Policy-based inconsistency management in relational databases

  • Authors:

  • Maria Vanina Martinez;Francesco Parisi;Andrea Pugliese;Gerardo I. Simari;V. S. Subrahmanian

  • Affiliations:

  • Department of Computer Science, Wolfson Building, Parks Road, Oxford OX1 3QD, United Kingdom;Universití della Calabria, Via Bucci, 87036 Rende CS, Italy;Universití della Calabria, Via Bucci, 87036 Rende CS, Italy;Department of Computer Science, Wolfson Building, Parks Road, Oxford OX1 3QD, United Kingdom;University of Maryland College Park, College Park, MD 20742, USA

  • Venue:
  • International Journal of Approximate Reasoning
  • Year:
  • 2014

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Abstract

Though inconsistency management in databases and AI has been studied extensively for years, it does not allow the user to specify how he wants to resolve inconsistencies. In real-world applications, users may want to manage or resolve inconsistencies based not only on the data, but their own knowledge of the risks involved in decision making based on faulty data. Each user should be empowered to use reasonable policies to deal with his data and his mission needs. In this paper, we start by providing an axiomatic definition of inconsistency management policies (IMPs) that puts this power in the hands of users. Any function satisfying these axioms is an IMP. We then define three broad families of IMPs, and derive several results that show (i) how these policies relate to postulates for the revision of belief bases and to recent research in the area of consistent query answering, and (ii) how they interact with standard relational algebra operators. Finally, we present several approaches to efficiently implement an IMP-based framework.