📡 EEL: Events in Context Library

An event represents any occurrence of interest at a specific point in space and time. 📡 Events in Context Library is a community-driven knowledge base designed to explore event data within their historical, societal, and environmental contexts. Complemented by the literature review Neural Spatio-Temporal Point Processes, this project takes a practical, hands-on approach to analyzing and understanding spatio-temporal event patterns.

Content

  1. 🔴 Tutorials: Introductory material on spatio-temporal event modeling, covering neural point processes, intensity estimation, and simulation. Suitable for building practical foundations.
  2. 🟠 Websites: Links to external resources with datasets, code, and academic projects on event prediction and spatio-temporal modeling.
  3. 🟡 Tools: Software libraries, notebooks, and platforms for data preprocessing, model fitting, and visualization in spatio-temporal analysis.
  4. 🟢 Datasets: Curated datasets on crime, conflict, protests, and humanitarian events, with rich temporal and geographic detail for event prediction and public safety research.
  5. 🔵 Conferences and Journals: Key venues for publishing and tracking research in spatial statistics, GIS, and spatio-temporal modeling.
  6. 🟣 Notable Papers and Methods: Influential works on neural temporal point processes and spatio-temporal statistics, highlighting key models and empirical studies.

Mission and Scope

Our mission is to lower entrance barriers and improve the quality of benchmarks in event data analysis. We aim to create a comprehensive resource for researchers and practitioners to access tutorials, datasets, tools, and literature in the field.

📚 Join the Conversation

Visit the Space‑Time Causality Reading Group for regular paper discussions and community meet‑ups.

🤝 Contribute

This project is community-driven. Everyone is welcome to contribute by adding new items to the website. After submission, your contribution will be reviewed and added to the site. You can submit via:

  • A form
  • by creating a Pull Request where you create a new ‘.csv’ file within the data folder (this also allows adding more than one fiel at once). You can also use this option to propose changes in existing entries.

If you want to report, please raise an issue on GitHub.

Funding

This work was funded by the Bundesministerium für Bildung und Forschung (BMBF) under Grant 01IW23005 and is part of the eventful project.