Presentation is loading. Please wait.

Presentation is loading. Please wait.

Ontology GeoConnections’ CGDI & CCRS’ NRCan

Similar presentations


Presentation on theme: "Ontology GeoConnections’ CGDI & CCRS’ NRCan"— Presentation transcript:

1 Ontology Work @ GeoConnections’ CGDI & CCRS’ NRCan
Brian McLeod Canada Centre for Remote Sensing Salutations …..

2 Intelec Geomatics Inc. (Montreal, Quebec)
The M3GO project is a small project funded by GeoConnections program. It is rather a “proof of concept” Of Ontology/Semantic work that is needed while developing an NSDI such as the Canadian Geospatial Data Infrastructure (CGDI), helping in data discovery through Portal such GeoConnections Discovery Portal. 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 data sources 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). Currently, we note a multiplication of geospatial data sources and an increased use of geospatial information technologies. Among others, there is the NTDB, the VMap librairies, the digital cartographic files, and several provincial geospatial data sources. Geospatial data and services are more and more available on the Web because of infrastructures specially developed for this purpose. Here, we think specifically to the CGDI and to the NSDI in the United States. Today, users of geospatial data are more and more making use of multiple heterogeneous data sources to satisfy their specific needs. At the beginning of the nineties, interoperability of geospatial data and geoprocessing has been proposed as a solution for sharing, re-using and integrating geospatial data.

5 Problem [Brodeur] Availability of multiple geospatial databases on the Web; Each database or information community uses a specific vocabulary; 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. At time being, the problem is that various geospatial databases exist and are accessible on the Web. Each database makes use of a specific vocabulary that has been chosen based on the needs of those who have developed these databases or the information community to which a database adheres. Therefore, databases are typically heterogeneous at the syntactic, schematic and also semantic level. However, users of geospatial data, who access more than one database to fulfill their specific needs, experience many problems such as access, sharing, and integration but more specifically the problem to locate the exact data they need; this is the problem that I have addressed in my research work. I intend here by locating the exact data, the search, the identification, the selection, and the extraction of geospatial data from external sources.

6 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? Here, we have a sample of data types extracted from six distinct geospatial data sources. They depict same phenomena of the topographic Reality differently. (Click) For instance, for the hydrographic theme, the NTDB uses … whereas Vmap uses …. For the vegetation theme, VMap uses … whereas British Columbia uses …. If I were a geospatial data user, I could have the following questions : What geospatial data fit my needs best? How do I integrate these data into a consistent set? Even more,(Click) how do I assess if the result I get from a query fit the initial perception I had of Reality when I submitted that query? 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].

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. One of the important problems facing users and providers of geospatial information is to bridge terminology and language gaps that currently hinder the flow of information. At the moment, users searching for information from geospatial databases must know and use in their search exactly the same concepts, vocabulary and language that the database uses; otherwise, their search may not yield relevant results. (Jean Brodeur’s slide is a very good example to showcase). For instance, users searching a database that is documented in English may not get results if they enter a key word that is French. Similarly, they may not get results if they enter a key word that is singular instead of plural, or that relates to but does not match a term recognized by the provider.

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 under the CGDI GeoInnovations program - An ontology is an explicit specification of some topic. - It is a formal and declarative representation which includes the vocabulary (or names) for referring to the terms in that subject area and the logical statements that describe what the terms are, how they are related to each other, and how they can or cannot be related to each other. - Ontologies therefore provide a vocabulary for representing and communicating knowledge about some topic and a set of relationships that hold among the terms in that vocabulary (e.g. Wine example Ontology 101) - Thesauri or Taxonomies are specific cases of ontologies

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 Implement a server with ontologies in at least 2 languages (French and English) experiment results with project partners Integrate the M3GO service to portal services (not implemented yet) Integrate the M3GO service to the M3Cat cataloguing tool (not implemented yet)

10 Participants Developers Users CRG, Université Laval Intelec Geomatics
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 CRG - Centre for Research in Geomatics, Laval University Quebec CIT-S – Centre for Topographic Information in Sherbrooke (Natural Resources Canada) CCRS – Canada Centre for Remote Sensing (Natural Resources Canada)

11 Inputs Scope Ontology in text or DBMS
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 GCMD – Global Change Master Directory Science Keywords in French and English IHO B6 – International Hydrographic Organization Feature names gazetteers e.g. Ridge, Valley, Slope, fans IHO S57 – International Hydrographic Organization Marine Objects e.g. Fog Signal, Ice area, Inshore traffic zone, Light float, Pipeline, Tidal stream

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 This data model was developed by JM Proulx (CRG-Laval University) as guideline for M3GO project. Intelec team uses the model to guide the development of meta classes, classes and subclasses (11) within Protege 2000, 3 metaclasess are developed within Protege 2000 i.e. Ontology, Concept and Name. Then populated the classes/sub-classes with GCMD Science Keywords provided by CCRS (French and English), build the relationship between french and english terms, etc…

15 Technologies A Java API is used to populate Protégé 2000 classes with GCMD content

16 Operations GetCapabilities GetOntology GetDefinition GetPrefered
GetSimilar GetTranslation GetGraph

17 Demonstration http://intelecgeomatics.com:8080/ogm3/default.jsp
Use terms related to “Climate Change” for instance: Snow Mass, Skin temperature, Methane, Ozone Select GetPreferred with GCMD in English for the term Ozone,  the service returns that the term is preferred Select GetSimilar ….. Try to find a “definition” by using “GetDefinition” operation with term = Guyot and GCMD as an Ontology- no definition is provided within GCMD Use the same term with IHO B6  a definition is provided Use skin temperature with GetGraph operation or Ottawa with Gazetteer

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 Slots are properties or relationships between classes
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 Etc. 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 ??


Download ppt "Ontology GeoConnections’ CGDI & CCRS’ NRCan"

Similar presentations


Ads by Google