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Consistency and Provenance in Rule Processing

  • Conference paper
Rule-Based Modeling and Computing on the Semantic Web (RuleML 2011)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7018))

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Abstract

Open collections of data and rules on the web are typically characterized by heterogeneous quality and imperfect consistency. In reasoning with data and rules on the web, it is important to know where an answer comes from (provenance) and whether the it is reasonable considering the inconsistencies (inconsistency-tolerance). In this paper, I draw attention to the idea that provenance and inconsistency-tolerance play mutually supporting roles under the theme of reasoning with imperfect information on the web. As a specific example, I make use of basic provenance information to avoid unreasonable answers in reasoning with rules and inconsistent data.

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Author information

Authors and Affiliations

  1. Computer Science Department, Stanford University, Stanford, CA, 94305, United States of America

    Eric Jui-Yi Kao

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  1. Eric Jui-Yi Kao
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Editors and Affiliations

  1. Frank Olken University, P.O. Box 527, 94701, Berkeley, CA, USA

    Frank Olken

  2. University of Bologna, CIRSFID, Via Galliera 3, 40128, Bologna, Italy

    Monica Palmirani

  3. DEIS, Università di Bologna, Italy

    Davide Sottara

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Kao, E.JY. (2011). Consistency and Provenance in Rule Processing. In: Olken, F., Palmirani, M., Sottara, D. (eds) Rule-Based Modeling and Computing on the Semantic Web. RuleML 2011. Lecture Notes in Computer Science, vol 7018. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24908-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-24908-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24907-5

  • Online ISBN: 978-3-642-24908-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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