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    ESA Anomaly Dataset

    • explore.openaire.eu
    • zenodo.org
    Updated Jun 25, 2024
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    Gabriele De Canio; Krzysztof Kotowski; Christoph Haskamp (2024). ESA Anomaly Dataset [Dataset]. http://doi.org/10.5281/zenodo.12528695
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    Dataset updated
    Jun 25, 2024
    Authors
    Gabriele De Canio; Krzysztof Kotowski; Christoph Haskamp
    Description

    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. 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. Further details can be found on the arXiv and Github. ReferencesDe 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.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Gabriele De Canio; Krzysztof Kotowski; Christoph Haskamp (2024). ESA Anomaly Dataset [Dataset]. http://doi.org/10.5281/zenodo.12528695

ESA Anomaly Dataset

Explore at:
72 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 25, 2024
Authors
Gabriele De Canio; Krzysztof Kotowski; Christoph Haskamp
Description

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. 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. Further details can be found on the arXiv and Github. ReferencesDe 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.

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