Abstract
Traits have become a crucial part of ecological and evolutionary sciences, helping researchers understand the function of an organism's morphology, physiology, growth and life history, with effects on fitness, behaviour, interactions with the environment and ecosystem processes. However, measuring, compiling and analysing trait data comes with data-scientific challenges. We offer 10 (mostly) simple rules, with some detailed extensions, as a guide in making critical decisions that consider the entire life cycle of trait data. This article is particularly motivated by its last rule, that is, to propagate good practice. It has the intention of bringing awareness of how data on the traits of organisms can be collected and managed for reuse by the research community. Trait observations are relevant to a broad interdisciplinary community of field biologists, synthesis ecologists, evolutionary biologists, computer scientists and database managers. We hope these basic guidelines can be useful as a starter for active communication in disseminating such integrative knowledge and in how to make trait data future-proof. We invite the scientific community to participate in this effort at http://opentraits.org/best-practices.html.
| Original language | English |
|---|---|
| Pages (from-to) | 444-458 |
| Number of pages | 15 |
| Journal | Methods in Ecology and Evolution |
| Volume | 14 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Feb 2023 |
Bibliographical note
Publisher Copyright:© 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Open Access - Access Right Statement
© 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Keywords
- data life cycle
- data science
- FAIR principles
- good practices
- metadata
- open science
- phenotype
- trait data