This practical guide to collecting metadata in agricultural research aims to provide an easy and practice-oriented introduction to the world of data documentation. A decision tree guides researchers with simple, practical questions through the topics: 1 Why data should be documented; 2 Which forms and formats are appropriate for data documentation in your own project; 3 Which metadata should be collected for your own research data; 4 How the metadata can be created; 5 Which forms of storage and linking with the research data should be considered; and 6 How the quality of the metadata can be ensured. In addition to the decision tree, this document also contains brief explanations of terms (Appendix I) that should be understood in order to answer the questions in the decision tree meaningfully. In addition, a metadata guide (Appendix II) with many agricultural science examples provides an overview of metadata, metadata schemas, terminologies and various forms of metadata collection and storage. Internal links in the decision tree refer to specific term explanations or further explanations in the metadata guide. The decision tree and the explanation of terms are available in German and English. For a proper reusability, both versions (German and english) are available in different formats (odt, docx, pdf). An interactive version of the decision tree was made by Justus Schneider: https://fairagro.github.io/metadata_decision_tree/index.html