Metadata always have a certain internal structure, even though the actual application can take different forms (e.g. from a simple text document to a table form to a very formalised form as an XML file that follows a certain metadata standard). The structure itself depends on the described data (for example, use of headers and legends in Excel spreadsheets versus a formalised description of a literary work in an OPAC), the intended use and the standards used. Generally speaking, metadata describe (digital) objects in a formalised and structured way. Such digital objects also include research data.

It makes sense, but is not absolutely necessary, for metadata to be readable not only by humans, but also by machines, so that research data can be processed by machines and automatically. Machines are primarily computers in this case, which is why one can also speak more precisely of readability for a computer. To achieve this, the metadata must be available in a machine-readable markup language. Research-specific standards in the markup language XML (Extensible Markup Language) are often used for this, but there are also others such as JSON (JavaScript Object Notation). When submitting (research data) publications, in most cases there is the option of entering the metadata directly into a prefabricated online form. Often it can take a substantial amount of time until a publication is submitted. Thus, it is important that metadata are collected and stored right when data are collected. A detailed knowledge of XML, JSON or other markup languages is therefore not necessarily required when creating metadata for your own project, but it can contribute to understanding how the research data is processed.

Machine readability is an essential point and becomes important, for example, when related research data are to be found by keyword search or compared with each other. A machine-readable file can be created using special programs. In the section “How do I create my metadata” you will be introduced to appropriate programs.