spatial information systems yesterday, today and tomorrow

Facultad de Ingeniería, Universidad de Cuenca, Ecuador

Thursday 2 June 2011

Beniamino Murgante

Spatial Information Spatial Information Systems yesterday, today Systems yesterday, today

and tomorrowand tomorrow

e-mail: [email protected]: http://www.unibas.it/utenti/murgante/Benny.htmlSkype: beniamino.murganteLinkedin: http://www.linkedin.com/pub/beniamino-murgante/7/960/9aa

Facultad de Ingeniería, Universidad de Facultad de Ingeniería, Universidad de Cuenca, Ecuador - Cuenca, Ecuador - Thursday 2 June 2011Thursday 2 June 2011

Spatial Information Systems yesterday, Spatial Information Systems yesterday, today and tomorrowtoday and tomorrow - Beniamino Beniamino MurganteMurgante

My booksMy books



Other books and special issuesOther books and special issues

Analysing, Modelling and Visualizing Spatial Environmental Data

NeoGeography and WikiPlanning"



Network co-founderNetwork co-founder




1,403 Members




1,680 Members



Ian McHarg

History of GISHistory of GIS

1969




1969

Physiographic obstructions Social aspects




1969

Physiographic obstructions



Origin of GISOrigin of GIS



Cost of the GIS softwareCost of the GIS software(Longley, et al. 2001)

Evolution of GISEvolution of GIS



IncreaseIncrease of GIS software of GIS software functionsfunctions

(Longley, et al. 2001)




GrowthGrowth of personal computers power of personal computers power (Moore's law(Moore's law))

(Longley, et al. 2001)





GIS users tend to develop their own data sets for many reason:

1. they may not know available existing data sets that could be appropriately used for their applications;

2. access to these data sets is difficult;3. they are not used to sharing data sets with

other sectors and/or organizations; 4. existing geospatial data sets stored in a

certain GIS system may not be easily exported to another system.




As a result, the new age of GIS is still characterized by:

1. many actors involved in data collection and distribution;

2. a proliferation of GIS applications, product types, and formats;

3. duplication as a consequence of the difficulties to access the existing data, and the highly specific quality of the data collected;

4. increasing difficulty in the exchange and use of data that came from different organizations;



CANRI 1999




Executive Order 12906 Executive Order 12906

Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure (NSDI)

1. "National Spatial Data Infrastructure" means the technology, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of geospatial data.

2. "Geospatial data" means information that identifies the geographic location and characteristics of natural or constructed features and boundaries on the earth. This information may be derived from, among other things, remote sensing, mapping, and surveying technologies. Statistical data may be included in this definition at the discretion of the collecting agency.

3. The "National Geospatial Data Clearinghouse" means a distributed network of geospatial data producers, managers, and users linked electronically.



Executive Order 12906Executive Order 12906



Executive Order 12906Executive Order 12906

Spatial Data Infrastructures:1. geographic data and attributes,2. catalogues and Web mapping (as a means to

discover, visualize, and evaluate the data),3. enough documentation (metadata)



Nebert, The SDI CookbookNebert, The SDI Cookbook

InformationResource

1. Document

Metadata

DataServer

MetadataServer

2. Publish

User

Registry3. Register

4. Query

5. Access



Nebert, The SDI CookbookNebert, The SDI Cookbook

WebClientWebClient

ClearinghouseServers

Gateway(s)User

Z39.50 protocolHTTP protocol

ServiceRegistryServiceRegistry

WebServerWebServer

•One Search across many servers•Metadata is the key



National Spatial Data InfrastructureNational Spatial Data Infrastructure



GeoportalsGeoportals



InteroperabilityInteroperability

The main barriers towards a full interoperability The main barriers towards a full interoperability are determined by three factors are determined by three factors (Murgante (Murgante 2011); 2011);

o Bureaucratic: Bureaucratic: due to a poor practice to share due to a poor practice to share data which, in most cases, leads to a sort of data which, in most cases, leads to a sort of personal property right by the employer, who personal property right by the employer, who provides to its management;provides to its management;

o Technological: Technological: mainly produced by differences mainly produced by differences between systems, structures and format of between systems, structures and format of data;data;

o Semantic: Semantic: due to the lack of correspondence in due to the lack of correspondence in meanings.meanings.



Information-Explosion EraInformation-Explosion Era

The complete elimination of bureaucratic barriers could The complete elimination of bureaucratic barriers could be achieved with a “be achieved with a “wikiwiki” approach to data production ” approach to data production and management. and management. (Murgante 2011); (Murgante 2011);

o Volunteered Geographic InformationVolunteered Geographic Information (Goodchild, 2007) (Goodchild, 2007) where distributed masses create, manage and where distributed masses create, manage and disseminate spatial datadisseminate spatial data,,

o CrowdsourcingCrowdsourcing (Goodchild, 2009) (Goodchild, 2009) organizations or organizations or companies externalize production using a mass companies externalize production using a mass collaboration collaboration (OpenStreetMap),(OpenStreetMap),

o NeogeographyNeogeography (Turner, 2006), (Turner, 2006), citizens produce data citizens produce data integrating maps with geo-tagged photos, videos, integrating maps with geo-tagged photos, videos, blogs, Wikipedia, etc..blogs, Wikipedia, etc..

o Cloud Servicies Cloud Servicies




Google Earth

bing virtual earth

openstreetmap




http://www.giscloud.com/map/11766/timatongis/tourism-in-matera-on-geographic-information-system



http://slashgeo.org/2011/05/24/Geospatial-Semantic-Web-Part-Inevitable-Future

Semantic MatchingSemantic Matching



Semantic Matching Semantic Matching

Neither a standard data format nor a common data model allows for the transfer of the meaning of information

The more complex issue of what is represented instead of how it is represented needs to be addressed




Users

Table Vegetation Table Fauna …

Logical Model

Faunawolf

wildcatfox

…

Database

VegetationConifers

Hardwood Species,

Mediterranean macchia…

fauna forestlive

Conceptual Model

VegetationFauna

observer

Real world




Perception

Lake??? Body of

water??? Lagoon???Basin???



ONTOLOGY: definitionsONTOLOGY: definitions

oAn ontology is “An explicit specification of a conceptualization” (Gruber, 93)

oAn ontology is a formal and explicit specification of a shared conceptualization ( Borst 1997)

o In order to implement an ontology, it is necessary to formalize some mental models within a community, aiming to capture domain knowledge and providing a common vision, which can be reused and shared by other groups (Chandrasekaran et al., 1999).




o Eco (2005) reviewing the book "Where are you? Mobile Ontology" (Ferraris 2005) high-lights that the most interesting aspect of the volume is not the fact that Ferraris developed a mobile phone ontology, but that its ontology allowed us to understand what a mobile phone is.

o Ontologies, aiming at ensuring system interoperability, allow to clarify in a deepened way several concepts, often considered known, but affected by a certain degree of superficiality (Murgante 2008).




o When a wider semantic matching is reached considering many communities, a certain detail of the original meaning is loosed (Fonseca et al., 2002)

o An ontology defines, then, the basic conditions, the relationships, the vocabulary of a domain, the rules for combining words and relationships to define any vocabulary extension (Neches et al., 1991).

o An ontology can be seen as a set of hierarchically structured terms for a domain description and can be used as a skeleton for a knowledge base (Swartout et al., 1997).



ONTOLOGYONTOLOGY

Four phases of Ontology building :

o the definition of concepts related to domain, which led to the realization of a glossary

o finding main concepts of the domain, associating definitions included in our glossary;

o hierarchically organizing concepts, finding super-classes and sub-classes of concepts with relationship IS_A;

o studying other types of relationships associated to concepts.



ONTOLOGYONTOLOGY

Fundamental steps in ontology building, represented through a layer cake (adapted from Cimiano, 2006).



ONTOLOGYONTOLOGY

o Terms are a fundamental aspect in ontology building; if an object has not been represented by a term, it means that it lacks in importance.

o Synonyms, on one hand are enrichments of language, while from an interoperability point of view are factors which may generate confusion.

o Many kinds of relationships exist: taxonomic (IS_A), meronimic (PART_OF) telic (PURPOSE_OF..) etc.



Ontologies Vs DatabaseOntologies Vs Database

The ontology is a formal explicit model for a domain

o Domain concepts

o Concepts property

o Property constraints

o Entity

o Attributes and relationships

o Constraints

OntologiesOntologies DatabaseDatabase

o An Entity relationship scheme can be translated in an ontology

o In the case of particularly complex domains an ontology allows a more effective representation



Building ontologies for disaster Building ontologies for disaster management: management:

seismic risk domainseismic risk domain

Damage definition

B. Murgante, G. Scardaccione, G. Las CasasB. Murgante, G. Scardaccione, G. Las Casas




seismic risk domainseismic risk domainDamage definitionDamage definition





seismic risk domainseismic risk domainDefinition of emergency area and strategic Definition of emergency area and strategic elementselements




Relationship IS_A is a link generalization / specialization among entities

Attribute 1

Sub-class 1

Super-class

Sub-class 2

Attribute 2 Attribute 3

IS_A

Super-class entities generalize the sub-classes

Sub-class entities are Super-class specialization

Sub-classes inherit Super-class attributes

Building ontologies for disaster management: Building ontologies for disaster management: seismic risk domainseismic risk domain




Super-classSuper-class

Sub-Sub-classclass





RelationshipRelationship

Contribuisce a

Vulnerabilità

Rischio sismico





Relationship IS_ARelationship IS_A




seismic risk domainseismic risk domainRepresentation of relationships between conceptsRepresentation of relationships between concepts




Attributes Attributes inherited from inherited from type of type of vulnerability vulnerability

Specific attribute ofSpecific attribute of

physic vulnerability physic vulnerability

Defining properties






Ontological Network Ontological Network

Tree structure concerning seismic risk.

spatial information systems yesterday, today and tomorrow

Technology

data production

data collection

statistical data

spatial data infrastructures

utilization of geospatial

format of data semantic

exchangeand use of data

existing geospatial