Ontological Resources and Top-Level Ontologies

1. Ontological Resources andTop-Level Ontologies Nicola Guarino LADSEB-CNR, Padova, Italy www.ladseb.pd.cnr.it/infor/ontology/ontology.html

2. 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

3. Intended models IK(L) Ontology The problem with ontologies:they are approximate characterizations Conceptualization C Commitment K=<C,I> Language L Models M(L)

4. The Ontology Sharing Problem (1) Agents A and B can communicate only if their intended models overlap

5. The Ontology Sharing Problem (2) Two different ontologies may overlap while their intended models do not (especially if the ontologies are not accurate enough)

6. The role of foundational ontologies(1) ITOP(L) M(L) False agreement! IB(L) False agreement minimized IA(L)

7. Bad ontology Goodontology Bad vs. Good Ontologies

8. 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

9. Hierarchies of ontologies

10. 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!)

11. 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 • ...

12. 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

13. 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.

14. 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)

15. 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

16. 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

17. 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

18. 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