Semantic search engine for
geographic data
Ontologies for urban development:
conceptual models for practitioners
Torino, 17 & 18/10/07
C. Pegoraro, M. Velluto
Direzione SISTEMI TERRITORIALI E AMBIENTALI
Semantic search engine for geographic data
OUR DOMAIN: GEOGRAPHIC DATA PRODUCED BY LOCAL ADMINISTRATIONS
SITAD
is the instrument that allows finding and consulting data. It consists in two main
services:
3.
Search engine
. Data search in a metadata catalogue. Three ways:
Subjects – classified in a simple taxonomy
Simple – keywords
Advanced – combines keywords, subject and other info (geographic
coverage, data responsible, scale etc.)
Search results: metadata forms providing data related information, summarized in a
properties list according with Dublin Core standard (or ISO19115: more
detailed)
CSI Piedmont manages a great amount of geographic data: detailed territorial knowledge
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Semantic search engine for geographic data
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Semantic search engine for geographic data
Search engine
. Data search in a metadata catalogue. Three ways:
•
Subjects – classified in a simple taxonomy
•
Simple – keywords
•
Advanced – combines keywords, subject and other info (geographic
coverage, data responsible, scale etc.)
Which is our
purpose
?
Add the fourth way to search data in SITAD:
ontology based
semantic search
Our purpose
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Theoretical background: FOUR PILLARS for ontologies
Semantics
ONTOLOGY
Schema
Foundational
Ontology
CONCEPT
DICTIONARY
CONCEPTUAL
SCHEMA
META MODEL
Lexicon
+
+
Semantic search engine for geographic data
Treccani Vocabulary of the Italian Language – textual
Treccani Vocabulary of the Italian Language – visual
Regulations on thematic extents: Italian Road Code,…
Technical & scientifical literature
CONCEPT
DICTIONARY
Lexicon
Semantics
Foundational
Ontology
CONCEPTUAL
SCHEMA
META MODEL
+
+
ONTOLOGY
Schema
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Semantic search engine for geographic data
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Semantic search engine for geographic data
CONCEPT DICTIONARY Hints 2/3
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Semantic search engine for geographic data
CONCEPT
DICTIONARY
Lexicon
Semantics
Foundational
Ontology
CONCEPTUAL
SCHEMA
META MODEL
+
+
ONTOLOGY
Schema
Experimental Phase: REFERENCE MATERIAL 2/3
SITAD, Regione Piemonte
INTESA GIS, Italy, Centro Interregionale
EUROROADS, eContent
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Semantic search engine for geographic data
CONCEPTUAL MODELLING Hints 2/3
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Semantic search engine for geographic data
CONCEPT
DICTIONARY
Lexicon
Semantics
Foundational
Ontology
CONCEPTUAL
SCHEMA
META MODEL
+
+
ONTOLOGY
Schema
Experimental Phase: REFERENCE MATERIAL 3/3
ISO Standards
JTC 1, Information Technology JTC 211, Geographic Information
other ISO thematic series
GEOUML from INTESA GIS specifications
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Semantic search engine for geographic data
Allen
Egenhofer
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META MODEL Hints 3/3
Semantic search engine for geographic data
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Semantic search engine for geographic data
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Semantic search engine for geographic data
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Semantic search engine for geographic data
Conceptual scheme (classes and relations)
High level
Conceptual scheme and objects
Low level
Certificated through national and international standards
Objects/instances
(metedata forms)
Certificated through Dublin Core or ISO
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To check the scheme: develop three parts of the ontology
Geometric ontology – referring to ISO TC 211 SERIES
A practical example
Thematic ontology – Civil Protection (referring to JRC ontology elaborated for the Regional Program for Risk Forecast and Prevention)
Thematic ontology – Viability (referring to Intesa GIS specifications)
Semantic search engine for geographic data
Geometric ontology:
Describes the relations
connecting classes of
geometrical instances
Thematic ontology:
Describes the relations
connecting concepts in a
specific thematic discipline
(e.g.: viability or civil
protection)
How represent?
Two kinds of ontology
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Geometric ontology:
•Classes: Contain geometric entities (e.g.: 2DSurfaces, 2DPoints, 3DComposite Curves etc)
•Relationships: hierarchical and topological (the 2Dsurfaces belong to the Surface class/
A 2Dsurface can adjoin to another or can contain it)
•Instances: Metedata forms (e.g. the form concerning the landslide areas is contained in the
2Dsurface class)
Thematic ontology:
•Classes: Contain conceptual entities (e.g.: In Civil Protection we have the Class ‘Risk’)
•Relationships: hierarchical and logical (e.g..: in Civil Protection, the Risk calculation requires the
defiition of other other concepts, such as Target, Impact Area, Risk source, etc)
•Instances: No real objects
Semantic search engine for geographic data
Has subclass
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Semantic search engine for geographic data
Detail: hierarchical and topological relationships in geo ontology
contains
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Requires
Internal to Internal to
Semantic search engine for geographic data
Integrating the ontologies
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The consistency of the represented schemes
has been checked step by step using a Racer
Pro reasoner
Semantic search engine for geographic data
•Which elements
are required
for
Risk
calculation
in
Civil Protection
?
•Which data (available in SITAD)
have
interest
in
Civil Protection
and
are
necessary
for
Risk Calculation
?
•Which data (available in SITAD) can
possibly
represent
Impact Areas
?
•What does a
Transport Network
Conlusions: semantic benefits
We can give answers to some complex questions…
•Impact Areas, Targets, Risk sources
and
Resources
•Transport Network
and
Landslides
Areas
•Every data
contained in
Surface
Class
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