Abstract
Traditional data repositories are typically focused on the storage and querying of crisp-precise domains of data. As a result, current commercial data repositories have no facilities for either storing or querying imprecise-approximate data. However, when considering scientific data (i.e. medical data, sensor data etc) value uncertainty is inherited to scientific measurements. In this paper we revise the context of “value uncertainty”, and examine common models related to value uncertainty as part of the OLAP model. We present our approach for extending the OLAP model to include treatment of value uncertainty as part of a multidimensional model inhabited by flexible date and non-rigid hierarchical structures of organisation.
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Rogova, E., Chountas, P. (2007). On Imprecision Intuitionistic Fuzzy Sets & OLAP – The Case for KNOLAP. In: Castillo, O., Melin, P., Ross, O.M., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72434-6_2
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DOI: https://doi.org/10.1007/978-3-540-72434-6_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72433-9
Online ISBN: 978-3-540-72434-6
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