Measurement of Performances Indicators (PIs) in highly distributed environments, especially in networked organisations, is particularly critical because of heterogeneity issues and sparsity of data. In this paper we present a semantics-based approach for dynamic calculation of PIs in the context of sparse distributed data marts. In particular, we propose to enrich the multidimensional model with the formal description of the structure of an indicator given in terms of its algebraic formula and aggregation function. Upon such a model, a set of reasoning-based functionalities are capable to mathematically manipulate formulas for dynamic aggregation of data and computation of indicators on-the-fly, by means of recursive application of rewriting rules based on logic programming.

Semantics-Based Multidimensional Query Over Sparse Data Marts / Diamantini, Claudia; Potena, Domenico; Storti, Emanuele. - STAMPA. - 9263:(2015), pp. 190-202. [10.1007/978-3-319-22729-0_15]

Semantics-Based Multidimensional Query Over Sparse Data Marts

DIAMANTINI, Claudia;POTENA, Domenico;STORTI, EMANUELE
2015-01-01

Abstract

Measurement of Performances Indicators (PIs) in highly distributed environments, especially in networked organisations, is particularly critical because of heterogeneity issues and sparsity of data. In this paper we present a semantics-based approach for dynamic calculation of PIs in the context of sparse distributed data marts. In particular, we propose to enrich the multidimensional model with the formal description of the structure of an indicator given in terms of its algebraic formula and aggregation function. Upon such a model, a set of reasoning-based functionalities are capable to mathematically manipulate formulas for dynamic aggregation of data and computation of indicators on-the-fly, by means of recursive application of rewriting rules based on logic programming.
2015
Big Data Analytics and Knowledge Discovery
978-3-319-22728-3
978-3-319-22729-0
978-3-319-22728-3
978-3-319-22729-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/227593
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