Data Train

Managing qualitative data ST-LE-2026-06

by Prof. Betina Hollstein (SOCIUM), Dr Viola Logemann (SOCIUM)

Europe/Berlin
Zoom

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Description

Motivation

The term “qualitative data” is used for various kinds of non-standardized materials in qualitative social research, including various types of text (e.g. interview transcripts, observation protocols), images, audiovisual data, or material artefacts. From the perspective of “quantitative” research – i.e., the application of statistical methods to standardized numerical data –, qualitative materials just seem to be data that need more structure. But qualitative material is a specific type of data that is usually richer, more context-dependent and more sensitive than quantitative data. On the other hand, qualitative data can be fruitfully analyzed with common tools of quantitative inquiry (e.g. text mining). Thus, this lecture addresses both quantitative and qualitative researchers and aims to introduce them to the particular ethical, legal and practical challenges of managing qualitative materials – e.g. in terms of data protection, informed consent, anonymization, documentation and data sharing – to outline good practices as well as examples of fruitful data management.

Learning contents

  1. Introducing qualitative data & research
    - What is qualitative research? Aims, examples & characteristics
    - Quantitative versus qualitative data & research processes
    - Methodology, context and data in qualitative inquiry
    - Mixing qualitative and quantitative data and research
  2. Managing qualitative data in practice
    - Data collection & informed consent
    - Data transformations for analysis
    - Anonymization/pseudonymization
    - Documentation/contextualization
    - Archiving & sharing data
    - Finding & re-using data

Learning outcomes

Basic overview about qualitative research data and their management.

Prior knowledge

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Further reading

Corti, Louise; van den Eynden, Veerle; Bishop, Libby; Woollard, Matthew (2020): Managing and sharing research data: A guide to good practice. 2nd ed. Los Angeles: SAGE Publications

Organized by

Data Train / U Bremen Research Alliance

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