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Ontology & Semantic Web – A Dummys Overview of Modern Technologies for Sharing Knowledge Mitsunori Ogihara Center for Computational Science.

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Presentation on theme: "Ontology & Semantic Web – A Dummys Overview of Modern Technologies for Sharing Knowledge Mitsunori Ogihara Center for Computational Science."— Presentation transcript:

1 Ontology & Semantic Web – A Dummys 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 conceptualizatio n 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 Solovitz93] 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 cant 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 – – OWL DL (Description Logic, standard version) – OWL Lite (restricted version) … basic constructs exist to logically express constructs of DL – OWL Full (for RDF) – 2003/Tutorial/examples.pdf 2003/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


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