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An Analytics-Aware Conceptual Model for Evolving Graphs

Published: 26 August 2013 Publication History

Abstract

Graphs are ubiquitous data structures commonly used to represent highly connected data. Many real-world applications, such as social and biological networks, are modeled as graphs. To answer the surge for graph data management, many graph database solutions were developed. These databases are commonly classified as NoSQL graph databases, and they provide better support for graph data management than their relational counterparts. However, each of these databases implement their own operational graph data model, which differ among the products. Further, there is no commonly agreed conceptual model for graph databases.
In this paper, we introduce a novel conceptual model for graph databases. The aim of our model is to provide analysts with a set of simple, well-defined, and adaptable conceptual components to perform rich analysis tasks. These components take into account the evolving aspect of the graph. Our model is analytics-oriented, flexible and incremental, enabling analysis over evolving graph data. The proposed model provides a typing mechanism for the underlying graph, and formally defines the minimal set of data structures and operators needed to analyze the graph.

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cover image Guide Proceedings
DaWaK 2013: Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery - Volume 8057
August 2013
371 pages
ISBN:9783642401305

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 26 August 2013

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