Towards a Temporal Graph Query Language for Durable Patterns

Dynamic graphs are often the initial data for scientific analyses. However, existing methods designed for static graphs struggle with efficiency and accuracy when applied dynamically. One challenge occurs when local interactions in dynamic graphs influence global phenomena. Practitioners then follow the evolution of relationships between individual elements in local structures. Such structures are called Durable Graph Patterns or evolving subgraphs. This work introduces the Durable Graph Pattern Query Language (DPQGL), which allows for user-friendly querying of durable graph patterns on dynamic graphs. DPGQL is, by design, agnostic to the underlying durable pattern-matching algorithm. We base our proposed language on the widely used Cypher Query Language. In our experiments with seven pattern shapes in 24 variations on real-world materials science data, we explore the impact on query runtimes from query complexity and the frequency of graph changes.