Temporal Property Graphs as Organizing Principles


Temporal Property Graphs as Organizing Principles

Principal Investigator

Institut für Angewandte Informatik (InfAI) e.V. at the University of Leipzig

Oracle Fellowship Recipient

Christopher Rost, Lucas Schons, Philip Fritzsche

Oracle Principal Investigator

Dieter Gawlick
Kam Shergill
Matthias Brantner, Senior Director
Paul Sonderegger
Souripriya Das
Zhen Hua Liu


This research project includes the development of a native property graph store with bi-temporal time management and querying via a graph query language like PGQL. For example, such a system can be used to organize multi-dimensional time-series of correlating sensor data as a graph structure. This task is followed by a prototypical implementation as a proof of concept and for experimental evaluation. One main focus is the retrieval of provenance information using features like snapshot retrieval and temporal predicate support. The existing graph query language should be extended by temporal features to define temporal graph patterns, e.g. to find subgraphs that happened in the past or within a period of time. Not only the analysis of the graph history is in the foreground, but rather a query that considers the continuous changes of the graph. Another task is the support of an efficient snapshot retrieval functionality to extract the state of the graph at a specific point in the past. In a continuing task, the store will be extended with a connector for the input of multi-dimensional event streams e.g. from IoT sensor data and ML systems.