Data sharing may be a particularly useful way for researchers to increase the impact of their research. Readings in this section will highlight what data sharing can look like and why researchers and communities might benefit from these practices.

Sharing qualitative data comes with its own challenges. Depending on the nature of the data, it may not be ethical to share data so that anyone can access it. This section outlines some of the common issues in sharing qualitative data and how researchers might respond to these challenges.

Qualitative researchers tend to approach research from a non-positivist perspective, which affects the kinds of questions qualitative researchers ask, the methodology they use, and the types of conclusions they want to draw. Thus, qualitative researchers have their own way of interacting (or not) with open science practices. These resources will help readers understand how qualitative researchers approach research, and by extension, open science.

Preregistration and registered reports may be useful for qualitative researchers who are hoping to confirm hypotheses. Preregistration may also be a helpful tool for reflexivity for some qualitative researchers.

This section contains articles that outline what open science can look like from a qualitative approach. These articles also outline several places where there may be tensions between mainstream, quantitatively-focused open science perspectives and those often held by qualitative researchers.

Reflexivity is an important practice within qualitative methods, and the critical examination of one’s position within a research study can lend itself to increased contextualization of and transparency in reporting.

Replication is a somewhat controversial topic within qualitative circles. Some researchers (e.g., Makel et al., 2022) argue that replication is useful for supporting transparency and intentionality, examining transferability of findings, and evaluating connections between reflexivity and research findings. Other researchers (e.g., Pownall, 2022) argue that before someone engages in replication of qualitative studies, they should critically examine how, why, and when it would make sense to do so, given differences in epistemologies and ontologies among qualitative researchers.

Secondary data analysis of quantitative methods is now prevalent and encouraged across disciplines in order to reduce costs of data collection, whereas the practice for qualitative data has been fraught with controversy that leads to concerns regarding methodological and ethical dilemmas (e.g. identity of the individual). However, depending on the positionality of the individual, it leads to more nuanced meanings that can ensure researchers can learn from one another. This section outlines some of the issues in secondary data analysis and recommendations to address these challenges.

Transparency in qualitative research tends to focus not only on transparency towards other researchers and/or funders, but also the communities with which they work. Rather than focusing on transparency insofar as it leads to reproducibility, qualitative researchers tend to focus on transparency insofar as it allows readers to understand the context under which research was done and allow them to come to their own conclusions about the extent to which research findings are logical, reliable, and generalizable.