Literature DB >> 14992506

Defaults, context, and knowledge: alternatives for OWL-indexed knowledge bases.

A Rector1.   

Abstract

The new Web Ontology Language (OWL) and its Description Logic compatible sublanguage (OWL-DL) explicitly exclude defaults and exceptions, as do all logic based formalisms for ontologies. However, many biomedical applications appear to require default reasoning, at least if they are to be engineered in a maintainable way. Default reasoning has always been one of the great strengths of Frame systems such as Protégé. Resolving this conflict requires analysis of the different uses for defaults and exceptions. In some cases, alternatives can be provided within the OWL framework; in others, it appears that hybrid reasoning about a knowledge base of contingent facts built around the core ontology is necessary. Trade-offs include both human factors and the scaling of computational performance. The analysis presented here is based on the OpenGALEN experience with large scale ontologies using a formalism, GRAIL, which explicitly incorporates constructs for hybrid reasoning, numerous experiments with OWL, and initial work on combining OWL and Protégé.

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Year:  2004        PMID: 14992506     DOI: 10.1142/9789812704856_0022

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  5 in total

1.  Strengths and limitations of formal ontologies in the biomedical domain.

Authors:  Stefan Schulz; Holger Stenzhorn; Martin Boeker; Barry Smith
Journal:  Rev Electron Comun Inf Inov Saude       Date:  2009-03-01

2.  Investigating subsumption in SNOMED CT: an exploration into large description logic-based biomedical terminologies.

Authors:  Olivier Bodenreider; Barry Smith; Anand Kumar; Anita Burgun
Journal:  Artif Intell Med       Date:  2007-01-22       Impact factor: 5.326

3.  Interoperability between phenotype and anatomy ontologies.

Authors:  Robert Hoehndorf; Anika Oellrich; Dietrich Rebholz-Schuhmann
Journal:  Bioinformatics       Date:  2010-10-22       Impact factor: 6.937

4.  Logical development of the cell ontology.

Authors:  Terrence F Meehan; Anna Maria Masci; Amina Abdulla; Lindsay G Cowell; Judith A Blake; Christopher J Mungall; Alexander D Diehl
Journal:  BMC Bioinformatics       Date:  2011-01-05       Impact factor: 3.169

5.  Terminologies for text-mining; an experiment in the lipoprotein metabolism domain.

Authors:  Dimitra Alexopoulou; Thomas Wächter; Laura Pickersgill; Cecilia Eyre; Michael Schroeder
Journal:  BMC Bioinformatics       Date:  2008-04-25       Impact factor: 3.169

  5 in total

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