Download Conceptual Modeling and Ontological Analysis

Ontological Resources and
Top-Level Ontologies
Nicola Guarino
LADSEB-CNR, Padova, Italy
www.ladseb.pd.cnr.it/infor/ontology/ontology.html
Main socio-economic needs
• Mutual understanding more important than mass interoperability
– Small progress, high payoff
• Cognitive transparency as a key for knowledge trustability
– open source vs. open knowledge
– transparency vs. invisibility
– quality evaluation and certification
• Seamless knowledge integration (H-H, H-C, C-C, H-C-H, C-H-C)
• Co-operative conceptual analysis
– Distinguished discipline (theory, methodology)
– Ad-hoc tools
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The problem with ontologies:
they are approximate characterizations
Conceptualization C
Commitment K=<C,I>
Language L
Models M(L)
Intended
models IK(L)
Ontology
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The Ontology Sharing Problem (1)
Agents A and B can communicate only if their intended models overlap
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The Ontology Sharing Problem (2)
M(L)
IA(L)
I B(L)
Two different ontologies may overlap while their intended models do not
(especially if the ontologies are not accurate enough)
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The role of foundational ontologies (1)
ITOP(L)
M(L)
False agreement minimized
IA(L)
IB(L)
False agreement!
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Bad vs. Good Ontologies
Bad ontology
Good
ontology
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The role of foundational ontologies (2)
• Bottom-up integration of domain-specific ontologies can
never guarantee consistency of intended models (despite
apparent logical consistency).
• Top-level foundational ontologies
– Simplify domain-specific ontology design
– Increase quality and understandability
– Encourage reuse
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Hierarchies of ontologies
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Ontology standardization challenges
• Development of a Core Meta-level Ontology
• Development of a library of Certified Foundational
Ontologies, as a result of harmonization and formal/technical
review of most used ontologies, lexical resources, metadata
content standardization proposals (mixed top-down/bottomup strategy)
• Adequate support for Co-operative ontology development
and standardization (see present difficulties of IEEE SUO)
– Tools
– Management
– Official recognition
– Dedicated resources (separated from language standardization
initiatives!)
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Current ontology standardization
initiatives
• Current initiatives
– SUO (SUO consortium proposal)
– Global WordNet Consortium
– ISO SC4
– eCommerce standards (UCEC, ebXML,…)
– Cultural repositories standards (Harmony, CIDOC)
– CEN/ISSS EC WG (MULECO)
– DAML (especially DAML-S)
– [W3C Web Ontology Working Group]
• Projects
– OntoWeb
– WonderWeb
– ...
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The OntoWeb strategy (1)
• Devote ad-hoc resources to content issues, separating
content from languages and tools
• Take existing standardization proposals seriously
• Develop a preliminary framework for characterizing and
comparing them
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The OntoWeb strategy (2)
• Select a few specific clusters of standardization proposals
which
– Are suitable for ontology-based harmonization
– Are of high interest for the EC (eCommerce, Enterprise
Integration)
– Show a concrete interest (and allocation of resources)
from the standardization bodies
– Involve at least 2-3 OntoWeb members willing to invest
resources on their own funds.
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The OntoWeb strategy (3)
• Implement a mixed bottom-up/top-down approach
– Looking at existing proposals to identify foundational
problems
– Applying well-founded principles and methodologies to existing
standards
• Aim at harmonization and mutual understanding
(does not necessarily imply modification nor compatibility)
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General research priorities
• Coding and structuring semantic content as different research
activities [see W3C as a bad example]
• More interdisciplinary work between different disciplines
(philosophy, linguistics, cognitive science, computer science) and
communities (DB, IS, OO, WWW, KE, KR, KM, KO, IR, NLP)
• Explicit recognition of theoretical foundations (learn from DL)
• Ad-hoc effort on tools for cooperative ontology development
and standardization
• Adequate support of large scale RTD activities in content
standardization and content metadata harmonization NOW!
– Linguistic ontologies vs. general and application ontologies
– e-Commerce vs. PDM and Digital Libraries
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Formal tools for ontological analysis
• Ontology-based comparison and evaluation of axiomatic
theories: expressivity, accuracy, domain richness, cognitive
adequacy
• Theories of formal ontology:
– Theory of Parts
– Theory of Wholes
– Theory of Essence and Identity
– Theory of Dependence
– Theory of Qualities
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Strategic domains for the SW
• Ontology of information and information processing
– Data, documents, media, representation structures…
– The author-document-subject relationship
– Semiotic relations
• Ontology of social entities
– Societies, communities, organizations, laws, contracts,
decisions…
• Ontology of social co-operation and interaction
• Ontology of artifacts
– Topological, morphological, kinematic, and functional
features as essential features for cognitive interaction
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Conclusions
• Well-founded upper level ontologies unavoidable
• Cognitive transparency is the basis for trustability
• Mutual understanding more important than mass
interoperability
• Mixed top-down/bottom-up strategy for cluster-based
interoperability, supported by semantic links among clusters
• Ad-hoc resources for content standards (separate from
language standards resources)
• Challenging research areas
– Ontology of social reality (interaction, cooperation, trust, control…)
– Cooperative ontology development based on argumentation theory
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