Minimal Information Framework for Scientific Data Collection from Remotely Piloted Aircraft Systems (RPAS)

. Citation:
Wyngaard, J., Barbieri, L. K., Vardeman II, C., Leahy, B., Swanz, S., Thomer, A.K. (2018). Minimal Information Framework for Scientific Data Collection from Remotely Piloted Aircraft Systems (RPAS). Poster presented at 11th plenary of the Research Data Alliance. Berlin. doi:10.6084/m9.figshare.6145739

Abstract: The image and sensor data collected by Remotely Piloted Aircraft Systems (also known as “drones”, or small Unmanned Aircraft Systems) are rapidly changing the way researchers in many domains collect data. However, in order for these data to be fully utilised they must be made FAIR [Findable, Accessible, Interoperable and Reusable]. An initial step towards achieving FAIRness is to both augment them with machine-readable, semantically-rich metadata, and to annotate them in ways that make their provenance (the record of the processes that created the data) explicit. In RPAS-based research this is particularly challenging given the many agents (e.g. people, RPAS, sensors, controllers, computers, software systems), and complex processes (e.g. pre- and post- correction processing, data integration) with often inexplicit relationships. We are working to draft a minimum information framework for data collected by RPAS, as well as a drone data ontology. The MIF outlines a core set of parameters all RPAS data should be accompanied by. The drone data ontology draws on existing ontologies and semantic web efforts.