Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats

Author:

Crystal-Ornelas RobertORCID,Varadharajan CharulekaORCID,O’Ryan DylanORCID,Beilsmith KathleenORCID,Bond-Lamberty BenjaminORCID,Boye Kristin,Burrus Madison,Cholia Shreyas,Christianson Danielle S.,Crow Michael,Damerow JoanORCID,Ely Kim S.ORCID,Goldman Amy E.ORCID,Heinz Susan L.ORCID,Hendrix Valerie C.ORCID,Kakalia Zarine,Mathes Kayla,O’Brien FiannaORCID,Pennington Stephanie C.ORCID,Robles EmilyORCID,Rogers AlistairORCID,Simmonds MaegenORCID,Velliquette TerriORCID,Weisenhorn PamelaORCID,Welch Jessica NicoleORCID,Whitenack Karen,Agarwal Deborah A.ORCID

Abstract

AbstractResearch can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats—instructions, templates, and tools for consistently formatting data within a discipline—can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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