Models and Query Languages for Temporal Property Graph Databases

Abstract

Although property graphs are increasingly being studied by the research community, most authors do not consider the evolution of such graphs over time. However, this is needed to capture a wide range of real-world situations, where changes normally occur. In this work, we propose a temporal model and a high level query language for property graphs and analyse the real-world cases where they can be useful, with focus on transportation networks (like road and river networks) equipped with sensors that measure different variables over time. Many kinds of interesting paths arise in this scenario. To efficiently compute these paths, also path indexing techniques must be studied.