A framework for FAIR robotic datasets

Corrado Motta; Simona Aracri; Roberta Ferretti; Marco Bibuli; Gabriele Bruzzone; Massimo Caccia; Angelo Odetti; Fausto Ferreira; Francesca de Pascalis

doi:10.1038/s41597-023-02495-3

Scientific Data (Sep 2023)

A framework for FAIR robotic datasets

Corrado Motta,
Simona Aracri,
Roberta Ferretti,
Marco Bibuli,
Gabriele Bruzzone,
Massimo Caccia,
Angelo Odetti,
Fausto Ferreira,
Francesca de Pascalis

Affiliations

Corrado Motta: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Simona Aracri: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Roberta Ferretti: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Marco Bibuli: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Gabriele Bruzzone: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Massimo Caccia: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Angelo Odetti: Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET)
Fausto Ferreira: University of Zagreb, Faculty of Electrical Engineering and Computing
Francesca de Pascalis: Institute of Marine Sciences (ISMAR), National Research Council of Italy (CNR), Department of Earth System Sciences and Environmental Technologies (DSSTTA)

DOI: https://doi.org/10.1038/s41597-023-02495-3
Journal volume & issue: Vol. 10, no. 1
pp. 1 – 9

Abstract

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Abstract It is essential to publish and make available environmental data gathered by emerging robotic platforms to contribute to the Global Ocean Observing System (GOOS), supported by the United Nations - Decade of Ocean Science for Sustainable Development (2021–2030). The transparency of these unique observational datasets needs to be supported by the corresponding robotic records. The data describing the observational platform behaviour and its performance are necessary to validate the environmental data and repeat consistently the in-situ robotic deployment. The Free and Open Source Software (FOSS), proposed in this manuscript, describes how, using the established approach in Earth Sciences, the data characterising marine robotic missions can be formatted and shared following the FAIR (Findable, Accessible, Interoperable, Reusable) principles. The manuscript is a step-by-step guide to render marine robotic telemetry FAIR and publishable. State-of-the-art protocols for metadata and data formatting are proposed, applied and integrated automatically using Jupyter Notebooks to maximise visibility and ease of use. The method outlined here aims to be a first fundamental step towards FAIR interdisciplinary observational science.

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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