Documentation with metadata is a must for data access and re-use.
Metadata is structured and machine readable data about data. Any data file in any format should have metadata fields as without metadata and documentation data sets are meaningless.
Metadata can broadly be broken into e.g.
The main purpose of metadata is to improve finding of research data and therefore it should be standardized, structured and machine and human readable. Metadata should be collected during the research process and the responsible person for metadata is the researcher.
Metadata is supplemented with documention e.g.
Documentation is done in different levels like research project (e.g. methodology), file level (e.g. relationships between files) and variable/item level (e.g. how variable was generated). Metadata is part of documentation.
Practical guide about how to document research data: Siiri Fuchs, & Mari Elisa Kuusniemi. (2018, December 4). Making a research project understandable - Guide for data documentation (Version 1.2). Zenodo. http://doi.org/10.5281/zenodo.1914401
FAIRsharing.org A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies.
Dublin Core metadata standard: Originally
DataCite Metadata Schema: Closely connected to the DOI system - is a list of core metadata properties chosen for the identification of a resource. Consist e.g. relation types to describe relations between RD (e.g. supplement to, version, part of, identical to etc.)
Vocabularies, ontologies and classifications