1. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Ontologies for the Integration of Geospatial Data Michael Lutz Semantics and Ontologies for GI Services April 24-28, 2006

2. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Goals Get an idea how ontologies can be used for the integration of geospatial data Define a shared vocabulary for the domain of landcover classifications Define land use classes for CORINE land cover classification Execute simple and defined queries

3. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Data Integration with Ontologies Motivation: Different classification schemes (e.g. for landuse or geological categories) in different countries (e.g. A,SLO,I) or user communities Goal: Enable users to use a familiar vocabulary and translate to other classification schemes Approach:  Define “shared vocabulary” (aka “skeleton ontology”)  Define class definitions for each classification scheme based on shared vocabulary  Define query using the shared vocabulary or an existing classification scheme  Find similar or matching concepts for the query

4. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Dataset 2 Dataset 1 equivalence or subsumption based on Domain Ontology Ontological (DL) description of the query concept “suitable for creating a business park” Query concept Application Ontology Concepts Ontologies for Enhanced GI Discovery Hybrid Ontology Approach Logical Reasoning Classification Scheme 2 Classification Scheme 1 Ontological (DL) description of the classes used in the classification Where are there areas that are suitable for creating a business park?

5. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Hybrid Approach Shared Vocabulary = One or several domain ontologies Especially domain ontologies should be property-centered, i.e. define properties and their ranges (and domains) Shared Vocabulary (property-centered) Application Ontology Existing Classification Scheme User-defined Classification Scheme Application Ontology Query Existing Classification Scheme provides vocabulary for define semantics for classes in

6. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Use Defined Classes Many ontologies are simple is-a hierarchies  little flexibility for adding new concepts (or queries) To add this flexibility, properties (not classes) should be seen as the primary entities Concepts should be defined using existing properties  use cardinality constraints and value restrictions to further constrain the range of a role inside concept definitions

7. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Types of Queries Simple Queries  Use an existing concept in one application ontology (i.e. a class in one classification system)  Look for matching (i.e. subsumed) concepts in other application ontologies  E.g. “show me all classes in your classification that correspond to my industrial complex class” Defined Queries  Use terms from the shared vocabulary to build a user- defined query concept  Look for matching (i.e. subsumed) concepts in all application ontologies  E.g. “show me all classes in your classification that have an inclination of less than 10% and have good transport connections”

8. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Example Application: Geological Maps Daten aus dem Kartenwerk Geologische Karte (DGK) des LAGB LSA, Geologische Grundkarte im Maßstab 1:25.000 Basis for engineering and hydro-geological decision making  different times  different authors  different areas  different classification systems  Semantic heterogeneity

9. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Goals establish a service for semantic mapping between the different classification systems Enable user-specific property-based queries

10. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Feinsand Grobsand Mittelsand Shared Vocabulary GESTEIN Sand Ton Schluff Karbonat Bestandteil hatNebenbestandteilehatHauptbestandteile hatKonsistenz Konsistenz Lagerung istGelagert 1...30...* 1 0...1

11. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Application/Query Concept Löss Grob- Schluff hatNebenbestandteilehatHauptbestandteile k. A. istGelagert 1...30...* 1 0...1 Locker Kalk k. A. istGelagert 0...1 hatKonsistenz

12. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Exercise 1: Define a Shared Vocabulary Look at the CORINE land cover classification at terrestrial.eionet.eu.int/CLC2000/classes Pick a few classes and try to come up with  Properties that describe them  The “fillers” of these properties -Find a common superclass that can be used as a range -Find subclasses for the individual fillers -Do they form value partitions? Try to model these properties and filler classes in OWL  What kind of information is easy to map to OWL? What is more difficult?

13. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Exercise 2: Define Land Cover Classes Split in 2 groups, using different land cover classification systems 1. CORINE 2. Realraumanalyse (www.uni-klu.ac.at/geo/ projekte/realraum/Typen.htm) Use common shared vocabulary  Import babyz.uni-muenster.de/ontologies/ont- skeleton.owl into a new Protégé project Create defined classes for your classification system Exchange results & do simple and defined queries

14. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Importing Ontologies Create and save a new Protégé project Import ontology

15. Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006 Importing Ontologies