DBAIMar 10, 2017

The Ontological Multidimensional Data Model

arXiv:1703.03524v24 citations
Originality Synthesis-oriented
AI Analysis

This work addresses data modeling challenges in multidimensional systems, but it appears incremental as it builds on existing relational reconstructions.

The paper introduces the Ontological Multidimensional Data Model, which extends a relational reconstruction of a multidimensional data model using Datalog+- constructs like tuple-generating dependencies, equality-generating dependencies, and negative constraints, and briefly notes its good computational properties.

In this extended abstract we describe, mainly by examples, the main elements of the Ontological Multidimensional Data Model, which considerably extends a relational reconstruction of the multidimensional data model proposed by Hurtado and Mendelzon by means of tuple-generating dependencies, equality-generating dependencies, and negative constraints as found in Datalog+-. We briefly mention some good computational properties of the model.

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