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