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
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
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
Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006
Dataset 2Dataset 1
equivalence or subsumption
based on
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
ClassificationScheme 2
ClassificationScheme 1
Ontological (DL) description of the classes used in the classification
Where are there areas that are suitable for creating a business park?
John Smith
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)
ApplicationOntology
ExistingClassification
Scheme
User-definedClassification
Scheme
ApplicationOntology
Query
ExistingClassification
Scheme
provides vocabulary for
define semantics for classes in
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
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”
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-geologicaldecision making
different times
different authors
different areas
different classification systems
Semantic heterogeneity
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
Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006
Feinsand
Grobsand
Mittelsand
Shared Vocabulary
GESTEIN
Sand
Ton
Schluff
KarbonatBestandteil
hatNebenbestandteilehatHauptbestandteile
hatKonsistenz
Konsistenz
LagerungistGelagert
1...3 0...*
1
0...1
Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006
Application/Query Concept
Löss
Grob-Schluff
hatNebenbestandteilehatHauptbestandteile
k. A. istGelagert
1...3 0...*
1
0...1
Locker
Kalk
k. A. istGelagert
0...1
hatKonsistenz
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?
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. CORINE2. 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
Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006
Importing Ontologies
• Create and save a new Protégé project
Import ontology
Ontologies for the Integration of Geospatial DataTU Wien, April 24-28, 2006
Importing Ontologies