Preprints
https://doi.org/10.5194/essd-2023-334
https://doi.org/10.5194/essd-2023-334
22 Sep 2023
 | 22 Sep 2023
Status: this preprint has been withdrawn by the authors.

Enabling FAIR Certification for Micrometeorological Datasets

Mark Roantree, Stevan Savić, Michael Scriney, and Branislava Lalić

Abstract. The current state of weather-induced agricultural losses, water use for irrigation, the appearance of new invasive species and disease vectors, new environmental zoning of plant diseases and pests, deforestation, increased urbanization, rural-to-urban migration and increased urban energy consumption for cooling and heating, together impose a scientific demand for FAIR micrometeorological data. FAIR data and metadata should be easily discoverable by humans or machines, accessible under specific conditions or restrictions, conform to recognized formats and standards to be combined and exchanged, and licensed according to community norms, allowing users to know what kinds of reuse are permitted. However, the lack of FAIR data costs Europe a minimum of €10.2bn per year or approximately 78 % of the Horizon annual 2020 budget. If data met the FAIR principle, it would improve data discovery and access, enable re-use, enhance understanding, especially across domains, reach as many people as possible, be cited more often, and open new routes to build cooperation. To support owners of micrometeorological data to make their data FAIR, the FAIR Micromet Portal was developed within the CA20108 COST Action to guide owners through FAIR principles, in a step-by-step manner, with the ultimate goal of making large volumes of data FAIR. This paper provides a detailed discussion on how this is achieved by validating micrometeorological data stored on the FAIR Micromet Portal against the full set of FAIR metrics.

This preprint has been withdrawn.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Mark Roantree, Stevan Savić, Michael Scriney, and Branislava Lalić

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-334', Anonymous Referee #1, 14 Nov 2023
  • RC2: 'Comment on essd-2023-334', Anonymous Referee #2, 27 Nov 2023

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-334', Anonymous Referee #1, 14 Nov 2023
  • RC2: 'Comment on essd-2023-334', Anonymous Referee #2, 27 Nov 2023
Mark Roantree, Stevan Savić, Michael Scriney, and Branislava Lalić

Data sets

Hourly Air Temperature Datasets from city of Novi Sad S. Savic, I. Secerov, J. Dunjic, and D. Milosevic https://doi.org/10.5281/zenodo.7738093

Metadata of the urban meteorological network in Novi Sad (Serbia) S. Savic, I. Secerov, J. Dunjic, and D. Milosevic https://doi.org/10.5281/zenodo.8237900

Mark Roantree, Stevan Savić, Michael Scriney, and Branislava Lalić

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This preprint has been withdrawn.

Short summary
A recent report on the cost of research that was non-FAIR compliant reached a conservative estimate of 10.2bn. While this should provide a strong motivation for researchers to make their data FAIR, it is not often clear how to do so and researchers should be provided with an understanding of FAIR and a clear pathway to compliance. In this paper, we present our system which helps climate researchers to ensure their data is FAIR compliant.
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