Ontology & Semantic Web – A Dummy’s Overview of Modern Technologies for Sharing Knowledge

1. Ontology & Semantic Web – A Dummy’s Overview of Modern Technologies for Sharing Knowledge Mitsunori Ogihara Center for Computational Science

2. What Is an Ontology? • Merriam-Webster: “The branch of metaphysics dealing with the nature of being” • What does it mean to exist? • What exists? • In the field of computer science an ontology is “a specification of a conceptualization” – Tom Gruber

3. World, Specification, Conceptualization • Human observes the world and conceptualizes it • That human conceptualization is put into a specification • The world matches the specification

4. What an Ontology Can Conceptualize • Things to exist • Individuals, not necessarily physical existence • Classes of individuals • Relations among things • Is a part of • Is not equal to • Properties about things • Has a value of

5. Problem • Conceptualization is ambiguous and inaccurate • How a person A sees the world is not necessarily equal to how a person B sees the world • Specification is difficult • Formal specification is tiresome • How efficiently can one develop an ontology? • How efficiently can one compare ontologies?

6. Why Was the Idea of Ontology Created? • Artificial Intelligence … a branch of computer science that studies computational methods of mimicking human intelligence • Intelligence includes ability to • Understand data obtained through senses • Acquire knowledge • Apply knowledge to solve problems • Understand emotion

7. Knowledge Representation • An area that studies how to formally think • [Davis, Shrobe, and Solovitz’93] Knowledge Representation is • A surrogate • A set of ontological commitments • A fragmentary theory of intelligent reasoning • A medium for efficient computation • A medium of human expression • Commitments are filters through which the world is observed

8. Semantic Web • The first generation of Web is HTML (Hypertext Markup Language) • This is designed so as to present texts in a format specification that can be easily understood and rendered • Search engines can find documents that may contain certain information by using keyword matches, but can’t find an answer to a question

9. Semantic Web • A new generation of web should provide not texts but structured information, a part of which may be texts • Resource Description Framework (where the resources are) • XML (Extensive Markup Language) • A user-definable format • Documents conforming to the format • Idea: • Decide on what information can a web page might contain • Decide on how to describe such information • Annotate the web page with such information in a predetermined format

10. Ontology Development Tools • OWL (Web Ontology Language) • Currently the most popular ontology description language • http://www.w3.org/TR/owl-features/ • OWL DL (Description Logic, standard version) • OWL Lite (restricted version) … basic constructs exist to logically express constructs of DL • OWL Full (for RDF) • http://www.cs.manchester.ac.uk/~horrocks/ISWC2003/Tutorial/examples.pdf

11. A History of Ontology Description Languages • KIF (1992) … Stanford, first-order logic • Loom (1992) … USC, first-order logic, for KR nor necessarily for ontologies • FLogic (1995) … Karlsruhe, combination of first-order logic and frames • OKBC (1997) … DARPA • XOL (1999) … SRI, an XML version of OKBC • OWL (2001) … W3C

12. Ontology Development Tools • Created along with development of description languages

15. Popular Free Tools • Protégé-2000 • Swoop … an open source project, hosted at Google

16. Ontology Building Process • Vocabulary • Need to settle on a set of words to be used to describe the domain knowledge (or the domain of the web contents) • Where to start? Thousands of words? • Knowledge Base Building • Express domain experts’ knowledge in terms of ontology • Who will translate knowledge into logical forms? Ambiguity issues? • Inference • Make new discovery • Identify classes and properties of an individual • Inference engines, compute-intensive

17. Exporting Ontologies • Protégé and Swoop (and others) have the ability to export/import data in various formats • Enables information exchange between ontologies

18. Finding a Nice Mapping • A mapping f of an ontology O to an ontology O’ is one that maps each class of O to a class of O’ and each property of O to another property of O’. We want: • For all classes c and d of O, c is a subclass of d if and only if f(c) is a subclass of f(d) in O’ • For all class c and property p of O, c has property p if and only if f(c) has property f(p) in O’ • Finding a perfect mapping is hard, and practically such a perfect mapping rarely exists • Finding a mapping that maximizes a certain quantity is also difficult, and is NP-hard • Heuristic methods are usually used (based on graph properties)

19. References • T.R.Gruber (1993), A Translation Approach to Portable Ontology Specifications, Knowledge Acquisition • V.Devedzik(2002), Understanding ontological engineering, Communications of the ACM • J.Gennari, M.Musen, R.Fergerson (2003), The evolution of Protégé: an environment for knowledge-based systems development, International Journal of Human-Computer Studies • A.Kalyanpur, B.Parsia, E.Sirin, B.Grau (2006), Swoop: A web ontology editing browser, Web Semantics: Science • O.Corcho et al. (2003), Methodologies, tools and languages for building ontologies. Where is their meeting point? Data&Knowledge Engineering • L.Lacy (2005), OWL: Representing information using the web ontology language • J.Euzenat, P. Shvaiko (2007), Ontology Matching, Springer