An analytics-aware conceptual model for evolving graphs

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, welldefined, 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.

Amine Ghrab, Sabri Skhiri, Salim Jouili, and Esteban Zimányi, An Analytics-Aware Conceptual Model For Evolving Graphs, proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery – DaWak 2013, Prague, Czech Republic, August 2013.

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A Conceptual Model For Evolving Graphs Analysis

Currently EURA NOVA is leading two PhD thesis in collaboration with the CODE/WIT Lab of the Université Libre de Bruxelles. Both thesis are supervised by Professor Esteban Zimànyi from ULB and Sabri Skhiri from EURA NOVA.

The goal of my thesis is to build a multidimensional analysis framework on top of NoSQL data, and most importantly Graphs. Recently our paper entitled: An Analytics-Aware Conceptual Model For Evolving Graphs was accepted for presentation on the 15th International Conference on Data Warehousing and Knowledge Discovery – DaWaK 2013. The conference will be held in Prague, Czech Republic from 26 to 29 August 2013. DaWaK is a reference conference on data warehousing bringing together researcher working on BI related topics.

In this post, I’ll give an overview of the research and contributions of this paper.

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