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

TLDR

FAIR principles and standardized reporting formats can increase transparency and collaboration in Earth and environmental science, but the vast diversity of data types makes widespread adoption difficult. The study presents eleven community reporting formats for diverse Earth science metadata and offers guidelines for developing new formats that fit scientific workflows. The authors compiled cross‑domain metadata templates, file‑formatting guidelines, and domain‑specific reporting templates for biological, geochemical, and hydrological data. These reporting formats can accelerate scientific discovery and predictions by making data more interoperable and reusable.

Abstract

Research 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.