https://github.com/multi-dimensional-process-mining/eventgraph_tutorial
Process mining, so far, has required sophisticated, special-purpose software to handle, filter, analyze event logs, discover models, and analyze deviations. This sequence of tutorials shows how to use a general purpose graph database system (Neo4j) and graph query language Cypher for process mining. The tutorials shows how to use Neo4j and Cypher to
- load event data into Neo4j, specifically event data over multiple case/entity identifiers
- how to construct and extend event knowledge graphs from event data over multiple case/entity identifiers with simple Cypher queries
- how to analyze event knowledge graphs through querying and filtering
- how to discover basic process models through aggregation directly in event knowledge graphs
- how to detect task execution patterns and construct a multi-layered event knowledge graph for advanced analyses over multiple levels of abstraction
The ready-made query templates enable users to begin learning process mining over multiple entities and in multiple behavioral dimensions and to design their own analysis stacks with very low effort: by simply using off-the-shelf graph database systems and standard query languages.
How to install:
- Download and install Neo4j desktop https://neo4j.com/download/
- Download the latest release (.zip) of the tutorial, including query templates Python scripts, and example data from https://github.com/multi-dimensional-process-mining/eventgraph_tutorial/releases
- Unzip into a local directory (on a path without dash character ‘-‘)
- Open ./order_process/tutorial-your-first-event-knowledge-graph.md (or .pdf)
Example data sets:
- an example dataset (.csv) is provided together with the tutorial, available here: https://github.com/multi-dimensional-process-mining/eventgraph_tutorial/blob/main/order_process/input_logs/order_process_event_table_orderhandling.csv
- 5 real-life datasets (BPI Challenges) to be used with Neo4j are available at https://zenodo.org/record/4708117
Contact person providing support during the summer school: Dirk Fahland (d.fahland@tue.nl)
Providing support on the following days: Monday evening (4th July 2022) through Friday noon (8th July 2022)