Schema's xs:long datatype.Whole numbers in the range -32768 .. 32767. A numeric datatype corresponding to the W3C XML Schema's xs:short datatype.A subset of real numbers, which can be represented by a finite-length sequence of decimal digits (0-9) separated by a period as a decimal indicator. An optional leading sign is allowed. If the sign is omitted, "+" is assumed. Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero(es) can be omitted. For example: -1.23, 12678967.543233, +100000.00, 210. A numeric datatype corresponding to the W3C XML Schema's xs:decimal datatype.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.Ordinal number of objects in a finite set, discrete. A simple incrementing Integer type. When using in DDI-L, the "isSequence" facet must be set to true, and the "interval" facet must be set to "1".A value that increases continuously and infinitely by a given amount. Use of this term in DDI-L indicates that the value increases by the amount provided in the "interval" facet; the "isSequence" facet will be set to "true".Use if the numeric type is known, but not found in the list.Unit of response is same as unit of observation/analysis.Unit of response is different than the unit of observation as part of the study design, and the identity of the response unit is also pre-determined by the study design. Such studies are actually called "informant surveys" and they involve, for instance, obtaining information about a community from certain select members who hold specific information, like church leaders, business owners or leaders, physicians, school teachers, civic leaders, etc. Or, if a business or organization is the unit of observation, information may be sought at different administrative/professional levels, etc.Unit of response is different than the unit of analysis because the sampled unit is unavailable/unable to participate. Proxies may be allowed by the study design, but their identity is not specifically designated (for example, anyone in the household can provide information about another household member, or any available student can provide information about another student, etc.).

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for float. A numeric datatype corresponding to the W3C XML Schema's xs:float datatype.

Data are entered directly by the interviewer, as a result of his/her own observations, and not by eliciting answers to a question.Use if the response unit is known, but not found in the list.

Use if the software package is known, but not found in the list. Mathematical average of a set of values. The mean is calculated by adding up two or more values and dividing the total by their number. In social/political science, it is usually the sum of the measurements divided by the number of subjects, or cases.Average value of all data if extracting the nth root of the product of all (n) values. Rarely used in social sciences.Average value of all data if calculating the reciprocal of the arithmetic mean of the reciprocal of values. Rarely used in social sciences.The (arithmetic) mean calculated after discarding given parts of observations at the high and low end (e.g., interquartile mean when the lowest 25% and the highest 25% are discarded, and the mean of the remaining values is calculated).

The most frequently observed data value (Statistics Canada).The values below which, and above which, half of the values in a distribution fall (50th percentile).Cases with observations which are considered to be valid, i.e., providing substantial information and to be included for calculation.Cases which are considered/defined as "missing" (e.g., not ascertained, not applicable, etc.), usually excluded from calculation.

The range of valid values, i.e., all values that fall between the lowest and highest valid values.

The variance is the mean square deviation of the variable around the average value. It reflects the dispersion of a frequency distribution around its mean (OECD Glossary of Statistics).The positive square root of the variance. The most widely used measure of dispersion of a frequency distribution.

The average of the absolute differences between each value and the overall mean. Measure of statistical dispersion around the mean, alternative to Standard Deviation.The median absolute deviation from the median. Measure of statistical dispersion around the median.The first of three values which separate the total frequency of a distribution into four equal parts.The second of three values which separate the total frequency of a distribution into four equal parts (= median).The third of three values which separate the total frequency of a distribution into four equal parts.The range between the first and third quartile values.The first of four values which separate the total frequency of a distribution into five equal parts.The second of four values which separate the total frequency of a distribution into five equal parts.The third of four values which separate the total frequency of a distribution into five equal parts.The fourth of four values which separate the total frequency of a distribution into five equal parts.The range between the first and fourth quintile values.The first of nine values which separate the total frequency of a distribution into ten equal parts.The second of nine values which separate the total frequency of a distribution into ten equal parts.The third of nine values which separate the total frequency of a distribution into ten equal parts.The fourth of nine values which separate the total frequency of a distribution into ten equal parts.The fifth of nine values which separate the total frequency of a distribution into ten equal parts (= median).The sixth of nine values which separate the total frequency of a distribution into ten equal parts.The seventh of nine values which separate the total frequency of a distribution into ten equal parts.The eighth of nine values which separate the total frequency of a distribution into ten equal parts.The ninth of nine values which separate the total frequency of a distribution into ten equal parts.

A percentile not covered by any of the other percentile terms.A measure for the asymmetry of a probability distribution of a variable.A measure for the "peakedness" of a probability distribution of a variable.

Indicates the percentage of valid cases of the total number of cases.Indicates the percentage of invalid cases of the total number of cases.Use if the summary statistic type is known, but not found in the list.Data collected repeatedly over time to study change in a population.Data collected over time about a group of individuals that are connected in some way or have shared some significant experience within a given period. Examples: birth, disease, education, employment, family formation, participation in an event.

Studies different samples/different groups of people from the same population at several points in time, using the same set of questions/variables. Conclusions are drawn for the population. Examples: public opinion polls, elections studies, etc.Data collected over time from, or about, the same sample of respondents.Reports from the panel are collected on a regular basis.Measurements are taken only when information is needed.Data collected repeatedly over time to study change in observations. These are typically "objective" measurements of phenomena that can be observed externally, as opposed to attitudes/opinions or feelings. Examples may include economic/financial indicators, natural/meteorological phenomena, vital statistics, etc.Phenomena are measured at every instant in time. Examples: lie detectors, electrocardiograms, etc.Measurements are taken at (usually regularly) spaced intervals. Examples: macroeconomics (weekly share prices, monthly profits, sales); meteorology (hourly temperature); measurements of individuals (blood pressure, weight, height); sociology (crime figures, employment figures), etc.Cross-sectional data is data collected by observing subjects at the same point in time, or without regard to differences in time. Analysis of cross-sectional data usually consists in comparing the differences among subjects, but is not focused on studying change over time (adapted from Wikipedia).Data collected at one point in time to complete information collected in a previous cross-sectional study; the decision to collect follow-up data is not included in the study design.Use if the time method is known, but not found in the list.

Central Standard Time (North and Central Americas) (CST)Eastern Standard Time (North and Central Americas, Caribbean) (EST)

Atlantic Standard Time (North America, Caribbean) (AST)

Universal Coordinated Time (UTC) / Greenwich Mean Time (GMT)

Eastern European Time (EET), (Arabic) Egypt Standard Time (ART)

Use if Time Zone is known, but not found in the list; enter new code in the same format used in this list, i.e., ±xx:xx as an offset from UTC.

0.9354974507694466532578698723046 degrees equals 100000m

N/S or E/W at equator: 0.11132; E/W at 23N/S: 0.10247N/S or E/W at equator: 0.011132; E/W at 23N/S: 0.010247

relates to the origin of the data, and ranges from the human to the highly technical. Where did the data come from? Why was it collected? Who collected it, when and where? What instruments/technologies were used to collect the data, and how were they set up? What has been done to the data since it was collected?provides information about access and usage rules.Who is allowed to view, edit or otherwise modify the data, or the metadata, and under what conditions? Who has some kind of authority over the data? Who has the authority to change the rules? Are there costs associated with access? Who has accessed the data, and what have they in turn done with it? Under what licence is the data being made available?used to record and facilitate relationships between or within digital resources. How is the data set up? What formats, and versions of formats, are used? How is the database configured? How does it relate to other data?includes information to help build a sense of trust in the data, and allow for the data to be used long into the future. Is the data authentic, authoritative, and original? Has there been any restructuring, e.g. due to software and file-formats changing? What software has been used to access the data in the past?

provides fundamental information for a person or a computer to read the data. How is the data set up? What formats, and versions of formats, are used? How is the database configured? How does it relate to other data?

The number of parts out of 100. In mathematics, a percentage is a number of ratio expressed as a fraction of 100. Percentages are used to express how large one quantity is relative to another quantity.

Two or more people related by blood, marriage (including step-relations), adoption or fostering and who may or may not live together (National Community Services Data Dictionary, Vers 3, AIHW, 2004). For example, used when researching the extent to which people provide support and assistance for their relatives.A more specific term, refers only to related people who live in the same household at a point in time. If not known whether the analysis unit is "Family" or "Household family", use "Family".A person or a group of persons who share the same dwelling unit and common living arrangements. These common living arrangements may include pooling some, or all, of their income and wealth, and consuming certain types of goods and services collectively, mainly housing and food (Eurostat).U.S. Census: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from the outside of the building or through a common hall.Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.

Anything material, but inanimate, that has an independent existence and may be perceived by the senses. Examples: objects of art (paintings, sculptures, etc.) or weapons, or vehicles, etc.

Use when the compared items have identical content. For variables, for example, all the elements of a variable description (name, label, question text, category values and codes, universe, concept) will be identical in form.Use when the compared items have similar but not identical content. For variables, for example, some of the elements of a variable description (name, label, question text, category values and codes, universe, concept) will be identical in form, while others will be different.Normally not used, as it would not be expected to compare items that have nothing in common. This term was necessary to complete the commonality range, and may be used in special cases, as determined by user needs (for instance, when comparability was expected, but not found).

Sequence of multiples of four base64 digits, where each 4-tuple represents a 24-bit integer. Each digit (a-z, A-Z, 0-9, +, /) represents a 6-bit integer between 0 and 63.

Analysis of how the study, in all its stages, was managed and/or conducted, including the outcome of methodological, technical, and business decisions. May serve as a basis for changes or improvements in planning future iterations of the data collection, or entirely new projects.

Handing over the data and available metadata (Submission Information Package in OAIS terms) to a data archive or repository for preservation, possible further processing, and dissemination.

Reports describing how the data were analyzed, as well as the resulting findings. These may take the form of conference posters or presentations, journal articles or online publications, books, book chapters, etc.

A pre-planned communication between two (or more) people - the interviewer(s) and the interviewee(s) - in which information is obtained by the interviewer(s) from the interviewee(s). If group interaction is part of the method, use “Focus group”. Data collection method in which a live interviewer conducts a personal interview, presenting questions and entering the responses. Use this broader term if not CAPI or PAPI, or if not known whether CAPI /PAPI or not.Computer-assisted personal interviewing. Data collection method in which the interviewer reads questions to the respondents from a computer's screen and keys in the answers. The administration of the interview is managed by a specifically designed program.

Computer-assisted telephone interviewing. The interviewer asks questions as directed by a computer, responses are keyed directly into the computer and the administration of the interview is managed by a specifically designed program. Interviews conducted via e-mail, usually consisting of several e-mail messages that allow the discussion to continue beyond the first set of questions and answers, or the first e-mail exchange. An interview conducted via the Internet. Examples include interviews conducted within online forums or using web-based audio-visual technology enabling the interviewer(s) and interviewee(s) to communicate in real time. Data collection method in which the respondent reads, or listens to the questions, and enters the responses by him/herself; no live interviewer is present, or participates in the questionnaire administration. If possible, use a narrower term.The questionnaire is not interactive and remains the same regardless of the responses given to prior questions. Use the broader term if the method is not described by any of the narrower terms. For example, for PDF and diskette questionnaires.

Self-administered survey using a traditional paper questionnaire delivered and/or collected by mail (postal services), by fax, or in person by either interviewer, or respondent.

Self-administered questionnaire in which the question sequence is not fixed, being managed by computer software. Some of the questions, as well as the order in which they are asked, are contingent to responses given to previous questions. Computer-assisted self-interview. Data collection method in which the respondents enter their own answers directly into a computer (desktop, laptop, Palm/PDA, etc.). The administration of the questionnaire is managed by a specifically designed program, but there is no real-time data transfer, as in the case of CAWI: the answers are stored on the computer used for the interview. Use CASI if not known whether VCASI, ACASI, or TACASI. Video computer-assisted self-interview. Earliest method of computer-assisted self-interviewing, in which respondents view the questions on a computer screen and typically enter answers using the computer keyboard, mouse, or touchscreen. (Thomas Harmon, et al. “Impact of T-ACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280)

Audio computer-assisted self-interview. Data are collected by using a recorded voice into a computer-assisted self-interview. The text of each question and its answer alternatives are displayed on the computer screen, while a pre-recorded interviewer’s voice reads these to the respondent, who listens privately through headphones. Respondents answer by selecting the appropriate response on the keyboard or directly on the computer screen. Sometimes referred to as audio-visual CASI (AVCASI). (adapted from https://syrp.org/images/ACASI_Insert_Singles.pdf) Telephone audio computer-assisted self-interview. TACASI adds telephone capabilities to a standard audio-CASI system, thereby allowing ACASI interviews to be conducted over the telephone, with the telephone’s touchtone keypad serving as the input device. (Thomas Harmon, et al. “Impact of TACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280) Computer-assisted Web interview. The administration of the questionnaire completion is managed by a specifically designed program. Questions can be tailored to previous question responses, enabling routing plans. Answers are stored directly on the main database which is accessible through the Web, using a password-secured webpage.A group discussion on a particular topic, organized for research purposes. The individuals are selected with relevance to the topic, and interaction among the participants is used as part of the method.

Research method that involves collecting data as they occur (for example, observing behaviors, events, etc.), without attempting to manipulate any of the independent variables.

Type of laboratory observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation. Example: Observation of children’s play in a laboratory playroom with the researcher taking part in the play.

Type of observation in which data regarding computer usage are being collected by software (like cookies, etc.) that is built into, or applied to local, or online computer programs. Information may be collected about the ways in which users interact with the programs, how much time they spend on a page, how they use specific sections of applications, how they navigate from page to page or from one application to another, etc.

An experiment conducted in a controlled, artificially created physical setting, in which a researcher manipulates one or several independent variables and measures its/their effect on the dependent variable.An experiment conducted in a natural, uncontrolled setting, in which the researcher manipulates one or several independent variables. Intervention/clinical studies are one example of field experiments. An experiment conducted in the virtual setting of the World Wide Web, in which experimental materials are programmed to implement artificial situations or events to be investigated in a distributed environment.(Reips, U.-D. (2002). Theory and techniques of Web experimenting. In B. Batinic, U.-D. Reips, & M. Bosnjak (Eds.), Online Social Sciences. Seattle: Hogrefe & Huber. Available: http://www.websm.org/uploadi/editor/Reips_2002_Theory_and_techniques.pdf [07 June 2013]) Registering by mechanical or electronic means, in a form that allows the information to be retrieved and/or reproduced. For example, images or sounds on disc or magnetic tape. As a mode of secondary data collection, content coding applies coding techniques to transform qualitative data (textual, video, audio or still-image) originally produced for other purposes into quantitative data (expressed in unit-by-variable matrices) in accordance with pre-defined categorization schemes. Example: coded party manifesto data like the "European Parliament Election Study 2009, Manifesto Study" (doi:10.4232/1.10204)"Capturing information in writing from a different source, or from a different medium, alphabet, or form of notation, like scientific formulae, or musical notes. For transcribed interviews or observations, it is recommended to document the primary mode of collection, using one of the interview or observation terms. Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.Presentation of information in a condensed form, by reducing it to its main points. Example: Abstracts of interviews or reports are published and used as data rather than the full-length interviews or reports. Statistics that relate to broad classes, groups, or categories. The data are averaged, totaled, or otherwise derived from individual-level data, and it is no longer possible to distinguish the characteristics of individuals within those classes, groups, or categories. For example, the number and age group of the unemployed in specific geographic regions, or national level statistics on the occurrence of specific offences, originally derived from the statistics of individual police districts. Modeling or imitative representation of real-world processes, events, or systems, often using computer programs. For example, a program modeling household consumption responses to indirect tax changes; or a dataset on hypothetical patients and their drug exposure, background conditions, and known adverse events. Assessing specific properties (or characteristics) of beings, things, phenomena, (and/ or processes) by applying pre-established standards and/or specialized instruments or techniques.

Assessment of physical properties of living beings, objects, materials, or natural phenomena. For example, blood pressure, heart rate, body weight and height, as well as time, distance, mass, temperature, force, power, speed, GPS data on physical movement and other physical parameters or variables, like geospatial data. Assessment of personality traits or psychological/behavioral responses by means of specialized measures or tests. For example, objective tests like self-report measures with a restricted response format, or projective methods allowing free responses, including word association, sentence or story completion, vignettes, cartoon test, thematic apperception tests, role play, drawing tests, inkblot tests, choice ordering exercises, etc.

A subset of real numbers, which can be represented by a finite-length sequence of decimal digits (0-9) separated by a period as a decimal indicator. An optional leading sign is allowed. If the sign is omitted, "+" is assumed. Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero(es) can be omitted. For example: -1.23, 12678967.543233, +100000.00, 210. A numeric datatype corresponding to the W3C XML Schema's xs:decimal datatype.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.Ordinal number of objects in a finite set, discrete. A simple incrementing Integer type. When using in DDI-L, the "isSequence" facet must be set to true, and the "interval" facet must be set to "1".A value that increases continuously and infinitely by a given amount. Use of this term in DDI-L indicates that the value increases by the amount provided in the "interval" facet; the "isSequence" facet will be set to "true".

Unit of response is different than the unit of observation as part of the study design, and the identity of the response unit is also pre-determined by the study design. Such studies are actually called "informant surveys" and they involve, for instance, obtaining information about a community from certain select members who hold specific information, like church leaders, business owners or leaders, physicians, school teachers, civic leaders, etc. Or, if a business or organization is the unit of observation, information may be sought at different administrative/professional levels, etc.Unit of response is different than the unit of analysis because the sampled unit is unavailable/unable to participate. Proxies may be allowed by the study design, but their identity is not specifically designated (for example, anyone in the household can provide information about another household member, or any available student can provide information about another student, etc.).

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for float. A numeric datatype corresponding to the W3C XML Schema's xs:float datatype.

Mathematical average of a set of values. The mean is calculated by adding up two or more values and dividing the total by their number. In social/political science, it is usually the sum of the measurements divided by the number of subjects, or cases.

The (arithmetic) mean calculated after discarding given parts of observations at the high and low end (e.g., interquartile mean when the lowest 25% and the highest 25% are discarded, and the mean of the remaining values is calculated).

The variance is the mean square deviation of the variable around the average value. It reflects the dispersion of a frequency distribution around its mean (OECD Glossary of Statistics).

The average of the absolute differences between each value and the overall mean. Measure of statistical dispersion around the mean, alternative to Standard Deviation.

Data collected over time about a group of individuals that are connected in some way or have shared some significant experience within a given period. Examples: birth, disease, education, employment, family formation, participation in an event.

Studies different samples/different groups of people from the same population at several points in time, using the same set of questions/variables. Conclusions are drawn for the population. Examples: public opinion polls, elections studies, etc.

Data collected repeatedly over time to study change in observations. These are typically "objective" measurements of phenomena that can be observed externally, as opposed to attitudes/opinions or feelings. Examples may include economic/financial indicators, natural/meteorological phenomena, vital statistics, etc.

Measurements are taken at (usually regularly) spaced intervals. Examples: macroeconomics (weekly share prices, monthly profits, sales); meteorology (hourly temperature); measurements of individuals (blood pressure, weight, height); sociology (crime figures, employment figures), etc.Cross-sectional data is data collected by observing subjects at the same point in time, or without regard to differences in time. Analysis of cross-sectional data usually consists in comparing the differences among subjects, but is not focused on studying change over time (adapted from Wikipedia).Data collected at one point in time to complete information collected in a previous cross-sectional study; the decision to collect follow-up data is not included in the study design.

relates to the origin of the data, and ranges from the human to the highly technical. Where did the data come from? Why was it collected? Who collected it, when and where? What instruments/technologies were used to collect the data, and how were they set up? What has been done to the data since it was collected?provides information about access and usage rules.Who is allowed to view, edit or otherwise modify the data, or the metadata, and under what conditions? Who has some kind of authority over the data? Who has the authority to change the rules? Are there costs associated with access? Who has accessed the data, and what have they in turn done with it? Under what licence is the data being made available?

includes information to help build a sense of trust in the data, and allow for the data to be used long into the future. Is the data authentic, authoritative, and original? Has there been any restructuring, e.g. due to software and file-formats changing? What software has been used to access the data in the past?

Two or more people related by blood, marriage (including step-relations), adoption or fostering and who may or may not live together (National Community Services Data Dictionary, Vers 3, AIHW, 2004). For example, used when researching the extent to which people provide support and assistance for their relatives.

A person or a group of persons who share the same dwelling unit and common living arrangements. These common living arrangements may include pooling some, or all, of their income and wealth, and consuming certain types of goods and services collectively, mainly housing and food (Eurostat).U.S. Census: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from the outside of the building or through a common hall.Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.

Normally not used, as it would not be expected to compare items that have nothing in common. This term was necessary to complete the commonality range, and may be used in special cases, as determined by user needs (for instance, when comparability was expected, but not found).

Analysis of how the study, in all its stages, was managed and/or conducted, including the outcome of methodological, technical, and business decisions. May serve as a basis for changes or improvements in planning future iterations of the data collection, or entirely new projects.

Computer-assisted self-interview. Data collection method in which the respondents enter their own answers directly into a computer (desktop, laptop, Palm/PDA, etc.). The administration of the questionnaire is managed by a specifically designed program, but there is no real-time data transfer, as in the case of CAWI: the answers are stored on the computer used for the interview. Use CASI if not known whether VCASI, ACASI, or TACASI. Video computer-assisted self-interview. Earliest method of computer-assisted self-interviewing, in which respondents view the questions on a computer screen and typically enter answers using the computer keyboard, mouse, or touchscreen. (Thomas Harmon, et al. “Impact of T-ACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280)

Audio computer-assisted self-interview. Data are collected by using a recorded voice into a computer-assisted self-interview. The text of each question and its answer alternatives are displayed on the computer screen, while a pre-recorded interviewer’s voice reads these to the respondent, who listens privately through headphones. Respondents answer by selecting the appropriate response on the keyboard or directly on the computer screen. Sometimes referred to as audio-visual CASI (AVCASI). (adapted from https://syrp.org/images/ACASI_Insert_Singles.pdf) Telephone audio computer-assisted self-interview. TACASI adds telephone capabilities to a standard audio-CASI system, thereby allowing ACASI interviews to be conducted over the telephone, with the telephone’s touchtone keypad serving as the input device. (Thomas Harmon, et al. “Impact of TACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280) Computer-assisted Web interview. The administration of the questionnaire completion is managed by a specifically designed program. Questions can be tailored to previous question responses, enabling routing plans. Answers are stored directly on the main database which is accessible through the Web, using a password-secured webpage.

Type of observation in which data regarding computer usage are being collected by software (like cookies, etc.) that is built into, or applied to local, or online computer programs. Information may be collected about the ways in which users interact with the programs, how much time they spend on a page, how they use specific sections of applications, how they navigate from page to page or from one application to another, etc.

An experiment conducted in the virtual setting of the World Wide Web, in which experimental materials are programmed to implement artificial situations or events to be investigated in a distributed environment.(Reips, U.-D. (2002). Theory and techniques of Web experimenting. In B. Batinic, U.-D. Reips, & M. Bosnjak (Eds.), Online Social Sciences. Seattle: Hogrefe & Huber. Available: http://www.websm.org/uploadi/editor/Reips_2002_Theory_and_techniques.pdf [07 June 2013])

As a mode of secondary data collection, content coding applies coding techniques to transform qualitative data (textual, video, audio or still-image) originally produced for other purposes into quantitative data (expressed in unit-by-variable matrices) in accordance with pre-defined categorization schemes. Example: coded party manifesto data like the "European Parliament Election Study 2009, Manifesto Study" (doi:10.4232/1.10204)"Capturing information in writing from a different source, or from a different medium, alphabet, or form of notation, like scientific formulae, or musical notes. For transcribed interviews or observations, it is recommended to document the primary mode of collection, using one of the interview or observation terms. Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.

Statistics that relate to broad classes, groups, or categories. The data are averaged, totaled, or otherwise derived from individual-level data, and it is no longer possible to distinguish the characteristics of individuals within those classes, groups, or categories. For example, the number and age group of the unemployed in specific geographic regions, or national level statistics on the occurrence of specific offences, originally derived from the statistics of individual police districts. Modeling or imitative representation of real-world processes, events, or systems, often using computer programs. For example, a program modeling household consumption responses to indirect tax changes; or a dataset on hypothetical patients and their drug exposure, background conditions, and known adverse events.

Assessment of physical properties of living beings, objects, materials, or natural phenomena. For example, blood pressure, heart rate, body weight and height, as well as time, distance, mass, temperature, force, power, speed, GPS data on physical movement and other physical parameters or variables, like geospatial data. Assessment of personality traits or psychological/behavioral responses by means of specialized measures or tests. For example, objective tests like self-report measures with a restricted response format, or projective methods allowing free responses, including word association, sentence or story completion, vignettes, cartoon test, thematic apperception tests, role play, drawing tests, inkblot tests, choice ordering exercises, etc.

A subset of real numbers, which can be represented by a finite-length sequence of decimal digits (0-9) separated by a period as a decimal indicator. An optional leading sign is allowed. If the sign is omitted, "+" is assumed. Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero(es) can be omitted. For example: -1.23, 12678967.543233, +100000.00, 210. A numeric datatype corresponding to the W3C XML Schema's xs:decimal datatype.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.

Unit of response is different than the unit of observation as part of the study design, and the identity of the response unit is also pre-determined by the study design. Such studies are actually called "informant surveys" and they involve, for instance, obtaining information about a community from certain select members who hold specific information, like church leaders, business owners or leaders, physicians, school teachers, civic leaders, etc. Or, if a business or organization is the unit of observation, information may be sought at different administrative/professional levels, etc.Unit of response is different than the unit of analysis because the sampled unit is unavailable/unable to participate. Proxies may be allowed by the study design, but their identity is not specifically designated (for example, anyone in the household can provide information about another household member, or any available student can provide information about another student, etc.).

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.

Data collected repeatedly over time to study change in observations. These are typically "objective" measurements of phenomena that can be observed externally, as opposed to attitudes/opinions or feelings. Examples may include economic/financial indicators, natural/meteorological phenomena, vital statistics, etc.

Measurements are taken at (usually regularly) spaced intervals. Examples: macroeconomics (weekly share prices, monthly profits, sales); meteorology (hourly temperature); measurements of individuals (blood pressure, weight, height); sociology (crime figures, employment figures), etc.Cross-sectional data is data collected by observing subjects at the same point in time, or without regard to differences in time. Analysis of cross-sectional data usually consists in comparing the differences among subjects, but is not focused on studying change over time (adapted from Wikipedia).

provides information about access and usage rules.Who is allowed to view, edit or otherwise modify the data, or the metadata, and under what conditions? Who has some kind of authority over the data? Who has the authority to change the rules? Are there costs associated with access? Who has accessed the data, and what have they in turn done with it? Under what licence is the data being made available?

U.S. Census: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from the outside of the building or through a common hall.Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.

Computer-assisted self-interview. Data collection method in which the respondents enter their own answers directly into a computer (desktop, laptop, Palm/PDA, etc.). The administration of the questionnaire is managed by a specifically designed program, but there is no real-time data transfer, as in the case of CAWI: the answers are stored on the computer used for the interview. Use CASI if not known whether VCASI, ACASI, or TACASI. Video computer-assisted self-interview. Earliest method of computer-assisted self-interviewing, in which respondents view the questions on a computer screen and typically enter answers using the computer keyboard, mouse, or touchscreen. (Thomas Harmon, et al. “Impact of T-ACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280)

Audio computer-assisted self-interview. Data are collected by using a recorded voice into a computer-assisted self-interview. The text of each question and its answer alternatives are displayed on the computer screen, while a pre-recorded interviewer’s voice reads these to the respondent, who listens privately through headphones. Respondents answer by selecting the appropriate response on the keyboard or directly on the computer screen. Sometimes referred to as audio-visual CASI (AVCASI). (adapted from https://syrp.org/images/ACASI_Insert_Singles.pdf) Telephone audio computer-assisted self-interview. TACASI adds telephone capabilities to a standard audio-CASI system, thereby allowing ACASI interviews to be conducted over the telephone, with the telephone’s touchtone keypad serving as the input device. (Thomas Harmon, et al. “Impact of TACASI on Survey Measurements of Subjective Phenomena”. Public Opinion Quarterly, vol. 73, issue 2, pp. 255-280)

Type of observation in which data regarding computer usage are being collected by software (like cookies, etc.) that is built into, or applied to local, or online computer programs. Information may be collected about the ways in which users interact with the programs, how much time they spend on a page, how they use specific sections of applications, how they navigate from page to page or from one application to another, etc.

An experiment conducted in the virtual setting of the World Wide Web, in which experimental materials are programmed to implement artificial situations or events to be investigated in a distributed environment.(Reips, U.-D. (2002). Theory and techniques of Web experimenting. In B. Batinic, U.-D. Reips, & M. Bosnjak (Eds.), Online Social Sciences. Seattle: Hogrefe & Huber. Available: http://www.websm.org/uploadi/editor/Reips_2002_Theory_and_techniques.pdf [07 June 2013])

As a mode of secondary data collection, content coding applies coding techniques to transform qualitative data (textual, video, audio or still-image) originally produced for other purposes into quantitative data (expressed in unit-by-variable matrices) in accordance with pre-defined categorization schemes. Example: coded party manifesto data like the "European Parliament Election Study 2009, Manifesto Study" (doi:10.4232/1.10204)"

Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.

Statistics that relate to broad classes, groups, or categories. The data are averaged, totaled, or otherwise derived from individual-level data, and it is no longer possible to distinguish the characteristics of individuals within those classes, groups, or categories. For example, the number and age group of the unemployed in specific geographic regions, or national level statistics on the occurrence of specific offences, originally derived from the statistics of individual police districts.

Assessment of personality traits or psychological/behavioral responses by means of specialized measures or tests. For example, objective tests like self-report measures with a restricted response format, or projective methods allowing free responses, including word association, sentence or story completion, vignettes, cartoon test, thematic apperception tests, role play, drawing tests, inkblot tests, choice ordering exercises, etc.

A subset of real numbers, which can be represented by a finite-length sequence of decimal digits (0-9) separated by a period as a decimal indicator. An optional leading sign is allowed. If the sign is omitted, "+" is assumed. Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero(es) can be omitted. For example: -1.23, 12678967.543233, +100000.00, 210. A numeric datatype corresponding to the W3C XML Schema's xs:decimal datatype.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.

Unit of response is different than the unit of observation as part of the study design, and the identity of the response unit is also pre-determined by the study design. Such studies are actually called "informant surveys" and they involve, for instance, obtaining information about a community from certain select members who hold specific information, like church leaders, business owners or leaders, physicians, school teachers, civic leaders, etc. Or, if a business or organization is the unit of observation, information may be sought at different administrative/professional levels, etc.Unit of response is different than the unit of analysis because the sampled unit is unavailable/unable to participate. Proxies may be allowed by the study design, but their identity is not specifically designated (for example, anyone in the household can provide information about another household member, or any available student can provide information about another student, etc.).

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.

Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.

Audio computer-assisted self-interview. Data are collected by using a recorded voice into a computer-assisted self-interview. The text of each question and its answer alternatives are displayed on the computer screen, while a pre-recorded interviewer’s voice reads these to the respondent, who listens privately through headphones. Respondents answer by selecting the appropriate response on the keyboard or directly on the computer screen. Sometimes referred to as audio-visual CASI (AVCASI). (adapted from https://syrp.org/images/ACASI_Insert_Singles.pdf)

Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.

Unit of response is different than the unit of observation as part of the study design, and the identity of the response unit is also pre-determined by the study design. Such studies are actually called "informant surveys" and they involve, for instance, obtaining information about a community from certain select members who hold specific information, like church leaders, business owners or leaders, physicians, school teachers, civic leaders, etc. Or, if a business or organization is the unit of observation, information may be sought at different administrative/professional levels, etc.

Single-precision 32-bit floating point type: The basic value space of float consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^24, and e is an integer between -149 and 104, inclusive. In addition, it also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign.

Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.

Double-precision 64-bit floating point type. The basic value space of double consists of the values m × 2^e, where m is an integer whose absolute value is less than 2^53, and e is an integer between -1075 and 970, inclusive. In addition to the basic value space described above, the value space of double also contains the following three special values: positive and negative infinity and not-a-number (NaN). The special values positive and negative infinity and not-a-number have lexical representations INF, -INF and NaN, respectively. Lexical representations for zero may take a positive or negative sign. For example, -1E4, 1267.43233E12, 12.78e-2, 12 , -0, 0 and INF are all legal literals for double. A numeric datatype corresponding to the W3C XML Schema's xs:double datatype.