1. February 24, 2006 ONTOLOGIES Helena Sofia Pinto ( sofia.pinto@dei.ist.utl.pt )

2. February 24, 2006 Summary Knowledge sharing Ontologies –What is an ontology? –Kinds of ontologies –How are ontologies built? Kind of life cycle Ontology building processes –Ontology building tools –Application areas and challenges –Where is the research?

3. February 24, 2006 Knowledge Sharing Problem: –The cost of knowledge based systems –Building the knowledge base from scratch KB Components –Medical diagnosis and medical tutoring Vocabulary definition: disease, organ, pathogenic agents (bacteria, virus, etc), kinds of bacteria (coli, coccos – estreptococcos, estaphilococcos -, etc) etc. – ontology –Electronic diagnosis vs medical diagnosis Raise hypothesis, test, refine, etc. – problem solving method

4. February 24, 2006 Knowledge Sharing Solution: –Reuse and Sharing of knowledge Translation of knowledge bases between different KR languages Arbitrary differences among systems belonging to the same family Remote access to the knowledge base of another system Meaning of what is shared: Lack of consensus about vocabulary

5. February 24, 2006 What is an ontology? Capture the static knowledge in a given domain that is accepted and sharable across applications and groups Defs: –An explicit formal specification of a shared conceptualization –a vocabulary of terms and some specification of their meaning

6. February 24, 2006 What is an ontology? Set of symbols (concepts) + hierarchy (organized) + some specification of their meaning (restrict the possible interpretations for those symbols) Concepts are defined by their relations with other concepts xpto xpt1 xpt2 O1 xv xv1 xv2 O2 rel1 ist

7. February 24, 2006 What is an ontology? Distinction ontology/KB –different role played by represented knowledge ontologies - k. +/- consensual of a community »process, activity, resource kb - k. specific of a particular problem being solved, changes with inference »activities of a particular enterprise; actual processes, activities, costs, resources used to build or produce a particular product; estimate of resources inferred to be needed to satisfy an order

8. February 24, 2006 What is an ontology? Depend on the application that powered its construction –Same domain/ different tasks a large number of common concepts differently defined: –different levels of detail (class, relation, etc.) –capturing different points of view (structural point of view, functional point of view, etc.) –different levels of granularity There is no “The Ontology!” – genuine alternatives!! –Not to the philosophers

9. February 24, 2006 Kinds of ontologies representation or meta- –capture the representation primitives in a KR family or paradigm (Frames: class, instance, relation -slots and facet-, function, etc.) general or upper –capture very general notions applicable across domains (Time: time-point, time-range, duration, overlaps, before, after, etc.) domain –specific of a particular domain (Chemical elements: elements, non-reactive elements, helium, non-metals, carbon, etc.) others...

10. February 24, 2006 Kinds of ontologies D. McGuinness – Ontologies Come of Age

11. February 24, 2006 Origin An Ontology that describes the processes of the Central Dogma of Molecular Biology for prokaryotic organisms. Formalized and can be used by an inference engine to answer user questions

12. February 24, 2006 Origin: Processes

13. February 24, 2006 Origin Entities

14. February 24, 2006 Origin Relations (1)

15. February 24, 2006 Origin: Relations (2)

16. February 24, 2006 Origin: Roles

17. February 24, 2006 Origin: Transcription

18. February 24, 2006 Origin: Transcription, subactivities

19. February 24, 2006 Origin: Activities

20. February 24, 2006 How are they built? General Process Life cycle Sub-Processes: –from scratch –by means of reuse: integration merge

21. February 24, 2006 General process EspecificaçãoConceptualizaçãoFormalizaçãoImplementaçãoManutenção Aquisição de Conhecimento Avaliação Documentação

22. February 24, 2006 Life cycle Prototipização evolutiva A1 CascataIterativo A1A2 A3 Evolutivo A1A2A3

23. February 24, 2006 Methodologies to build from scratch There are a few methodologies to build ontologies from scratch None of existing methodologies from scratch is widely accepted It is still more of a craft than an engineering task

24. February 24, 2006 Methodologies to build from scratch Most representative methodologies are: –TOVE methodology [Gruninger, Fox 1995] –ENTERPRISE methodology [Uschold, King 1995] –METHONTOLOGY [Fernández, Gómez-Pérez, Sierra 1999]

25. February 24, 2006 TOVE TOVE activitycorresponds to Capture motivating scenarios and formulate informal competency questions Specify terminology, formulate formal competency questions and specify axioms and definitions in FOL Evaluate competency and completeness Specification Conceptualization, Formalization and Implementation Evaluation

26. February 24, 2006 ENTERPRISE ENTERPRISE activitycorresponds to Identify purpose and scope Capturing knowledge Knowledge Acquisition and Conceptualization Specification EvaluateEvaluation Coding Formalization and Implementation DocumentDocumentation

27. February 24, 2006 Techniques Knowledge acquisition: –brainstorming, interviews, questionnaires, text analysis, mind maps –experts, books, norms, etc. Conceptualization: –middle-out, grouping, glossary of terms, concept classification trees Formalization: –intermediate tabular representations (concept dictionary, table of binary relations, etc.)

28. February 24, 2006 Ontology evaluation One needs to guarantee quality –technical evaluation: judge ontologies, their software environment and documentation against a framework: consistency, completeness, conciseness, etc. –user assessment: judge from the user point of view the usability and usefulness of ontologies, their software environment and documentation when they are reused or shared in applications understandability, technically evaluated, portable, etc. [Gómez-Pérez, Juristo, Pazos 1995] [Gómez-Pérez 1999]

29. February 24, 2006 Ontology evaluation –ONTOCLEAN: analyze hierarchical taxonomy using philosophical principles. Aims: –assure that instances do not violate class properties –assure consistent hierarchical structure [Guarino, Welty, 2001, 2002]

30. February 24, 2006 Ontology building tools Most important tools freely available: –PROTÉGÉ, http://protégé.stanford.edu/ –Ontolingua Server, http://WWW-KSL-SVC.stanford.edu:5915 –OntoEdit, http://ontoprise.de/products/ontoedit/ –KAON, http://kaon.semanticweb.org/ [Duineveld, Stoter, Weiden, Kenepa, Benjamins 1999] Some provide help to identify similar concepts (merge): PROTÉGÉ (PROMPT, ex-SMART) Ontolingua Server (Chimaera)

31. February 24, 2006