The specification of metadata forms the basis of the FAIR principles. Metadata describes (research) data. It improves the documentation and findability of data. You are already familiar with typical metadata such as title, publisher, author or date. In addition, metadata contains descriptive information about the context of the data, such as measuring devices, measurement location or software used. This helps to better understand the dataset. Metadata facilitates the long-term understanding of the collected research data and supports their subsequent use. The extra effort is worth it!
Metadata and the associated data can be linked e.g. via a persistent identifier or via a README file.
A README file is a text file that is attached to a dataset to describe and understand it. The README file is used to explain what the dataset is about. Primarily, it contains contextual or structural metadata to facilitate reuse. Such information can be, for example, units of measurement parameters, information about processing steps or an overview of individual files in a data package. Overall, the README file should be kept short and simple, but contain all the information necessary to understand the data set.
The development of standards enables an automated and machine-readable exchange of metadata. Currently, the best-known standards are DataCite and Dublin Core.
A list of discipline specific metada standards can be found here: