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Information Systems Frontiers

Erschienen in:

20.03.2020

TopoGraph: an End-To-End Framework to Build and Analyze Graph Cubes

verfasst von: Amine Ghrab, Oscar Romero, Sabri Skhiri, Esteban Zimányi

Erschienen in: Information Systems Frontiers | Ausgabe 1/2021

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Abstract

Graphs are a fundamental structure that provides an intuitive abstraction for modeling and analyzing complex and highly interconnected data. Given the potential complexity of such data, some approaches proposed extending decision-support systems with multidimensional analysis capabilities over graphs. In this paper, we introduce TopoGraph, an end-to-end framwork for building and analyzing graph cubes. TopoGraph extends the existing graph cube models by defining new types of dimensions and measures and organizing them within a multidimensional space that guarantees multidimensional integrity constraints. This results in defining three new types of graph cubes: property graph cubes, topological graph cubes, and graph-structured cubes. Afterwards, we define the algebraic OLAP operations for such novel cubes. We implement and experimentally validate TopoGraph with different types of real-world datasets.

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Titel: TopoGraph: an End-To-End Framework to Build and Analyze Graph Cubes
verfasst von: Amine Ghrab
Oscar Romero
Sabri Skhiri
Esteban Zimányi
Publikationsdatum: 20.03.2020
Verlag: Springer US
Erschienen in: Information Systems Frontiers / Ausgabe 1/2021
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI: https://doi.org/10.1007/s10796-020-10000-z

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