ESA Anomaly Dataset
<p>ESA Anomaly Dataset is the first large-scale, real-life satellite telemetry dataset with curated anomaly annotations originated from three ESA missions. We hope that this unique dataset will allow researchers and scientists from academia, research institutes, national and international space agencies, and industry to benchmark models and approaches on a common baseline as well as research and develop novel, computational-efficient approaches for anomaly detection in satellite telemetry data.</p> <p>The dataset results from the work of an 18-month project carried by an industry Consortium composed of Airbus Defence and Space, KP Labs and the European Space Agency’s European Space Operations Centre. The project, funded by the European Space Agency (ESA), is part of the Artificial Intelligence for Automation (A²I) Roadmap (De Canio et al., 2023), a large endeavour started in 2021 to automate space operations by leveraging artificial intelligence.</p> <p>Further details can be found on the <a href="https://arxiv.org/abs/2406.17826">arXiv</a> and <a href="https://github.com/kplabs-pl/ESA-ADB">Github</a>.</p> <p><em>References</em><br>De Canio, G. et al. (2023) Development of an actionable AI roadmap for automating mission operations. In, 2023 SpaceOps Conference. American Institute of Aeronautics and Astronautics, Dubai, United Arab Emirates.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 12
- Harmonization
- 4
- Access
- 8
- Reuse readiness
- 8
- Engagement
- 0