Project data

Artificial or empirical, every dataset tells a story.

Project database

Learn how project data drives decisions and research

Over the years, the Operations Research & Scheduling (OR&S) group has created and collected extensive project data for both research and teaching purposes. The story behind the generation and use of these datasets is detailed in the book "A Quest for Projects with Scarce Resources: Seeking Schedule Intelligence Through Project Data Discovery". Below, you can find links to the relevant databases for exploration and experimentation.

Our database collection consists of both artificially generated project data and empirical project data. The artificial datasets have been created using network generators for academic research purposes, while the empirical datasets have been collected from real-world projects.

Part of our database collection is already accessible via GitHub. The remaining databases are currently being prepared for public release and will be made available soon.

Artificial projects

  • RCPLIB - The Resource-Constrained Project Scheduling Problem (RCPSP)

  • MSLIB - The Multi-Skilled Resource-Constrained Project Scheduling Problem (MSRCPSP)

  • The Resource-Constrained Project Scheduling Problem with Alternative Subgraphs (RCPSP-AS)

  • MMLIB - The Multi-Mode Resource-Constrained Project Scheduling Problem (MMRCPSP)

  • MPLIB - The Resource-Constrained Multi-Project Project Scheduling Problem (RCMPSP)

Empirical projects

  • DSLIB - The empirical database with real project data for scheduling, risk analysis and control

Note: For detailed information on these databases, please visit our university project data page.