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Foundational challenges in automated semantic Web data and ontology cleaning

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4 Author(s)
Alonso-Jimene, J.A. ; Comput. Sci. & Artificial Intelligence Dept., Univ. de Sevilla, Spain ; Borrego-Diaz, J. ; Chavez-Gonzalez, A.M. ; Martin-Mateos, F.J.

Nowadays, Web-based data management needs tools to ensure secure, trustworthy performance. The Utopian future shows a semantic Web providing dependable framework that can solve many of today's data problems. However, the realistic immediate future raises several challenges, including foundational semantic Web issues, the abstract definition of data, and incomplete, evolving ontologies. In either case, the marriage of data and ontologies is indissoluble and represents the knowledge database (KDB), a basic ingredient of the semantic Web. In this article, we look closely at problems in data analysis, the first phase of data cleaning. Applying automated reasoning systems to semantic Web data cleaning and to cleaning-agent design raises many challenges. We can build trust in semantic Web logic only if it's based on certified reasoning.

Published in:

Intelligent Systems, IEEE  (Volume:21 ,  Issue: 1 )