The term metadata becomes cryptic and often we cannot imagine anything under it. In reality, the term "metadata" covers a very wide range of possibilities for documenting data, especially in the case of research data. They give context to the data at hand and can contain, for example, information about the hardware and software used, people, institutions and projects involved, but also references to other data or publications. Metadata is also the sub-information contained in PDF documents, image files, text files, etc.
Why is Metadata so important?
Unfortunately, without sufficient description of your data, it is useless. This circumstance applies not only to the people who receive the data, but also to yourself, since especially details regarding the collected data are forgotten relatively quickly. In general, documentation via metadata is part of a good RDM practice and simplifies the exchange of data for further use or reuse enormously. If the metadata is even stored in a structured form, machine processing is also possible and a search for specific data/data types, such as in the TU Graz Repository, can be achieved. While implementing reasonable metadata practices may take effort initially, you and others will benefit in the long term through reduced work during research.
Standards for Metadata
Everyone is free to design their metadata according to their own requirements and needs. However, if you want to achieve better comparability and interoperability with other research data, it is recommended to use standardized metadata. These are usually discipline-specific and can often also be machine-readable. A number of metadata standards can be found here and at Fairsharing.
Furhter Information (will be extended continuously)
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