1.  2003 Rosina Weber Ontologies

2.  2003 Rosina Weber What are ontologies? originally, the filed dedicated to study the nature of everything sometimes referred to simply as knowledge bases aim to provide a common language to support knowledge sharing systems that implements tasks that use knowledge (and thus somehow perform knowledge sharing) should all guarantee a common language

3.  2003 Rosina Weber WHAT IS AN ONTOLOGY? From K. McCain presentation March, 2002

4.  2003 Rosina Weber Ontologies in AI Artificial intelligence researchers have adopted ontologies as a comprehensive knowledge representation formalism to provide commonsense reasoning in support of knowledge tasks such as knowledge acquisition and reuse. Lenat DB (1976) AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search. PhD thesis, Stanford University

5.  2003 Rosina Weber What are ontologies (in AI)? “Ontologies are explicit specifications of conceptualizations.” most cited definition from Gruber (1993)

6.  2003 Rosina Weber What are ontologies (in AI)? Ontologies are explicit descriptions of shared conceptualization: 1.explicit 2.descriptions 3.shared 4.conceptualization

7.  2003 Rosina Weber 1. explicit Has to be explicitly defined through descriptions types and constraints are explicitly defined

8.  2003 Rosina Weber 2. descriptions concepts (or classes) in a domain properties of each concept describing various features and attributes and restrictions on the attributes (facets)

9.  2003 Rosina Weber 3. shared Common to members of a domain/field Consensual knowledge –not private to one individual, accepted by a group

10.  2003 Rosina Weber 4. conceptualization – Interpreted concepts –conceptual (abstract) model of a domain through its relevant concepts

11.  2003 Rosina Weber Types of Information  concepts, atomic types  cardinality of constraints  is-a hierarchy among concepts  relationships between concepts  taxonomies of relations  reified statements  axioms  semantic entailments

12.  2003 Rosina Weber Universal Semantic Relationships  STRICT INCLUSION – X is a kind of Y  SPATIAL – X is a place in Y; X is a part of Y  CAUSE-EFFECT – X is a result of Y; X is a cause of Y  RATIONALE – X is a reason for doing Y  LOCATION FOR ACTION – X is a place for doing Y  FUNCTION – X is used for Y  MEANS-END – X is a way to do Y  SEQUENCE – X is a step (stage) in Y  ATRTRIBUTION – X is an attribute (characteristic) of Y From Spradling, The Ethnographic Interview From K. McCain presentation March, 2002

13.  2003 Rosina Weber Types of Ontologies Domain –Additional specializations are possible applications, tasks Linguistic –Account for grammar and meanings in a natural language e.g., WordNet for American English

14.  2003 Rosina Weber Uses of domain ontologies interoperability among information systems semantic web: link, coordinate software agents sharing knowledge bases among KBS intelligent retrieval, search

15.  2003 Rosina Weber Why ontologies for KBS? identify specific classes of objects and relations that exist in some specific domain need to understand and share common concepts of a domain by different systems multiple systems can use one same ontology and exchange knowledge and information without conflict ontological analysis captures the intrinsic conceptual structure of a domain and is the essential step in building coherent knowledge bases represent facts (propositions) in a domain by combining terms and concepts represent attitudes, e.g., hypothesize, believe, expect, hope, desire, fear, predicts, plans

16.  2003 Rosina Weber Ontologies vs. knowledge bases An ontology together with a set of individual instances of classes constitutes a knowledge base ontology is a basic structure around which a KB can be built knowledge bases represents what is true about a domain by using terms and concepts defined in the ontologies building an ontology implies that the representation language and the ontological analysis can be reused

17.  2003 Rosina Weber Ontologies supporting NLU natural language understanding –Syntactic Analysis (Parsing) –Semantic Analysis –Pragmatic Analysis natural language interfaces information systems, Artificial Intelligence systems search engines machine translation developing an ontology with ML from a collection of documents and the end-user to support domain-independent information extraction (IJCAI 01)

18.  2003 Rosina Weber ES methodology knowledge base (e.g.,frames and methods) knowledge base (e.g.,frames and methods) explanation general knowledge user I n t e r f a c e user I n t e r f a c e expert problem expert solution inference engine (agenda) inference engine (agenda) working memory ( short-term mem/information ) working memory ( short-term mem/information ) Knowledge acquisition

19.  2003 Rosina Weber ES supported by ontologies knowledge base (e.g.,frames and methods) knowledge base (e.g.,frames and methods) explanation expert problem expert solution inference engine working memory user I n t e r f a c e user I n t e r f a c e domain specific application specifictop level natural language Knowledge acquisition

20.  2003 Rosina Weber Ontologies supporting ES domain specific application specific top level natural language expert problem expert solution reasoning

21.  2003 Rosina Weber ontologies supporting CBR domain specific application specific top level natural language

22.  2003 Rosina Weber Development steps Determine the domain and scope Consider reusing existing ontologies Enumerate important terms in the ontology Define the classes and the class hierarchy Define the attributes of classes (slots) Define the facets of the slots Create instances from Noy & McGuinness

23.  2003 Rosina Weber Ontologies development process ontology development is an iterative process determine scope consider reuse enumerate terms define classes consider reuse enumerate terms define classes define properties create instances define classes define properties define constraints create instances define classes consider reuse define properties define constraints create instances from Noy & McGuinness

24.  2003 Rosina Weber Some challenges hugeness –amount of knowledge is overwhelming interaction –nature of problem to be solved –type of inference strategy to use multiple views –difficult consensus dynamic world –reorganization, maintenance context (not represented) all impact on construction, reusability, interfacing

25.  2003 Rosina Weber Ontology editors (development environments) ONTOLINGUA http://ontolingua.nici.kun.nl WEBONTO* http://kmi.open.ac.uk/projects/webonto/ PROTEGEWIN http://smi-web.stanford.edu/projects/prot-nt/ ONTOSAURUS* http://www.isi.edu/isd/ontosaurus.html ODE KADS22 Duineveld, A.J., Stoter, R., Weiden, M.R., Kenepa, B. and Benjamins, V.R. (2000). WonderTools? A comparative study of ontological engineering tools. International Journal of Human-Computer Studies 52(6): 1111-1133.

26.  2003 Rosina Weber Duineveld et al.,2000

27.  2003 Rosina Weber Looking at some ontologies Open University http://kmi.open.ac.uk/projects/webonto/ http://www.isi.edu/isd/ontosaurus.html USC/Information Sciences Institute

28.  2003 Rosina Weber These slides were built mainly based on: Noy, Natalya F. and McGuinness, Deborah L.. Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001. Online:http://protege.stanford.edu/publications/ ontology_development/ontology101.html B. Chandrasekaran, John R. Josephson, and V. Richard Benjamins What Are Ontologies, and Why Do We Need Them? Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999 Tautz, C. empolis

29.  2003 Rosina Weber Further Reading van Heijst, G. (1995) The Role of Ontologies in Knowledge Engineering, PhD thesis, University of Amsterdam.

30.  2003 Rosina Weber Bibliography (i) 1 Introductory Chandrasekaran, B.; Josephson, John R. and Benjamins, V. Richard. What Are Ontologies, and Why Do We Need Them? Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999. Gruninger, M. and Lee, Jintae. Ontology Applications and Design. Guest Editors. Communications of the ACM, Vol. 45, No. 2 February, 2002. Guarino, N. and Poli, R. The role of ontology in the information technology. Int’l J. Human-Computer Studies, Vol. 43, Nos. 5/6, Nov- Dec. 1995, pp. 623-965. Heijst, G. van Schreiber, A. Th. and Wielinga, B. J. Using explicit ontologies for KBS development. International Journal of Human- Computer Studies, 46(2/3):183-292, 1997. Swartout, William and Tate, Austin Guest Editors' Introduction: Ontologies Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

31.  2003 Rosina Weber Bibliography (ii) Gruber, T. A translational approach to portable ontologies. Knowledge acquisition, vol. 5, no.2, 1993, pp. 199-220. Tautz, C. Tutorial on Practical Ontology Construction.,Bertelsmann Mohn Media Group, empolis, Germany (unpublished slides). 2 Applications Andre Valente, Thomas Russ, Robert MacGregor, and William Swartout Building and (Re)Using an Ontology of Air Campaign Planning Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999 Mariano Fernández López, Asunción Gómez-Pérez, Juan Pazos Sierra, and Alejandro Pazos Sierra Building a Chemical Ontology Using Methontology and the Ontology Design Environment Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999 Gleb Frank, Adam Farquhar, and Richard Fikes Building a Large Knowledge Base from a Structured Source Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999

32.  2003 Rosina Weber 2.1 Ontologies and Knowledge Management V.R. Benjamins, D. Fensel, A. Gómez Pérez link Knowledge Management through Ontologies Ulrich Reimer (ed.) PAKM 98 Practical Aspects of Knowledge Management. Proceedings of the Second International Conference Basel, Switzerland, October 29-30, 1998. Motta,Enrico; Shum, Simon Buckingham and Domingue, John. Ontology-Driven Document Enrichment: Principles, Tools and Applications. International Journal of Human-Computer Studies, 52, (6), 1071-1109. O’Leary, D. E. (1998). Using AI in Knowledge Management: Knowledge Bases and Ontologies. Intelligent Systems, 13, 3, pp. 34-39. 2.1.1 Web portals Staab, S.; Jürgen, A.; Decker, S.; Erdmann, E.; Hotho, A.; Maedche, A.; Schnurr, H.P.; Studer, R.; Sure, Y. (2000). AI for the Web - Ontology-based Community Web Portals. Proceedings of the 17th National Conference on Artificial Intelligence and 12th Innovative Applications of Artificial Intelligence Conference, AAAI 2000/IAAI 2000, Menlo Park/CA, Cambridge/MA, AAAI Press/MIT Press. Bibliography (iii)

33.  2003 Rosina Weber 3. Design and development of ontologies Benjamin, J., Borst, P., Akkermans, J., & Wielinga, B. (1996). Ontology construction for technical domains. In Shadbolt, N., editor, Proceedings 9th European Knowledge Acquisition Workshop EKAW'96, pages 98-114, Berlin. Springer-Verlag. Lecture Notes in Artificial Intelligence No. 1076. Borst,P.,Akkermans,H. and Top,J., Engineering Ontologies, International Journal of Human-Computer Studies, 46:365-406, 1997 Gómez-Pérez, A.; Fernandez, M.; De Vicente, A. Towards a Method to Conceptualize Domain Ontologies. Workshop on Ontological Engineering. ECAI'96. 1996. Pags. 41-51. Gruber, T. (1995). Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, 43:907-928. Bibliography (iv)

34.  2003 Rosina Weber Noy, Natalya F. and McGuinness, Deborah L.. Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001. Online:http://protege.stanford.edu/publications/ ontology_development/ontology101.html 3.1 Ontology editors Duineveld, A.J., Stoter, R., Weiden, M.R., Kenepa, B. and Benjamins, V.R. (2000). WonderTools? A comparative study of ontological engineering tools. International Journal of Human-Computer Studies 52(6): 1111-1133. Farquhar,A. Fikes,R. and Rice, J. The Ontolingua Server: a Tool for Collaborative Ontology Construction; Intl. Journal of Human- Computer Studies 46, 1997. Bibliography (v)

35.  2003 Rosina Weber 4 Learning and acquisition of ontologies Frank,Gleb; Farquhar, Adam and Fikes, Richard Building a Large Knowledge Base from a Structured Source Intelligent Systems & their applications Vol. 14, No. 1, January/February 1999 5 Ontologies and knowledge-based systems van Heijst, G. (1995). The Role of Ontologies in Knowledge Engineering. PhD thesis, University of Amsterdam. 5.1.1 Ontologies and CBR systems Díaz-Agudo, B. & González-Calero, P.A. (2000). An architecture for knowledge intensive CBR systems. Proceedings of the Fifth European Workshop on Case-Based Reasoning (pp. 37-48). Munich: Springer. Bibliography (vi)