'One size doesn't fit all': Lessons from interaction analysis on tailoring Open Science practices to qualitative research.

Abstract

The Open Science Movement aims to enhance the soundness, transparency, and accessibility of scientific research, and at the same time increase public trust in science. Currently, Open Science practices are mainly presented as solutions to the 'reproducibility crisis' in hypothetico-deductive quantitative research. Increasing interest has been shown towards exploring how these practices can be adopted by qualitative researchers. In reviewing this emerging body of work, we conclude that the issue of diversity within qualitative research has not been adequately addressed. Furthermore, we find that many of these endeavours start with existing solutions for which they are trying to find matching problems to be solved. We contrast this approach with a natural incorporation of Open Science practices within interaction analysis and its constituent research traditions: conversation analysis, discursive psychology, ethnomethodology, and membership categorisation analysis. Zooming in on the development of conversation analysis starting in the 1960s, we highlight how practices for opening up and sharing data and analytic thinking have been embedded into its methodology. On the basis of this presentation, we propose a series of lessons learned for adopting Open Science practices in qualitative research.