Metadata is data that describes other data and in this connection metadata means the descriptive information on research data. From the point of view of the researcher, collecting and preserving metadata is about documenting one’s own work and thus an integral part of the research process. It is best to start the systematic storing of metadata already in the beginning of the research so that the research data’s metadata will be up-to-date and of good quality. If metadata is not collected, the future accessibility and usability of a research cannot be guaranteed: in future it might not be possible to determine what the stored data is and why it has been collected. By storing good and high-quality metadata, it is possible to ensure the findability, preservability and future usability of the data and research. 

Metadata can be stored either together with the research data or to a separate file. It is possible to store metadata, e.g. to the research data finder service Etsin. The actual research data can be stored into a discipline-specific data archive or to a national or international research data storage service. Metadata can be stored as a text file but if the research data is extensive, it should be stored using the metadata standards. All the necessary metadata will be collected in accordance with the regulations and in a consistent form with the help of the standards. What is essential is that the metadata can be located and identified in such a universal form that it will be legible also in the future.

Metadata contains the following information:
• name of the research data
• authors and dates
• how the research data has been created and processed
• what is the purpose of use of the data and how it can be reused, i.e. the data’s usage rights and terms
• where the data has been stored to, under which file name and in which file format
• details related to the funding
• subject headings or subject cataloging

Remember version control. Record the possible context information (e.g. the prevailing circumstances at the time of the data collection that have an effect on the observation units) and paradata (e.g. the date of the interview, research situation changes). Document also other potential types of data and devices that advance the research (blogs, social media, researcher collaboration etc.).

For more information


Information Specialist
Anne Karhapää
tel. 0294 45 8213


Data Management Guidelines, Finnish Social Science Data Archive

Siiri Fuchs, & Mari Elisa Kuusniemi. (2018). Making a research project understandable - Guide for data documentation. 

Research data management: Data description and metadata, Curtin University Library

Documentation and metadata, Checklist for the description of metadata, MIT Libraries

Disciplinary metadata, Provides help in the selection of the metadata stardard, DCC



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