Tabular strategies for metadata in ecology, evolution, and the environmental sciences

• Published in: Ecology and evolution Vol. 12; no. 8; pp. e9245 - n/a
• Main Authors: Lortie, C. J., Vargas Poulsen, Camila, Brun, Julien, Kui, Li
• Format: Journal Article
• Language: English
• Published: Bognor Regis John Wiley & Sons, Inc 01.08.2022; John Wiley and Sons Inc; Wiley
• Subjects: data; Data collection; Datasets; Ecoinformatics; Ecologists; Ecology; Environmental science; Evolution; Extensible Markup Language; Metadata; open science; Programming languages; R programming language; Repositories; Reuse; tables; Tables (data); template; Viewpoint; workflows
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.9245

Data support knowledge development and theory advances in ecology and evolution. We are increasingly reusing data within our teams and projects and through the global, openly archived datasets of others. Metadata can be challenging to write and interpret, but it is always crucial for reuse. The value metadata cannot be overstated—even as a relatively independent research object because it describes the work that has been done in a structured format. We advance a new perspective and classify methods for metadata curation and development with tables. Tables with templates can be effectively used to capture all components of an experiment or project in a single, easy‐to‐read file familiar to most scientists. If coupled with the R programming language, metadata from tables can then be rapidly and reproducibly converted to publication formats including extensible markup language files suitable for data repositories. Tables can also be used to summarize existing metadata and store metadata across many datasets. A case study is provided and the added benefits of tables for metadata, a priori, are developed to ensure a more streamlined publishing process for many data repositories used in ecology, evolution, and the environmental sciences. In ecology and evolution, researchers are often highly tabular thinkers from experimental data collection in the lab and/or field, and representations of metadata as a table will provide novel research and reuse insights. The last few years have pushed many disciplines to additional computational work. In ecology and evolution, we have embraced and used computation extensively including R, Python, open data, and many other open science tools. Data reuse even within existing collaborative networks can be a challenge nonetheless, and better metadata is the one outstanding issue. Here, we highlight this continued opportunity to improve as a discipline anew. We also provide a novel solution—consider using tables for metadata.