Ontology Work @ GeoConnections’ CGDI & CCRS’ NRCan

1. Ontology Work @ GeoConnections’ CGDI& CCRS’ NRCan Brian McLeod mcleod@ccrs.nrcan.gc.ca Canada Centre for Remote Sensing

2. Intelec Geomatics Inc. (Montreal, Quebec) GeoInnovations (technology development program)

3. Overview • Semantic interoperability background • Ontology Service Project • Context • Introduction • Objectives • Methodology • Architecture • Software • Demonstration • Next Steps

4. Introduction [Brodeur] • Multiplication of geospatial datasources and increased usage of geospatial information technologies • NTDB, VMap, DCF, BDTQ, OBM, Geographic Data BC; • Geospatial data and services are more and more accessible on the Web • Canadian Geospatial Data Infrastructure (CGDI), NSDI; • Today, users are turned to various geospatial data sources to fulfill their needs; • Interoperability of geospatial data and geoprocessing, proposed at the beginning of the nineties, constitutes a solution for the sharing, re-use, and integration of geospatial data(McKee and Buehler 1998; Sondheim, Gardels and Buehler 1999).

5. Problem [Brodeur] • Availability of multiple geospatial databases on the Web; • Each database or information community uses a specificvocabulary; • Databases are heterogeneous at syntactic, structural and semantic levels; • Many users benefit from more than one geospatial database to satisfy their needs; • Many problems such as the difficulty to locate geospatial data • Locating: search, identification, selection and extraction of geospatial data from external sources.

6. Spatial pictogram descriptions: :0D ; :1D ; :2D ; ?:unknown geometry ; :multiple geometry ; :alternate geometry (see [Bédard, 1999 #231] and [Brodeur, 2000 #149] for more details). 1[Natural Resources Canada, 1996 #240]; 2[VMap, 1995 #117]; 3[BC Ministry of Environment Lands and Parks (Geographic Data BC), 1992 #121]; 4[OBM, 1996 #120]; 5[Québec, 2000 #123]; 6[New Brunswick, 2000 #243]. Problem How does someone assess if the result he/she gets from his/her request corresponds to the initial perception of the reality he/she had in mind when he/she sent that request?

7. Context – Metadata discovery • To bridge terminology and language gaps • Search exactly the same concepts, vocabulary and language that the database uses; otherwise, their search may not yield relevant results.

8. Project – Multiusage, Multistandard, and Multilingual Geospatial Ontology Service • Develop a geospatial ontology service that can be used by applications and other services • The project was funded in March 2003 under the CGDI GeoInnovations program

9. Objectives • Examine requirements related to geospatial ontologies • Identify the operations that a service must fulfill to meet requirements • Define Web protocols to access the service • Develop the service using interoperability standards • Technology assessment

10. Participants • Developers • CRG, Université Laval • Intelec Geomatics • Users • Ministry of National Defence • Ministère des Ressources naturelles du Québec • Ministry of Fisheries and Oceans (CHS • Natural Resources Canada (CTI-S & CCRS) • NatureServe Canada • Environment Canada • Commission for Environmental Cooperation

11. Inputs • Scope • Language known by client (service) • Ontology of keywords • Ontology in text or DBMS • Initial Content (GCMD-bilingual, IHO B6 and S57) • Guide for building ontologies • UTF-8 for character encoding

12. Protégé - software related • Free, open source, java • Customizable editor • Plugins can be added • Database can be accessed by an API

13. Protégé can be used for the following • Class modeling. Protégé provides a graphical user interface (GUI) that models classes (domain concepts) and their attributes and relationships. • Instance editing. From these classes, Protégé automatically generates interactive forms that enable you or domain experts to enter valid instances. • Model processing. Protégé has a library of plug-ins that help you define semantics, perform queries, and define logical behavior. • Model exchange. The resulting models (classes and instances) can be loaded and saved in various formats, including XML, UML, and RDF (Resource Description Framework). Protégé also provides a scalable database back end.

14. Data Model

15. Technologies

16. Operations • GetCapabilities • GetOntology • GetDefinition • GetPrefered • GetSimilar • GetTranslation • GetGraph

17. Demonstration http://intelecgeomatics.com:8080/ogm3/default.jsp

18. Entry Page

19. Server Capabilities

20. GetOntology Request

21. GetOntology Response

22. GetDefinition Request

23. GetDefinition Response 1

24. GetDefinition Response 2

25. GetPrefered Request

26. GetPrefered Response

27. GetSimilar Request

28. GetSimilar Response

29. GetTranslation Request

30. GetTranslation Response

31. GetGraph Request

32. GetGraph Response

33. Thank you Questions ??

34. M3GO Protégé-2000 Presentation

35. Protégé - software related • Free, open source, java • Customizable editor • Plugins can be added • Database can be accessed by an API

36. Protégé can be used for the following • Class modeling. Protégé provides a graphical user interface (GUI) that models classes (domain concepts) and their attributes and relationships. • Instance editing. From these classes, Protégé automatically generates interactive forms that enable you or domain experts to enter valid instances. • Model processing. Protégé has a library of plug-ins that help you define semantics, perform queries, and define logical behavior. • Model exchange. The resulting models (classes and instances) can be loaded and saved in various formats, including XML, UML, and RDF (Resource Description Framework). Protégé also provides a scalable database back end.

37. Metaclasses M3GO implementation inside Protégé is composed of 3 metaclasses: • ONTOLOGIE • CONCEPT • NOM • A metaclass is a template, or a class whose instances are themselves classes

38. Each metaclass is defined by a set of attributes called slots

39. Subclasses • M3GO uses 11 subclasses to implement the model • Each subclass is also defined by a series of properties (slots)

40. Adding a slot Slots are properties or relationships between classes

41. Building an Ontology Building an ontology is done by implementing previously defined metaclasses in a hierarchical manner

42. Example: a Valley

43. Forms are automatically generated and fully customisable

44. Protégé’s plugins • Storage • CLIPS • XML • XML Schema • RDF • OIL (Ontology Inference Layer) • DAML+OIL • UML • XMI • Visualization • Jambalaya • TGVizTab • OntoViz • Project and file management • BeanGenerator • DataGenie • Prompt • Etc.

45. Thank you Questions ??