Data processing

When choosing research tools, it is advisable to think beyond the immediate needs of a single project. A good choice enables data to be re-analysed in the future and research outputs to be reused. Wherever possible, researchers should favour open-source software that supports widely used open file formats and has an active user community, as this often indicates long-term sustainability and support. Failing to consider these factors can undermine the reproducibility of research. For example, access to proprietary software may be lost if a licence is no longer available, or software required to process a specialised file format may cease to be developed altogether. This does not mean that commercial software should be avoided. In many cases, proprietary tools are the most effective option for a particular analysis. Where such software is used, however, researchers should ensure that it allows data to be converted into an open file format.

Integrated development environment for the open-source statistical programming language R

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Free and open-source tool for qualitative data coding

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Recommended tools for data processing

For statistical analysis, we recommend R (in the development environment RStudio or Positron; both work on Windows, macOS and Linux) – it is a free, open-source and widely used statistical programming language. Stata and SPSS continue to be widely used in the social sciences, but they are proprietary and closed source, which means that replicating the analysis may depend on access to the relevant software licence. The licences of SPSS and other software can be purchased via the IT helpdesk.

Survey data can be collected using the university’s LimeSurvey environment, which students and staff can access using their University of Tartu user account.

A widely used tool for coding qualitative data in the social sciences is MAXQDA, a commercial software package. The University of Tartu does not provide a centrally managed licence for MAXQDA, but licences can be purchased on a project basis through the IT helpdesk portal. Open-source alternatives include QualCoder and Taguette, which offer a more limited range of features but are open source and support the open file format REFI-QDA. Another commonly used tool for qualitative content analysis is the web-based platform QCAmap.org, which, however, is not recommended for coding sensitive material.

Please note

When processing personal data or other sensitive information, it is essential to ensure that the chosen tools adequately protect data confidentiality and that the data is not transferred from the university to external software providers’ or service providers’ servers. For this reason, it is recommended to analyse data either on a university-managed workstation or within cloud services administered by the University of Tartu. Personal data must not be processed in commercial generative AI tools (such as ChatGPT, Claude, Copilot, Gemini, etc.), as this could lead to such information reaching third parties.

Good to know

Practical guidance on issues to consider when processing research data can be found in Chapter 3, “Processing Data”, of the CESSDA Data Management Expert Guide.