Data Demo for Qualitative Data Research: NVivo, Taguette, Python
Do you have “unstructured data” (e.g., government documents, interview transcripts, site videos) that you want to analyze qualitatively? Are you unsure about which tools fit your needs (small or large dataset, solo or team project) and how to use them?
This demo will use data from a multi-city study of urban greening (climate action plans, oral histories, health measures, videos of urban farmers) to illustrate three tools:
- Commercial software: NVivo (free to Stanford faculty, students, staff)
- Open source software: Taguette (free to all—built using Python and Calibre)
- Programming language: Python (free to all)
Come see (1) how to choose the right tool for you (based on your epistemological assumptions, research questions, dataset size/type, project partners), (2) how to get these tools, and (3) how to use these tools to qualitatively analyze your data. The workshop will include information about Stanford resources for learning these tools.
Alesia Montgomery is the Subject Specialist for Sociology, Psychology, and Qualitative Data at Stanford. For over two decades, she has been engaged in qualitative research and teaching. Her publications include the forthcoming book, Greening the Black Urban Regime, and articles in the International Journal of Urban & Regional Research, City & Community, Global Networks, and Ethnography.
- Specialized Content Knowledge & Skills
- Learning advanced disciplinary knowledge & skills
- Conducting research & scholarship
- Collaborating within & across disciplines