Abstract
Some data models use so-called maybe tuples to express the uncertainty, whether or not a tuple belongs to a relation. In order to assess this relation’s quality the corresponding vagueness needs to be taken into account. Current metrics of quality dimensions are not designed to deal with this uncertainty and therefore need to be adapted. One major quality dimension is data completeness. In general, there are two basic ways to distinguish maybe tuples from definite tuples. First, an attribute serving as a maybe indicator (values YES or NO) can be used. Second, tuple probabilities can be specified. In this paper, the notion of data completeness is redefined w.r.t. both concepts. Thus, a more precise estimating of data quality in databases with maybe tuples (e.g. probabilistic databases) is enabled.
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Panse, F., Ritter, N. (2009). Completeness in Databases with Maybe-Tuples. In: Heuser, C.A., Pernul, G. (eds) Advances in Conceptual Modeling - Challenging Perspectives. ER 2009. Lecture Notes in Computer Science, vol 5833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04947-7_25
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DOI: https://doi.org/10.1007/978-3-642-04947-7_25
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