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Queries for modeling, importing, and analyzing multi-dimensional event data using the Labeled Property Graph data model of Graph Databases such as Neo4J.

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Using Graph Databases for Event Data

Description

This repository collects queries for modeling, importing, and analyzing event data as Knowledge Graphs using the Labeled Property Graph data model of graph databases. All scripts and queries are licensed under LGPL v3.0, see LICENSE. Copyright information is provided within each Project.

Projects

The following projects are part of this repository

csv_to_eventgraph_neo4j

Data model and generic query templates for translating and integrating a set of related CSV event logs into single event graph over multiple behavioral dimensions, stored as labeled property graph in Neo4J. See csv_to_eventgraph_neo4j/README.txt

Publications:

exploration_bpic2017

Implementation of an explorative case study to model the BPI Challenge 2017 data sets using Neo4J. Publications:

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Queries for modeling, importing, and analyzing multi-dimensional event data using the Labeled Property Graph data model of Graph Databases such as Neo4J.

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  • Python 100.0%