Institute of Marine Engineering (INM), National Research Council of Italy (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET), Genoa, 16149, Italy.
Arcadia SIT, Vigevano, 27029, Italy.
Sci Data. 2023 Sep 13;10(1):620. doi: 10.1038/s41597-023-02495-3.
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.
必须发布和提供新兴机器人平台收集的环境数据,以支持联合国“海洋科学促进可持续发展十年”(2021-2030 年)下的全球海洋观测系统(GOOS)。这些独特观测数据集的透明度需要相应的机器人记录来支持。描述观测平台行为及其性能的数据对于验证环境数据和一致地重复原位机器人部署是必要的。本文提出的免费和开源软件(FOSS)描述了如何使用地球科学中已建立的方法,按照 FAIR(可发现、可访问、可互操作、可重复使用)原则对海洋机器人任务的数据进行格式化和共享。本文是将海洋机器人遥测数据实现 FAIR 化并使其可发布的分步指南。本文提出、应用并自动集成了最新的元数据和数据格式协议,以最大限度地提高可见度和易用性。这里概述的方法旨在成为实现 FAIR 跨学科观测科学的第一步。