3. Prepare Data

Publication Year: 08. 04. 2017    Date of last inspection: 08. 04. 2017


It is recommended to start preparing data already in the phase of study planning. A good practice of preparing data for long-term storage and access includes the preparation of a Data Management Plan. By constantly documenting and taking into consideration good practices and standards you can expand the quality of your data.

  The instructions on how to deposit data and documentation: 

  • Data: should be in a digital form, accompanied by appropriate descriptions (size of data file, format; in case of quantitative data: number of variables and units, meanings of codes – for example, the data file ASCII, together with an SPSS program for reading the data file and with the labels of questions and codes, etc.; in case of qualitative data: description of content, context, process of creation of data file etc.).
  • Questionnaire (if used in the study): in case your study used a questionnaire to collect the data, you need to include it in the submission package in its original format.
  • Accompanying materials: it is advisable to include all other possible materials that would help in understanding the content of the submitted data files, such as a codebook, frequency lists, instructions for interviewers, information on how the study was conducted etc.
  • Publications, based on the data: links to the publications (for example COBISS or URN / DOI).
  • All of the files should be sent to the ADP through Cloud or given to us on an appropriate data file exchange media (for example CD-ROM, USB stick etc.).


The ADP staff is available to answer any questions or dilemmas in preparing the documentation for submission to ADP.



The ADP prepared Recommendations on how to manage your data file (2012) (available only in Slovenian) for the users of the statistical program SPSS. You may, of course, use other statistical software of your preference as well.

The document is divided into the following chapters:

– the naming of the variables,
– describing of variables,
– defining values of the variables and open answers,
– managing missing values,
– determining types of variables,
– transforming variables,
– assigning weights,
– managing missing answers,
– anonymization of the data


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We recommend reading the recommendations of the UK Data Service and Finnish Social Science Data Archive for the preparation of your qualitative data file.


  How to cite this page?

Social Science Data Archives. YEAR. 3. Prepare Data. Accessed: http://adp.fdv.uni-lj.si/eng/deli/postopek/priprava/ (DD. month year).