Research Data Management

The most important thing in data management is that you identify the different types of data and are aware of the measures required by them. The data management plan is based on the general description of the data. It should include a brief description of the kind(s) of data you are collecting, creating or using in your research.

In its simplest form, the description can be a short, written text. If you use many different datasets in your study, you might want to present them in the form of a list or a table. Please note that he details of data analysis and research methods are described in the research plan.

Please include the following items in the general description:

• types of data
• file formats
• estimate of the size or quantity of the datasets
• a mention of whether the data include personal data or other confidential or classified information
• measures to be taken to ensure consistency and quality of data.

Distinguish the following:

• data collected for this project (e.g. surveys, interviews, and samples)
• data produced as an outcome of the research process (e.g. analyses of responses to questionnaires, research diaries)
• previously collected existing data which is being reused in this project (e.g. archival materials, statistics, publications).

Please note that the research outputs of your research, such as articles or a dissertation, are not research data and are not included in the DMP. Research literature can be research data if they are the subject of your analysis. In this case they are seen as previously collected existing data.

Research data are typically written text, images, sound or video recordings, or numerical data, but they can also include physical objects. Data can be in digital, analogue or physical format.

Some examples of research data:

• interview recordings
• interview transcriptions
• surveys
• artworks
• samples
• archival materials
• publications
• objects
• research diaries
• researcher’s notes
• source codes and software

Data must always be saved in such a file format that it will be accessible and readable in the future. We recommend using standard file formats that are as open as possible and widely known in the research community.

• Select the file formats already during the early stages of the research project.
• Make sure that the file format selected is suitable for the intended purpose.
• Avoid using file formats controlled by single commercial company unless these are widely used and supported.
• Please note that it may be necessary to convert the file format used to another format for the purpose of long-term storage.

Support in selecting file formats is available through the ICT Services. For further information on selecting file formats, consult the following resources:

The general description of the data must include an explanation of the measures taken in the course of the research project to ensure that the data remains unchanged throughout its life cycle. The quality of the data may be jeopardized, for example, during processing, analysis, transfer or conversion of the data. Explain the measures taken to ensure the consistency and quality of data and how quality assurance is documented.

Some examples of quality assurance measures:

• version control
• consistent data organisation and file-naming conventions
• using standard equipment, methods and software
• checking the transcripts against the original
• using the quality assurance guide
• careful documentation of the stages of data collection and processing
• digitization of analogue data
• training and guidance of members of the research group.