Ontologies and Classifications

1. Ontologies and Classifications Nicola Guarino Laboratory for Applied Ontology (LOA) Institute for Cognitive Sciences and Technologies (ISTC-CNR) Trento, Italy www.loa-cnr.it

2. Summary • Classifications have a central role within information architecture • Proper use of classifications requires understanding their terms • Especially in presence of multiple, heterogeneous classifications • Main role of [computational] ontologies is to clarify the meaning of terms • Therefore, “ontology” is not just a trendy name for “classification” Ontologies and classifications play complementary roles in information architecture

3. Functions of classifications • Support information retrieval and analysis. • partition the search space on the base of pre-determined criteria (encoded by syntactic keys) • Provide triggers for action.

4. Pictures Work Vacations Home Europe Italy A simple classification What’s the meaning of these terms? What’s the meaning of arcs? …they do not represent analytic relationships!

5. The source of all problems: different languages, different conceptualizations

6. A first solution: glossaries and thesauri • Glossaries: link terms to concepts, described informally by glosses • Thesauri: add structural relationships (generalization, part, dependence, causation…) among terms (and concepts). • Multilingual glossaries and thesauri are available for many domains. • General thesauri (e.g., WordNet) are available for many languages

7. Standard glossaries and thesauri can help, but... • Defining standard vocabularies is difficult and time-consuming • Once defined, standards don’t adapt well • Heterogeneous domains need a broad-coverage vocabulary • People don’t implement standards correctly anyway • Vocabulary definitions are often ambiguous or circular • Accessing and integrating heterogeneous glossaries and thesauri becomes a nightmare

8. The need to focus on CONTENT • The key problems • content-based information access (semantic matching) • content-based information integration (semantic integration) • To approach them, content must be studied, understood, analyzed as such, independently of the way it is represented. • Computer technologies are not really good for that (focus is usually on representation and reasoning) • A strong interdisciplinary approach is needed

9. What is an ontology

10. Ontology, lexicon, semantics • Distinctions among contents: Ontology (capital ‘o’) • Reference to content: Lexicon, via Semantics • Every organization, every computer system • Makes (implicit) ontologic assumptions • Adopt a certain lexicon, to which an intended semantics is ascribed.

11. Ontology and Ontologies • Ontology: the philosophical discipline • Study of the nature and structure of being qua being (content qua content) • ontologies: Specific (theoretical or computational) artifactsexpressing the intended meaning of a vocabularyin terms of primitive categories and relations describingthe nature and structure of a domain of discourse Gruber: “Explicit and formal specifications of a conceptualization”

12. apple LE same conceptualization mela LI What is a conceptualization • The implicit rules used to structure reality as perceived and organized by an agent, independently of: • the vocabulary used • the actual occurence of a specific situation • Different situations involving same objects, described by different vocabularies, may share the same conceptualization.

13. An example: the concept of red a b {a} {b} {a,b} {}

14. Conceptualization Perception Reality State of affairs State of affairs relevant invariants across situations:D,  Perceivedsituations Phenomena Bad Ontology Ontological commitmentK (selects D’D and ’) Models MD’(L) Ontology InterpretationsI Intended models for each IK(L) Ontology models Language L ~Good

15. Less good BAD WORSE Good Ontology Quality: Precision and Coverage High precision, max coverage Low precision, max coverage Max precision, limited coverage Low precision, limited coverage

16. Why precision is important Farmer’s ontology Company’s ontology What “apple” means for the juice company What “apple” means for the farmer Possible interpretations of “apple” Area of falseagreement!

17. Ontologies and...

18. Levels of Ontological Precision game(x)  activity(x) athletic game(x)  game(x) court game(x)  athletic game(x)  y. played_in(x,y)  court(y) tennis(x)  court game(x) double fault(x)  fault(x)  y. part_of(x,y)  tennis(y) game athletic game court game tennis outdoor game field game football tennis football game field game court game athletic game outdoor game Axiomatic theory Taxonomy game NT athletic game NT court game RT court NT tennis RT double fault Glossary DB/OO scheme Catalog Thesaurus Ontologicalprecision

19. analytic relationships among terms! Ontologies and taxonomies

20. Ontologies vs. classifications • Classifications focus on: • access, based on pre-determined criteria (encoded by syntactic keys) • Ontologies focus on: • Meaning of terms • Nature and structure of a domain

21. Ontologies vs. Database Schemas • Database schemas: • Constraints focus on data integrity • Relationships and attribute values out of the DoD • Typically non-executable • Ontologies: • Constraints focus on intended meaning • Relationships and attribute values first class citizens • Typically executable

22. A single, imperialistic ontology? • An ontology is first of all for understanding each other • ...among people, first of all! • not necessarily for thinking in the same way • A single ontology for multiple applications is not necessary • Different applications using different ontologies can co-exist and co-operate (not necessarily inter-operate) • ...if linked (and compared) together by means of a general enough basic categories and relations (primitives). • If basic assumptions are not made explicit, any imposed, common ontology risks to be • seriously mis-used or misunderstood • opaque with respect to other ontologies

23. Idea of Chris Welty, IBM Watson Research Centre, while visiting our lab in 2000 Which primitives? The role of ontological analysis • Theory of Essence and Identity • Theory of Parts (Mereology) • Theory of Wholes • Theory of Dependence • Theory of Composition and Constitution • Theory of Properties and Qualities The basis for a common ontology vocabulary

24. The semantic web architecture [Tim Berners Lee 2000]

25. Formal Ontology • Theory of formal distinctionsand connectionswithin: • entities of the world, as we perceive it (particulars) • categories we use to talk about such entities (universals) • Why formal? • Two meanings: rigorous and general • Formal logic: connections between truths - neutral wrt truth • Formal ontology: connections between things - neutral wrt reality

26. When is a precise (and well-founded) ontology useful? • When subtle distinctions are important • When recognizing disagreementis important • When careful explanation and justification of ontological commitment is important • When mutual understanding is more important than interoperability.

27. Role of ontologies in information architecture(thanks to Dagobert Soergel) • Relate concepts to terms. Clarify their meaning by providing a system of definitions. • Provide a semantic road map and common conceptual reference tool across different disciplines, languages, and cultures • Make medical concepts clear to social science researchers and vice versa… • Improve communication. Support learning by helping the learner ask the right questions • Support information retrieval and analysis • Support the compilation and use of statistics • Support meaningful, well-structured display of information. • Support multilinguality and automated language processing • Support reasoning.

28. Conclusions • In general, classifications are not ontologies • Some classifications are ontologies • Ontologies are needed to understand, integrate, reason on classifications • Every ontology induces a classification • Both ontologies and classifications are a fundamental tool for information architecture

29. A new journal:Applied Ontology • Editors in chief: • Nicola Guarino • ISTC-CNR • Mark Musen • Stanford University • IOS Press • Amsterdam, Berlin, Washington, Tokyo, Beijing • www.applied-ontology-org