Data management plan - Documentation and metadata

The data management plan describes how your data will be created, handled, and rendered findable, accessible, interoperable, and genuinely usable. The key to this is the so-called basic metadata (name, authors, description, location, availability, etc.), which is filed and maintained in the research data section of the Converis research information system at the University of Jyväskylä. When the data processing is completed and the research project ends, the metadata will be published from Converis to the JYX publication archive. In JYX, the metadata will be assigned a DOI and a permanent landing page, which will contribute to the referencing, discoverability and accessibility of the data. In this way, you anticipate the future publication of metadata at this point. The publication of metadata does not require or imply the opening of the whole document, but it can be done through the same landing page.

The University's research data policy requires that this basic metadata is always published, even when the data itself cannot be made openly available.

 
Note that the survey data may consist of several different entities and sub groups, which can described separately and may have varying degrees of openness. The data management plan should also address this possibility. If the data are published in a location other than JYX, the basic metadata will be published in the same place. In these cases, too, the aim is to comb the base metadata into Converis and integrate it into the university's research information system dataset.

Documentation of your data is key to the (re)usability and interoperability of your data. Documentation ensures the transparency, reproducibility and usability of your research. It also allows other users (both human and computer) to find and use the files. Without timely documentation, the data soon ends up incomprehensible and hence unusable.

Your records management plan should explain what your records consist of, how they are created, where they are stored and where they may be published.

The most common forms of documentation are systematic README.txt files, field and laboratory diaries, technical metadata from lab equipment, documentation fields in analysis software such as Jupyter, data inventories, annotations, and log files. The list goes on.