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Joint ISPRS WG II/3 - WG II/6
Workshop on Multiple Representation and Interoperability of Spatial Data,
Hannover, Germany, February, 22 - 24, 2006
Geo-ontology Integration:
Identifying Issues, Dimensions
and Developing Guidelines
M. Kavouras & M. Kokla
School of Rural and Surveying Engineering
National Technical University of Athens
Structure of the presentation
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Definition of fundamental terms
Different perspectives
Principal characteristics of ontology integration
Fundamental questions of ontology integration
Three sub-processes
Directions to ontology integration
What is meant by “ontology”
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Ontology is usually defined as “a formal, explicit
specification of a shared conceptualization of a
domain” (Gruber, 1993).
• Provide complete and commonly accepted
descriptions – documentations of the concepts of a
domain
• GEOGRAPHIC ONTOLOGIES are usually
terminological: a concept is described by a term, a
natural language definition and relations to other
concepts.
What is meant by “integration”

Different terms to denote a number of related
processes: association, coordination, combining,
matching, mapping, translation, merging, alignment,
unification, etc.
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Fundamental objective of all approaches:
1. Compare the semantics of original ontologies
2. Determine the following:
• Whether the given ontologies are to some degree
similar, related, or disjoint.
• How to compare concepts in order to identify
similarities and heterogeneities.
• How to associate the original ontologies on the basis
of the previous findings.
What is meant by
“ontology integration”
Ontology integration: integration of different existing
ontologies (inter-ontology mapping)
vs.
 Ontology-based integration: integration of different
database schemata to a single reference (toplevel) ontology
vs.
 Data integration: based on a single model.
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Two perspectives
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A “higher” ontological perspective with an
interest in conceptualizing and representing
knowledge about a domain (in our case,
geographic reality)
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semantic conflicts due to different conceptualizations
and models of the domain in an information system.
A “lower” explication perspective with an interest
in formalizing, processing and associating existing
information or data.
conflicts in the specification of the conceptualization
(e.g., encoding differences, representation language
mismatches).
 terminological conflicts can be treated at the
explication level; but they often carry some semantic
weight
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Ontological and
semantic notions
are used differently
according to
TWO PERSPECTIVES
A “higher”
ontological
perspective
conceptualization
differences
terminological
differences
A “lower”
design/implementation
perspective
explication
differences
Conceptualization Differences (1)
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Perspective/interest. Often what determines the
concepts and taxonomies to be designed or
adopted is the application needs (different
application needs create different taxonomies).
Disciplinary training. Disciplines tend to develop a
common understanding of their domain
knowledge.
Methodology. In the scientific context, the methods
we employ often determine to a great extend what
is we see and how we partition reality (e.g., land
cover nomenclatures according to the
interpretation method used - remote sensing).
Conceptualization Differences (2)
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Granularity. The scale of analysis determines not
only the taxonomical detail but may create
completely different taxonomies (e.g., a 1:100000
land cover nomenclature differs considerably from
that of 1: 5000).
Ethno-/cultural-/socio-based view. Many
geographic concepts of a domain are the result of
constructive social agreement and partial
consensus.
Human cognitive diversity. When people work
autonomously, they perceive and conceptualize
geospace differently, creating thus their own
cognitive taxonomies.
DISCIPLINARY
TRAINING
INTEREST/
PERSPECTIVE
GRANULARITY
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Taxonomic
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diversity 5 7
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ETHNO-/SOCIO/CULTURAL-VIEW
METHODOLOGY
COGNITIVE
DIVERSITY
Principal characteristics
of ontology integration
1. Assumptions made about the source of semantics
and the objective of the process
2. Semantic level addressed
3. Input (source) / Output components
4. Method used
5. Degree of change - alteration caused to the
original ontologies
6. Degree of interaction or user involvement
Fundamental questions
of ontology integration (1)
Q1: Which semantics affect integration?
Action: Define the semantic elements which shall prevail integration.
Q2: Where semantics emanate from?
Action: Determine the available sources of semantics.
Q3: How is semantics derived?
Action: Use appropriate approach to extract semantic components
from available sources.
Q4: How are concepts and ontologies compared?
Action: Define which concepts and ontologies are to be compared
and the basis of their comparison.
Q5: How is similarity/heterogeneity among concepts
determined?
Action: Decide on how the comparison takes place and what the
possible/acceptable outcome of the comparison is.
Fundamental questions
of ontology integration (2)
Q6: How is heterogeneity resolved/reconciled?
Action: Decide on how heterogeneities among concepts are
reconciled
Q7: What type of integration is preferred?
Action: Define what resource ontologies are to be integrated and
their role during and after integration, if a target ontology is used to
guide integration, etc.
Q8: Is user/expert involvement essential in the process?
Action: Determine the degree of automation or interaction/expert
involvement needed in resolving complex cases.
Q9: How is the result evaluated?
Action: Determine the basis of assessing the result of integration, how
objective/subjective the result may be, what kind of inconsistencies
are expected, should be avoided, etc.
Input concepts
ontologies
Αρχικές
έννοιες - -Οντολογίες
SEMANTIC
ΕΞΑΓΩΓΗ
INFORMATION
ΣΗΜΑΣΙΟΛΟΓΙΚΗΣ
EXTRACTION
ΠΛΗΡΟΦΟΡΙΑΣ
Three subprocesses
for semantic
integration
Διαδικασία
Process
I 1
Semanticallyπλούσιες
rich concepts
Σημασιολογικά
έννοιες
CONCEPT
ΣΥΓΚΡΙΣΗ
COMPARISON
ΚΑΤΗΓΟΡΙΩΝ
Διαδικασία
Process
II 2
Similarities
and
Ομοιότητες
καιheterogeneities
ετερογένειες
INTEGRATION
ΟΛΟΚΛΗΡΩΣΗ
Integrated ontology
Ολοκληρωμένη
οντολογία
Διαδικασία
Process
III 3
Process I:
Semantic Information Extraction
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Source components: free text, corpora, thesauri,
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Taxonomic ontologies vs. formal ontologies.
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What constitutes semantic information ?
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specialized text (e.g., definitions), terms, nomenclatures, data
dictionaries, hierarchical classifications, database schemata,
etc.
Empirical ad hoc approaches attempting to
formalize the concepts involved, and design the
associated databases.
Information extraction (IE) approaches based on
NLU/NLP - central terms in computational linguistics
and artificial intelligence.
Process II:
Concept - Ontology Comparison
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Comparison and similarity measures reveal/depict
how difficult integration (Process III) will be.
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A comparison shall reveal and somehow measure
similarities or heterogeneities (conflicts).
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Similarity between geographic concepts can be
estimated by combining feature and linguistic
matching, and semantic distance calculation
(Tversky, 1977; Rodríguez & Egehhofer 2002; Yaolin
et al. 2002).
Process II also needs to resolve the heterogeneities.
Process III: Integration (1)
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Alignment is a mapping between concepts of
different ontologies bringing them into mutual
agreement.
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Translation/conversion utilities are used to provide
functionality.
No ontology is distorted.
A target ontology may or may not be aligned with the
resource ontologies.
Partial compatibility creates a merging of only those
parts of ontologies that are considered more similar.
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The merged parts distort the initial common ontology parts.
A target ontology may or may not be used for the merging
of the common parts.
Process III: Integration (2)
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Unification (also fusion), extends partial
compatibility to all ontologies and their concepts.
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Each resource ontology is distorted to become fully
compatible with the others; there is a single ontology at the
end.
The initial ontologies are distorted.
A target ontology may or may not be used for defining the
unified ontology.
True integration creates a single integrated
ontology whose parts are the resource ontologies
including some additional concepts necessary for
the association.
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The user deals with a single integrated ontology.
The resource ontologies are not distorted
A target ontology may or may not be used in the
integration.
m1
m2
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Alignment
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m5
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Partial
compatibility
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Unification
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True
integration
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Principal directions
to ontology integration
1.
2.
3.
4.
Conforming to a single central ontology
Manual ad-hoc mappings
Intuitive mappings based on “light” lexical information
Intuitive mappings based on explication
characteristics
5. Intuitive mappings based on structural similarity
6. Relating (grounding) to a single shared or top-level
ontology
7. Direct mappings based on “deep” semantics
8. Integration by view-based query processing
9. Compound similarity measures
10. Extensional mappings based on common spatial
reference
TO DISCUSS
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Core ideas behind intelligent integration
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Geospatial semantics (properties…)
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What is missing in the framework? Identify research
“holes”
DISCUSSION 2
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What is special about SPATIAL ONTOLOGIES
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Vocabulary – ontology of ontologies
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ONTOLOGIES (KR)- YES, SEMANTICS- NO (…later)
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1.
HOW to go from Simple iconic level to the formal level
2.
From the formal level to the semantic level
3.
Establish properies – context (neighborhood)
SEMANTIC IS NOT THEMATIC
DISCUSSION 3
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Cognitive basis for categorization
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Research on ontologies needed
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Not real ontologies existing
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Work on combining extensional and intensional
information useful - complementary
Difference between schema and ontology
integration
Missing : contextual analysis, relationships
DISCUSSION 3
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Forest ?????
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Similar concepts may have different reps
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TOP LEVEL ONTOLOGIES? Ambitious goal – USE the
same ontology to compare different domains
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How to derive semantic properties
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What is special about SPATIAL