Skip to main navigation Skip to search Skip to main content

Making Drone Data FAIR Through a Community-Developed Information Framework

Research output: Contribution to journal › Article › peer-review

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.

Original languageEnglish (US)
Article number1
JournalData Science Journal
Volume22
Issue number1
DOIs
StatePublished - 2023

Keywords

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

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Making Drone Data FAIR Through a Community-Developed Information Framework'. Together they form a unique fingerprint.

Cite this