Ontological Resources andTop-Level Ontologies

Nicola GuarinoLADSEB-CNR, Padova, Italy

www.ladseb.pd.cnr.it/infor/ontology/ontology.html

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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

Language LCommitment K=<C,>

Ontology

Models M(L)

Intended models IK(L)

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The Ontology Sharing Problem (1)

M(L)

I A (L)

I B (L)

Agents A and B can communicate only if their intended models overlap

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The Ontology Sharing Problem (2)

M(L)

I A (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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ITOP(L)

IA(L)

M(L)

IB(L)

The role of foundational ontologies (1)

False agreement!

False agreement minimized

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Bad vs. Good Ontologies

Goodontology

Bad 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

top-level ontologydomain ontologytask & problem-solving ontology

application ontology

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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/bottom-up 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