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Meta-knowledge in systems design: panacea … or undelivered promise?

Published online by Cambridge University Press:  04 June 2001

YANNIS KALFOGLOU ,
TIM MENZIES ,
KLAUS-DIETER ALTHOFF  and
ENRICO MOTTA
YANNIS KALFOGLOU
Affiliation:
School of Artificial Intelligence, 80 South Bridge, University of Edinburgh, Edinburgh EH1 1HN, Scotland – now associated with: Knowledge Media Institute (KMi), The Open University, Walton Hall, Milton Keynes MK7 6AA, England. yannisk@dai.ed.ac.uk.
TIM MENZIES
Affiliation:
NASA/WVU Software Research Lab, 100 University Drive, Fairmont, WV, USA – now associated with: Department of Electrical and Computer Engineering, 2356 Main Mall, Vancouver V6T1Z4 BC, Canada. tim@menzies.com.
KLAUS-DIETER ALTHOFF
Affiliation:
Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany. klaus-dieter.althoff@iese.fhg.de.
ENRICO MOTTA
Affiliation:
Knowledge Media Institute (KMi), The Open University, Walton Hall, Milton Keynes MK7 6AA, England. e.motta@open.ac.uk.
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Abstract

In this study we present a review of the emerging field of meta-knowledge components as practised over the past decade among a variety of practitioners. We use the artificially defined term “meta-knowledge” to encompass all those different but overlapping notions used by the artificial intelligence and software engineering communities to represent reusable modelling frameworks: ontologies, problem-solving methods, patterns and experience factories and bases, to name but a few. We then elaborate on how meta-knowledge is deployed in the context of system's design to improve its reliability by consistency-checking, enhance its reuse potential and manage its knowledge-sharing. We speculate on its usefulness and explore technologies for supporting deployment of meta-knowledge. We argue that, despite the different approaches being followed in systems design by divergent communities, meta-knowledge is present in all cases, in a tacit or explicit form, and its utilisation depends on pragmatic aspects which we try to identify and critically review on criteria of effectiveness.

Keywords

OntologiesProblem-Solving MethodsExperiencewarePatternsDesign TypesCost-Effective Analysis
Type
Review Article
Information
The Knowledge Engineering Review , Volume 15 , Issue 4 , December 2000 , pp. 381 - 404
Copyright
© 2000 Cambridge University Press

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Footnotes

The idea for this study emerged from a panel debate among the authors that took place in the SEKE'99 conference (Menzies, 1999a). Thanks to Daniela Carbogim, Virginia Brilhante and David Robertson for their comments on an early draft. The research described in this paper is supported by a European Union Marie Curie Fellowship (programme: Training and Mobility of Researchers) for the first author and partially supported by NASA through cooperative agreement NCC 2–979 for the second author.