Improving FAIRness of drone data through community effort
Rattachement africain : gb, au, Botswana. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
The use of Uncrewed Aerial Vehicles (UAVs), including both autonomous and remotely piloted aerial systems, is increasingly prevalent across various scientific disciplines, enabling the collection of large volumes of data for diverse research applications. These data are essential for environmental monitoring, such as terrestrial and marine studies, species detection, and atmospheric data collection. However, the volume of data generated and the absence of standardised workflows often complicate data sharing and publication. To address these challenges, the Natural Environment Research Council (NERC) Environmental Data Service (EDS, [1]) has developed guidelines aimed at ensuring that UAV-collected data are Findable, Accessible, Interoperable, and Re-usable (FAIR) [2][3]. In collaboration with the Research Data Alliance, ongoing efforts are focused on developing recommendations for both general and domain-specific data formats and metadata, while also addressing challenges such as ethics and the use of persistent identifiers (PIDs) for instruments [4]. These efforts aim to streamline the data lifecycle for research using small UAVs and autonomous platforms, facilitating integration into research cloud infrastructures. [1] https://eds.ukri.org/environmental-data-service[2] Fremand, Alice. 2023 UAV data management handbook. UK Polar Data Centre, British Antarctic Survey, 13pp. https://nora.nerc.ac.uk/id/eprint/536392/[3] Fremand, Alice. 2023 Towards a data commons: Imagery and derived data from autonomous and remotely piloted aerial vehicles. UK Polar Data Centre, British Antarctic Survey, 24pp. https://nora.nerc.ac.uk/id/eprint/536398/[4] https://www.rd-alliance.org/groups/small-uncrewed-aircraft-and-autonomous-platforms-data-working-group/members/all-members/
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Improving FAIRness of drone data through community effort
- Date Crossref
- 18/03/2025
- Éditeur
- Copernicus GmbH
- Type
- posted-content
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