Future-proof trait data: from simple rules to practical implementation

1. Trait-based approaches are central to ecological and evolutionary research, offering insights into species functions, interactions, and ecosystem dynamics. As the field increasingly relies on reusing existing trait data, robust data management practices are essential to ensure data long-term utility. 2. While guidelines such as the FAIR principles provide frameworks for documenting, structuring, and sharing trait data, their practical application remains challenging due to the complexity and diversity of available resources. This article addresses these challenges by presenting a step-by-step approach to the data life cycle, using the FAIRTraits plant trait database as a case study. 3. We provide practical guidance on key steps for sharing trait data effectively, including 1) data description, 2) data structuring, 3) data quality control, and 4) data publication. Each step is supported by examples and solutions to common challenges. 4. By offering practical solutions throughout the data-sharing process, we aim to inspire researchers to adopt best practices in data management. We hope this work can serve as a guide through simple practices that can improve the quality, accessibility, and reusability of trait data, supporting future ecological research.