Ontology-driven spatial information retrieval in GRIP

Ontology-driven spatial information retrieval in GRIP Naicong Li, Nathan Strout, Steve Paplanus, Thomas Leuteritz University of Redlands Redlands, CA USA AAG 2007, San Francisco

Ontology-driven spatial information retrieval in GRIP • Objective • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • System design • Future work

Ontology-driven spatial information retrieval in GRIP • Objective • Knowledge organization and information retrieval for data with heterogeneous format, syntax, and semantics • Use GRIP as development platform, use desert tortoise recovery plan data repository as project data • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • System design • Future work

Ontology-driven spatial information retrieval in GRIP • Objective • Knowledge organization and information retrieval for data with heterogeneous format, syntax, and semantics • Use GRIP as development platform, use desert tortoise recovery plan data repository for project data • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • System design • Future work

Ontology-driven spatial information retrieval in GRIP • Objective • Geographically Referenced Information Portal (GRIP) • Open service architecture • Supports distributed processing • Search data with heterogeneous data format • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • System design • Future work

Ontology-driven spatial information retrieval in GRIP • Objective • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Desert tortoise declared endangered species • USFWS recovery plan identifying critical habitat units (CHU) and recommended recover actions • CHUs under management of various agencies: BLM, NPS, military bases, etc. • Centralized data repository with digital library and GIS data • GRIP to provide framework underlying the information portal for the data repository • Information retrieval requirement analysis • System design • Future work

GIS DATA – SDE GEOSPATIAL DATABASE 147 tortoise related feature classes 501 base map feature classes 26 raster data sets All with FGDC compliant metadata • ESRI • ESRI

DTP RESOURCE LIBRARY • The DTP Library is a searchable repository in Sharepoint, combining all the project resources. The digital library includes 4000 items. • The documents are sorted in the following categories: • Free form text documents • Images • Maps

Ontology-driven spatial information retrieval in GRIP • Objective • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • Improve interoperability among heterogeneous data • Allow integrated queries for GIS and non GIS data • Organize query results semantically • Facilitate knowledge discovery • System design • Future work

Ontology-driven spatial information retrieval in GRIP • Objective • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • System design • Integrated solution to knowledge organization and information retrieval • Ontology development • Ontology-based information organization • Ontology-based information retrieval • Making implicit information in data explicit • Future work

Ontology-driven spatial information retrieval in GRIP • System design -- Integrated solution to knowledge organization and information retrieval

Ontology-driven spatial information retrieval in GRIP • System design -- Integrated solution to knowledge organization and information retrieval Knowledge organization

Ontology-driven spatial information retrieval in GRIP • System design -- Integrated solution to knowledge organization and information retrieval Information retrieval

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific • Based on a controlled vocabulary agreed upon by a user community • Prototype ontology being developed for system design and testing purposes

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific • Based on a set of controlled vocabulary agreed upon by a user community • Prototype ontology being developed for system design and testing purposes • Categories, instances, attributes, relations

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific • Based on a set of controlled vocabulary agreed upon by a user community • Prototype ontology being developed for system design and testing purposes • Categories, instances, attributes, relations • All the concepts have corresponding natural language expression(s)

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific • Based on a set of controlled vocabulary agreed upon by a user community • Prototype ontology being developed for system design and testing purposes • Categories, instances, attributes, relations • All the concepts have corresponding natural language expression(s) • Axioms defined based on project needs

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific • Based on a set of controlled vocabulary agreed upon by a user community • Prototype ontology being developed for system design and testing purposes • Categories, instances, attributes, relations • All the concepts have corresponding natural language expression(s) • Axioms defined based on project need • In OWL-DL

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology development • Application domain specific and project specific • Based on a set of controlled vocabulary agreed upon by a user community • Prototype ontology being developed for system design and testing purposes • Categories, instances, attributes, relations • All the concepts have corresponding natural language expression(s) • Axioms defined based on project need • In OWL-DL • Using SWEET as upper level ontology

Ontology-driven spatial information retrieval in GRIP Natural language expressions Attribute and relation definitions

Ontology-driven spatial information retrieval in GRIP Natural language expression Attribute and relation definitions Instances

Ontology-driven spatial information retrieval in GRIP Causal relationship Threat factor categories

Ontology-driven spatial information retrieval in GRIP • Example of inverse relations: • manages – managedBy • predatorOf – hasPredator • Example of transitive relations: causal relation • Between threat factors and tortoise population reduction • Among threat factors

Ontology-driven spatial information retrieval in GRIP • Example of inverse relations: • manages – managedBy • predatorOf – hasPredator • Example of transitive relations: causal relation • Between threat factors and tortoise population reduction • Among threat factors • Landfill ravens tortoise population reduction supports causes

Ontology-driven spatial information retrieval in GRIP • Example of inverse relations: • manages – managedBy • predatorOf – hasPredator • Example of transitive relations: causal relation • Between threat factors and tortoise population reduction • Among threat factors • Landfill ravens tortoise population reduction • Landfill habitat extent loss tortoise population reduction supports causes causes causes

Ontology-driven spatial information retrieval in GRIP • Example of inverse relations: • manages – managedBy • predatorOf – hasPredator • Example of transitive relations: causal relation • Between threat factors and tortoise population reduction • Among threat factors • Landfill ravens tortoise population reduction • Landfill habitat extent loss tortoise population reduction • Grazing habitat extent loss tortoise population reduction supports causes causes causes causes causes

Ontology-driven spatial information retrieval in GRIP • Example of inverse relations: • manages – managedBy • predatorOf – hasPredator • Example of transitive relations: causal relation • Between threat factors and tortoise population reduction • Among threat factors • Landfill ravens tortoise population reduction • Landfill habitat extent loss tortoise population reduction • Grazing habitat extent loss tortoise population reduction • Grazing soil compaction habitat degradation • tortoise population reduction supports causes causes causes causes causes causes causes causes

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information organization • Mapping between concepts in the ontologies and • data in geodatabases • Text documents (keyword field in metadata)

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information organization • Mapping between concepts in the ontologies and • data in geodatabases • Text documents (keyword field in metadata) • “Registration mappings” = “a set of rules describing the association between semantic types and structural types”* • Xquery for xml data source • SQL expression for relational database data source * Bowers & Ludascher 2004

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information organization • Mapping between concepts in the ontologies and • data in geodatabases • Text documents (keyword field in metadata) • “Registration mappings” = “a set of rules describing the association between semantic types and structural types”* • Xquery for xml data source • SQL expression for relational database data source • Including mapping between process/service concepts and geoprocessing tools** * Bowers & Ludascher 2004 ** Lutz & Klein 2006

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information retrieval • User query types • Browsing (guided by ontologies)* • Searching (query keyword  concept in ontologies; query expansion guided by ontologies) • Retrieving GIS and non GIS data through the same query UI • Query results organized semantically by the ontology * Guarino 1998, Fonseca et al 2002

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information retrieval • User query types • Browsing (guided by ontologies) • Searching (query keyword  concept in ontologies; query expansion guided by ontologies*) • Retrieving GIS and non GIS data through the same query UI • Query results organized semantically by the ontology * Fu et al 2005

Ontology-driven spatial information retrieval in GRIP Live demo for design concept

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information retrieval • User query types • Browsing (guided by ontologies) • Searching (query expansion guided by ontologies) • Retrieving GIS and non GIS data through the same query UI • Query results organized semantically by the ontology

Ontology-driven spatial information retrieval in GRIP • System design -- Ontology-based information retrieval • User query types • Browsing (guided by ontologies) • Searching (query expansion guided by ontologies) • Retrieving GIS and non GIS data through the same query UI • Query results organized semantically by the ontology • System design -- Ontology-based information retrieval • Making implicit information in data explicit

Ontology-driven spatial information retrieval in GRIP • Objective • Geographically Referenced Information Portal (GRIP) • Desert tortoise recovery plan data repository • Information retrieval requirement analysis • System design • Future work

Ontology-driven spatial information retrieval in GRIP