(Optional course) Data compilation and documentation 

Knowledge: Students obtain up-to-date knowledge of data archiving, data quality rules and checks, and data management and documentation technologies.
Skills: Students are able to complete a codebook documentation of empirical data.
Attitudes: Students obtain a positive attitude toward data archiving as a method of conserving expensive resources and understand its significance for further research and teaching.

The completion of the MSc thesis involves conducting an empirical research study, where research master students collect and analyse primary and/or secondary qualitative and/or quantitative data to investigate their thesis topic. For the student and the wider research community the empirical data are often useless without a technical documentation describing the data file. Hence it is important to adequately document and archive the data in an efficient and consistent manner. Thorough data documentation facilitates checking and preservation of a dataset and ensures that the wider academic public will be able to use the data. It reduces the likelihood of incorrect use of the data by others and it can also help students should they return to the dataset for analysis at some stage in the future.
The minimum material that should be created and preserved in the form of a data documentation typically includes contextual information about the thesis topic, information about the data collection methods and the structure of the dataset, and technical information about, if applicable, variables and values, coding and classification schemes, derived variables, weighting and grossing, missing data, validation and cleaning and other checks.