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QDEF and Its Approximations in OBDM

  • arXiv (Cornell University)
  • Cornell University
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Abstract

Given an input dataset (i.e., a set of tuples), query definability in Ontology-based Data Management (OBDM) amounts to find a query over the ontology whose certain answers coincide with the tuples in the given dataset. We refer to such a query as a characterization of the dataset with respect to the OBDM system. Our first contribution is to propose approximations of perfect characterizations in terms of recall (complete characterizations) and precision (sound characterizations). A second contribution is to present a thorough complexity analysis of three computational problems, namely verification (check whether a given query is a perfect, or an approximated characterization of a given dataset), existence (check whether a perfect, or a best approximated characterization of a given dataset exists), and computation (compute a perfect, or best approximated characterization of a given dataset).

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Publication details

DOI
10.48550/arxiv.2108.10021
OpenAlex
W3193882774
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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