agricultural education collections & repositories: scratching the surface

agricultural education collections & repositories

scratching the surface

Nikos Manouselis, Vassilis ProtonotariosAgro-Know Technologies

nikosm@ieee.org; vprot@agroknow.gr

(long) introduction

learning object

"any entity, "any entity, digitaldigital or non-digital, that may or non-digital, that may be used for be used for learninglearning, , educationeducation or or trainingtraining""

ΙΕΕΕ Learning Technology Standards Committee (2002)

http://www.soilassociation.orghttp://www.soilassociation.org

http://www.climatecrisis.nethttp://www.climatecrisis.net

http://www.teachersdomain.orghttp://www.teachersdomain.org

http://www.digitalgreen.orghttp://www.digitalgreen.org

learning object

"any entity, "any entity, digitaldigital or non-digital, that may or non-digital, that may be used for be used for learninglearning, , educationeducation or or trainingtraining““

+ metadata describing this use+ metadata describing this use

Publisher

Date Catalog

SubjectID

AuthorTitle

metadata

educational metadata

NOT a learning object

…a learning object, in context

metadata reflect the context

our context

agricultural science(s)

lots of data produced & consumed

what does ag-specific mean?• data types/formats very particular to

agricultural education?• classification of data around agriculture-specific

themes & topics?• connectivity and combination of data with

other sources of agricultural interest?• usage scenarios, environments & tools tightly

connected and specialised for agricultural practices and applications?

data types & formats• bibliographic metadata• educational content• statistical/economic data• germplasm collections• soil maps• DNA sequence markers/data• …more

classification schemes• knowledge organisation systems for agriculture

– AGROVOC, CABI, NAL, …

• in recent work, we identified more than 88 ag-specialised ones

[Palavitsinis & Manouselis, “Agricultural Knowledge Organization Systems: analysis of an indicative sample”, in press]

classification schemes• knowledge organisation systems for agriculture

– AGROVOC, CABI, NAL, …

• in recent work, we identified more than 88 ag-specialised ones

[Palavitsinis & Manouselis, “Agricultural Knowledge Organization Systems: analysis of an indicative sample”, in press]

connectivity & combination of data • interoperability to achieve remix & reuse

– learning technology standards & specifications

• recently revisited metadata analysis of agricultural learning repositories– 11 out of 13 found implementations have been

analysed– satisfactory conformance to base metadata schemas

was found– next step: harmonization & exchange of good practices[Manolis et al., “Revisiting an analysis of agricultural learning repository metadata: preliminary

results”, MTSR’12]

connectivity & combination of data Metadata TermsGroup of Common Properties

Property dc:-based dcterms:-based lom:-based More specific Metadata Terms

1. General Characteristics Identifier dc:identifier

dcterms:identifier lom:identifier  

  Title dc:title dcterms:title lom:title dcterms:alternative

  Language dc:languagedcterms:language lom :language  

  Descriptiondc:description

dcterms:description

lom :description dcterms:abstract

ags:DescriptionNotes  Keyword dc:subject dcterms:subject lom:keyword ags:subjectThesaurus2. Life Cycle Entity role dc:creator dcterms:creator lom: role  

   dc:contributor

dcterms:contributor lom: role  

    dc:publisherdcterms:publisher lom: role  

3. Technical Characteristics Format dc:format dcterms:format lom:format  

4. Educational Characteristics

Learning Resource Type dc:type  

lom:learningResourceType  

5. Intellectual Property Rights

Rights Description dc:rights dcterms:rights lom:rights ags:rightsStatement

dcterms:license

scenarios & environments• very much context-specific: educational

activity workflows to be carefully studied and modelled

• preliminary ideas currently explored in connection with digital content– e.g. educational scenarios/pathways

http://portal.organic-edunet.eu/index.php?option=com_content&view=article&id=2177&catid=1&Itemid=103

required: learning repositories

definitions• digital repository: system for the storage,

location and retrieval of digital resources• digital learning repository (DLR):

– nature of resources or their description reflects an interest of use in an educational context

Holden C., “From Local Challenges to a Global Community: Learning Repositories Summit”, Academic ADL Co-Lab, 2003

putting it all together• agricultural data/content being stored and

described to serve educational activities– types of data/content that would serve typical

educational needs in this context– metadata that includes proper thematic

classification and ensures interoperability– design & development of educational

scenarios/pathways on top of this content

interesting (?) questions

• do existing, generic learning repositories have content of agricultural interest?– do they have a lot?

• are there learning repositories focusing particularly to agricultural & rural stakeholders?– where are they?

preliminary study

• took place during 2005 • examined 59 well-known general-purpose

repositories– found in 27 of them (~45%) agricultural content

BUT• in a total of ~881,000 educational resources:

– …only 3,201 resources (0.36%) related to agricultural topics

Tzikopoulos et al., "Investigating Digital Learning Repositories' Coverage of Agriculture-related Topics", ITAFE 2005.

0

500

1000

1500S

um

34.5% of resources not 34.5% of resources not particularly classified particularly classified

subject classification

so we assume that…• learning repositories that particularly

focus on agricultural & rural stakeholders–should probably have more relevant

content–should probably have it better

described/categorized

technology• content management systems for digital

repositories exist and are very popular– many of them specifically adapted for educational

content (e.g. Dspace, ePrints, Fedora, …)

• some tools already being adapted for the agricultural domain– e.g. AgriOceanDSpace, Organic.ePrints, AgriDrupal, …

• learning management systems also include resource/collection repository component– Moodle (and agriMoodle), ILIAS, …

technology• content management systems for digital

repositories exist and are very popular– many of them specifically adapted for educational

content (e.g. Dspace, ePrints, Fedora, …)

• some tools already being adapted for the agricultural domain– e.g. AgriOceanDSpace, Organic.ePrints, AgriDrupal, …

• learning management systems also include resource/collection repository component– Moodle (and agriMoodle), ILIAS, …

ADOPTION, AVAILABILITY, O

PENESS

more problems?

--indicative list--

a. metadata authoring/creationb. metadata curation/validationc. metadata values/vocabulariesd. metadata multilingualitye. …lots more

34

a. authoring/creation

• metadata creation is a painful and costly process–automatic generation can help–high quality/accuracy/relevance

descriptions require human intervention

35

a. authoring/creation

36

b. curation/validation

• good online services demand high quality (or at least not poor quality) description of content–someone needs to take the final decision

before something is published–especially relevant when content

development has been costly/labourous

37

b. curation/validation

38

c. values/vocabularies• mappings and crosswalks among values and

vocabularies of different collections are crucial–usually manually defined and maintained–difficult to ensure that all applications will

publish and link their vocabularies–vocabulary bank management tend to become

too complex for the purpose that they serve

39

c. values/vocabularies

40

d. multilinguality• for multilingual contexts, everything

needs to become (and be maintained) multilingual–metadata values and labels– interface labels for various systems–automatic translation helps but usually

produces rather rough/poor translations

41

d. multilinguality

42

conclusionconclusion

potential• learning objects/resources: useful• having them organised in learning

repositories: good • exploring ways to introduce them into

formal and informal education & training–challenging and worthwhile

challenges• technical issues

–mainly interoperability• content issues

–taking advantage of existing collections– integrate traditional data types/sources

coming from agricultural science–combine with cultural heritage, research

work/outcomes, …

thank you!