What is metadata? 

Metadata is machine-readable information that describes your research data. Because of its machine-readability, metadata increases the findability of your research data.  Metadata is typically information about the project and/or samples. It can be general, e.g. title of the data set, key words, authors + affiliations, funder, licence, but also discipline-specific, e.g. species, sample type, geographical range. Metadata is provided in a metadata file, for example, the Yoda metadata form, included in the data documentation (see below) and/or entered via a metadata form during the process of depositing data in a repository.  

 

What is data documentation? 

Data documentation tells the story of your research and explains your research data: the who, what, where, when, why, and how. Documenting your research data makes them understandable and reusable. For example, the purpose of your research, explanation of variables/abbreviations in the form of a codebook, steps undertaken in data collection and analyses. Documentation, usually in the form of a README file, accompanies a data set when published or archived.    

 

WUR recommendations 

WUR recommends that you provide both a README file and a metadata file with your data set, as well as a codebook that explains variables, abbreviations, and terminology used in your data files. WUR research data specialists have created templates for both a readme file and codebook. You can download these here. Most data repositories use a metadata standard to describe data sets for which the form is filled in when depositing your research data.