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"A generic modelling to capture the temporal evolution in graphs", IRIT

on the October 20, 2020

 A temporal graph is based on two aspects: it is a graph that models the interconnection of data and that includes time dimension to model the temporal evolution of data. Temporal graphs are commonly used in different domains to capture the different evolution types that occur in a graph over time.

However, existing modelling solutions of temporal graph do not allow to manage all temporal evolution types in the real world. In this paper, we propose a generic model that is able to manage the temporal evolution at different levels: at the schema level to capture the temporal evolution in the graph data structure, and at the instance level to capture the temporal evolution of data contained in entities and their relationships as well as the temporal evolution of the graph topology.

We complete our proposed modelling solution with a set of translation rules compatible with the property graph model. The feasibility of our proposal is illustrated through an implementation of our model in the Neo4j system.
Updated on October 16, 2020