Event Data and Queries for Multi-Dimensional Event Data in the Neo4j Graph Database

Zenodo (CERN European Organization for Nuclear Research)

Abstract

Datasets and scripts for modeling business process event log data in Neo4j Provides input data for 5 datasets (BPIC14, BPIC15, BPIC16, BPIC17, BPIC19) Provides Python scripts to prepare and import each dataset into a Neo4j database instance through Cypher queries, representing behavioral information not globally (as in an event log), but locally per entity and per relation between entities. Provides Python scripts to retrieve event data from a Neo4j database instance and render it using Graphviz dot. The data model and queries are described in detail in: Stefan Esser, Dirk Fahland: Multi-Dimensional Event Data in Graph Databases (2020) https://arxiv.org/abs/2005.14552 Fork the query code from Github: https://github.com/multi-dimensional-process-mining/graphdb-eventlogs

Authors 2

1. Stefan Esser Aachen INFORM GmbH

   Inform (Germany)

   Affiliation as printed

   INFORM GmbH, Aachen, Germany

2. Dirk Fahland