Making Drone Data FAIR Through a Community-Developed Information Framework

Lindsay Barbieri; Jane Wyngaard; Sarah Swanz; Andrea K. Thomer

doi:10.5334/dsj-2023-001

Making Drone Data FAIR Through a Community-Developed Information Framework

Authors

Lindsay Barbieri University of Vermont, Gund Institute for Environment, Burlington, Vermont, 05401; Earth Science Information Partners, Severna Park, MD 21146 https://orcid.org/0000-0001-8495-6402
Jane Wyngaard University of Cape Town, Department of Electrical Engineering, Cape Town, 7701 https://orcid.org/0000-0001-7877-2391
Sarah Swanz Washington University in St. Louis, University Libraries, St. Louis, MO, 63130 https://orcid.org/0000-0001-8728-914X
Andrea K. Thomer University of Arizona, School of Information, Tucson, AZ, 85721 https://orcid.org/0000-0001-6238-3498

DOI:

https://doi.org/10.5334/dsj-2023-001

Keywords:

sUAS, drones, metadata, minimum information framework, uncrewed aerial systems

Abstract

Small Uncrewed Aircraft Systems (sUAS) are an increasingly common tool for data collection in many scientific fields. However, there are few standards or best practices guiding the collection, sharing, or publication of data collected with these tools. This makes collaboration, data quality control, and reproducibility challenging. To that end, we have used iterative rounds of data modeling and user engagement to develop a Minimum Information Framework (MIF) to guide sUAS users in collecting the metadata necessary to ensure that their data is trust-worthy, shareable and reusable. This paper briefly outlines our methods and the MIF itself, which includes 74 metadata terms in four classes that sUAS users should consider collecting for any given study. The MIF provides a foundation which can be used for developing standards and best practices.

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Published

2023-01-25

Issue

Vol. 22 (2023)

Section

Research Papers

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