1 SOCoP Introduction to Spatial Ontologies Spatial Ontology Community of Practice Maps and map visualization Features and feature geometries Geographic and spatial-temporal relationships

2 Topics Value of Ontologies Value of Ontologies SOCoP Overview SOCoP Overview Introduction to Ontologies Introduction to Ontologies Ontological Example Ontological Example

3 Benefits of Formal Ontologies for Organizations Drivers - Ontologies are important for the federal government, because they enable semantic translation and support standardization efforts such as the Federal Enterprise Architecture and its information models: Drivers - Ontologies are important for the federal government, because they enable semantic translation and support standardization efforts such as the Federal Enterprise Architecture and its information models: organize informationorganize information quality controlquality control information discoveryinformation discovery data repurposingdata repurposing integration of data sourcesintegration of data sources enable semantic webenable semantic web Spatial Ontology - an explicit, partial description or vocabulary of Spatial Ontology - an explicit, partial description or vocabulary of representations which people use in geospatial/spatial domains

4 Spatial Ontology Community of Practice (SOCoP) The Spatial Ontology Community of Practice was officially begun in October of 2006 The Spatial Ontology Community of Practice was officially begun in October of 2006 Purpose Purpose SOCoP is chartered as a Community of Practice under the Best Practices Committee of the Federal CIO CouncilSOCoP is chartered as a Community of Practice under the Best Practices Committee of the Federal CIO Council Role Role To foster collaboration among researchers, technologists & users of spatial knowledge representations and reasoning towards the development of spatial ontologies for use by all in the Semantic Web.To foster collaboration among researchers, technologists & users of spatial knowledge representations and reasoning towards the development of spatial ontologies for use by all in the Semantic Web. Support open collaboration and open standards for increased interoperability of spatial data across governmentSupport open collaboration and open standards for increased interoperability of spatial data across government

5 Spatial Ontology Community of Practice (SOCoP) Role (continued) Role (continued) Synchronize with Geospatial Profile of FEA and the Geospatial LOB as well as across the entire spectrum of applicable geospatial standards (via W3C, ISO, OGC, etc.).Synchronize with Geospatial Profile of FEA and the Geospatial LOB as well as across the entire spectrum of applicable geospatial standards (via W3C, ISO, OGC, etc.). Document best practices, and create opportunities to partner with other cross domain and ontology CoP groups.Document best practices, and create opportunities to partner with other cross domain and ontology CoP groups. Help inventory geospatial ontologies, develop an approach to institutionalizing and streamline the effort to support the development and management of ontologies across geospatial lines of business both in and out of governmentHelp inventory geospatial ontologies, develop an approach to institutionalizing and streamline the effort to support the development and management of ontologies across geospatial lines of business both in and out of government

6 Spatial Ontology Community of Practice Current Focus Current Focus Build membershipBuild membership Conduct an Inventory of Spatial OntologiesConduct an Inventory of Spatial Ontologies Establish relationships with other geospatial ontology and semantics activities such as OGC, W3C, and the Geospatial Intelligence Standards Working GroupEstablish relationships with other geospatial ontology and semantics activities such as OGC, W3C, and the Geospatial Intelligence Standards Working Group Participate/Present at Conferences and WorkshopsParticipate/Present at Conferences and Workshops Examine the potential for a pilotExamine the potential for a pilot Membership Membership Membership in the SOCoP is open to interested partiesMembership in the SOCoP is open to interested parties Co-Chairs: Co-Chairs: Kevin Backe, Topographic Engineering Center, US Army Corps of EngineersKevin Backe, Topographic Engineering Center, US Army Corps of Engineers John Moeller, Northrop Grumman Information TechnologyJohn Moeller, Northrop Grumman Information Technology Executive Secretariat: Executive Secretariat: Gary Berg-Cross, Engineering, Management and IntegrationGary Berg-Cross, Engineering, Management and Integration

7 Spatial Ontology Community of Practice Meetings: Meetings: Regularly Scheduled meetings are every other month on the 4 th Thursday from 11:00 – 1:00 ETRegularly Scheduled meetings are every other month on the 4 th Thursday from 11:00 – 1:00 ET For more information go to the SOCoP wiki at: For more information go to the SOCoP wiki at:

8 Introduction to Ontologies : What is an Ontology For? Ontologies are a primary focus of the development of the Semantic Web Ontologies are a primary focus of the development of the Semantic Web Different systems, on the internet and other government networks, typically cannot “talk” to each other since they do not share a common understanding of the data Different systems, on the internet and other government networks, typically cannot “talk” to each other since they do not share a common understanding of the data Metadata tagging is especially important for iconic data which are not proceesable like strings and digits. Ontologies provides semantics for such metadata annotations. Thus ontologies support information systems by providing an unambiguous representation of the concepts and relationships used in a given problem area Thus ontologies support information systems by providing an unambiguous representation of the concepts and relationships used in a given problem area The ontology must take human-understandable concepts and make them processable by information systemsThe ontology must take human-understandable concepts and make them processable by information systems A quality ontology should serve as a robust reference framework to which information systems can point to proscribe the meaning of information used by a systemA quality ontology should serve as a robust reference framework to which information systems can point to proscribe the meaning of information used by a system

9 What Makes up an Ontology? An ontology is an explicit description, preferably in a formal language, based on a conceptualization of a domain. An ontology usually is built on : An ontology is an explicit description, preferably in a formal language, based on a conceptualization of a domain. An ontology usually is built on : ClassesClasses A class can be thought of as a concept in the domain A class can be thought of as a concept in the domain a class of air-traffic objects (e.g. Commercial Airport)a class of air-traffic objects (e.g. Commercial Airport) a class of regions (e.g. Mid-Atlantic) a class of regions (e.g. Mid-Atlantic) A class includes a collection of elements with similar propertiesA class includes a collection of elements with similar properties The Backbone of an Ontology is made up of Classes in a Class Hierarchy (a formal taxonomy) The Backbone of an Ontology is made up of Classes in a Class Hierarchy (a formal taxonomy) Properties & attributes of concepts (with descriptions)Properties & attributes of concepts (with descriptions) Relationships between classes like subClass, intersection, unionRelationships between classes like subClass, intersection, union Relationships between classes and properties like allValuesFrom, cardinalityRelationships between classes and properties like allValuesFrom, cardinality

How is an ontology represented? It is expressed within a representational formalism which provides some degree of formal semantics to express the meaning of its assertionsIt is expressed within a representational formalism which provides some degree of formal semantics to express the meaning of its assertions E.g. relational model, UML, frames, logics, RDFS, OWL…. E.g. relational model, UML, frames, logics, RDFS, OWL…. However, these differ in expressivity However, these differ in expressivity  p(x)  y API In RDFS, there is not much one can say about a part-of property If OWL we can: Define the properties partOf and hasPart as inverses, Define allValuesFrom restriction on the property partOf for all classes of things that are parts to the classes of things they are parts of, Define allValuesFrom restriction for the inverse property hasPart, Make partOf or hasPart transitive. See

What Demo Ontology Looks Like - Class Hierarchy and Assertions Airplane air-traffic object Physical- Object Airport fuel- truck Non- mobile- resource mobile- resource isa Gate isa Airport Runway comprisesRunway xsd:int runwayLength Lighting comprises isLitBy Represents the geospatial world from the perspective of the relevant domain Incoming data is mapped to this ontology upon entering the knowledgebase Quality measured as ability to represent concepts in a potential question Derived from the vocabulary of the users in this area Imply inheritance for properties over subclasses

12 Demo Goal Provide a set of ontologies Provide a set of ontologies Domain OntologyDomain Ontology Airports and Airplanes Airports and Airplanes Base Geospatial OntologyBase Geospatial Ontology Geometries from GML Geometries from GML Filter OntologyFilter Ontology Spatial Relationships Spatial Relationships Feature OntologiesFeature Ontologies AIXM, DAFIF, Gazetteer AIXM, DAFIF, Gazetteer These support: These support: A user asking a query in the vocabulary of his or her own perspectiveA user asking a query in the vocabulary of his or her own perspective Automatic query decomposition to original data source conceptsAutomatic query decomposition to original data source concepts Automatic discovery of appropriate data sourcesAutomatic discovery of appropriate data sources Ultimately, geospatial data interoperability that is transparent and useful to the userUltimately, geospatial data interoperability that is transparent and useful to the user Use different ontologies to address the problem modularlyUse different ontologies to address the problem modularly

13 Ontology Modularity Base Spatial Ontologies Base Spatial Ontologies Describes fundamental conceptsDescribes fundamental concepts Ontology of Geometries Ontology of Geometries Ontology of Spatial Relationships Ontology of Spatial Relationships Topological, Euclidean, Network basedTopological, Euclidean, Network based Spatial Domain Ontologies Spatial Domain Ontologies Describes concepts specific to a domainDescribes concepts specific to a domain Hydrology Hydrology Disaster Relief Disaster Relief Air Defense Air Defense Development and testing of these ontologies was done as part of the OGC Interoperability Experiment on Geospatial Semantic Web Development and testing of these ontologies was done as part of the OGC Interoperability Experiment on Geospatial Semantic Web We used several OGC standards as starting material for the ontologies.We used several OGC standards as starting material for the ontologies.

14 Sample “Logistic” Query What airports within meters of Saint Louis can support a C5? Data needs to come from multiple sources!Data needs to come from multiple sources! Aero Feature or Geo Feature? Statutory or Nautical? Straight-line or driving? Coordinate system? Feature property or non-spatial information?

15 Geospatial Ontology Usage Domain Ontology Web Feature Service Knowledge Base Geospatial Filter Ontology Base Geospatial Ontology (Derived from GML) Feature Data Source Ontology

16 Base Geospatial Ontology Foundation for all other geospatial related ontologies Foundation for all other geospatial related ontologies Analogous to (and very likely derived from) GML and the related abstract types Analogous to (and very likely derived from) GML and the related abstract types Will need to evolve over time; a rich ontology with the coverage of GML cannot be created overnight Will need to evolve over time; a rich ontology with the coverage of GML cannot be created overnight Geometry LineString PolygonPoint Spatial Region Centroid

17 Our Demo Domain Ontology Airplane air-traffic object Physical- Object Airport fuel- truck Non- mobile- resource mobile- resource isa Gate isa Airport Runway comprisesRunwa y xsd:int runwayLength Lighting comprises isLitBy Represents the geospatial world from the perspective of the relevant domain Incoming data is mapped to this ontology upon entering the knowledgebase Quality measured as ability to represent concepts in a potential question Derived from the vocabulary of the users in this area NavAid ILS… Uses Dynamic Entity isa

18 Feature Data Source Ontology Represents concepts needed to describe features returned from a feature server Represents concepts needed to describe features returned from a feature server Extends the concepts of the base geospatial ontology as related to the domain of the web feature server Extends the concepts of the base geospatial ontology as related to the domain of the web feature server Data Source Ontologies Derived from: Data Source Ontologies Derived from: DAFIFDAFIF Aeronautical data – US standard Aeronautical data – US standard Simple ontology mirrors DAFIF schema Simple ontology mirrors DAFIF schema AIXMAIXM Aeronautical data – US/European standard Aeronautical data – US/European standard Ontology mirrors XML schema Ontology mirrors XML schema GazetteerGazetteer City locations City locations

19 Geospatial Filter Ontology Ontology to represent geospatial relationships Ontology to represent geospatial relationships Used by the WFS client to represent queries Used by the WFS client to represent queries Used by the WFS to advertise available filters and accept filter queries Used by the WFS to advertise available filters and accept filter queries Overlaps Geometry operand Geometry operand

20 Ontologies Together as a Query C5CapableAirport 50000m radius DWithin satisfiesFilter City referenceGeometry PropertyIsLike satisfiesFilter “NAME” property “Saint Louis” literal

21 Ontologies Together in Action

22 Future Directions Investigate/develop spatial representations Investigate/develop spatial representations Develop ontology alignment tools and techniques Develop ontology alignment tools and techniques Prototype spatial semantic knowledgebase Prototype spatial semantic knowledgebase Semantic service oriented architectures Semantic service oriented architectures

23 Recap: Rationale for Ontologies: why they matter Quality ontologies serve to resolve semantic differences between disparate “informational concepts” such as business definitions and metadata descriptions, Quality ontologies serve to resolve semantic differences between disparate “informational concepts” such as business definitions and metadata descriptions, e.g. “Gauge Height = Stage = Stream Gauge”,e.g. “Gauge Height = Stage = Stream Gauge”, They do this by representing intended meaning in a formalism such as OWL (Web Ontology Language).They do this by representing intended meaning in a formalism such as OWL (Web Ontology Language). Build the framework for Semantic Service Oriented Architectures (SOA) such as supports standard messaging: Build the framework for Semantic Service Oriented Architectures (SOA) such as supports standard messaging: Geospatial ontologies allow the creation of Controlled Vocabulary for purposes such as navigation, discovery of geo-spatial data, etc.Geospatial ontologies allow the creation of Controlled Vocabulary for purposes such as navigation, discovery of geo-spatial data, etc. Formal ontologies provide a means for communication between or among people, organizations, and/or software systems through standardization and consistencyFormal ontologies provide a means for communication between or among people, organizations, and/or software systems through standardization and consistency Formal ontologies can be designed modularly with some general modules for use across systems or application areas. Formal ontologies can be designed modularly with some general modules for use across systems or application areas. In this way, ontologies can be exchanged among heterogeneous systems that may also use them differently.In this way, ontologies can be exchanged among heterogeneous systems that may also use them differently.