Making Drone Data FAIR Through a Community-Developed Information Framework

被引：0

作者：

Barbieri L. ^{[1
,2
]}

Wyngaard J. ^{[3
]}

Swanz S. ^{[4
]}

Thomer A.K. ^{[5
]}

机构：

[1] University of Vermont, Gund Institute for Environment, Burlington, 05401, VT

[2] Earth Science Information Partners, Severna Park, 21146, MD

[3] University of Cape Town, Department of Electrical Engineering, Cape Town

[4] Washington University in St. Louis, University Libraries, St. Louis, 63130, MO

[5] University of Arizona, School of Information, Tucson, 85721, AZ

来源：

Data Science Journal | 2023年 / 22卷 / 01期

关键词：

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

D O I：

10.5334/dsj-2023-001

中图分类号：

学科分类号：

摘要：

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. © 2023 The Author(s).

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