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Accessibility of research data to disabled users has received scant attention in literature and practice. In this paper we briefly survey the current state of accessibility for research data and suggest some first steps that repositories should take to make their holdings more accessible. We then describe in depth how those steps were implemented at the Qualitative Data Repository (QDR), a domain repository for qualitative social-science data. The paper discusses accessibility testing and improvements on the repository and its underlying software, changes to the curation process to improve accessibility, as well as efforts to retroactively improve the accessibility of existing collections. We conclude by describing key lessons learned during this process as well as next steps. 

Expectations to share data underlying studies are increasing, but research on how participants, particularly those in qualitative research, respond to requests for data sharing is limited. We studied research participants’ willingness to, understanding of, and motivations for data sharing. As part of a larger qualitative study on abortion reporting, we conducted interviews with 64 cisgender women in two states in early 2020 and asked for consent to share de-identified data. At the end of interviews, we asked participants to reflect on their motivations for agreeing or declining to share their data. The vast majority of respondents consented to data sharing and reported that helping others was a primary motivation for agreeing to share their data. However, a substantial number of participants showed a limited understanding of the concept of “data sharing.” Additional research is needed on how to improve participants’ understanding of data sharing and thus ensure fully informed consent. 

In this short practice paper, we introduce the public version of the Qualitative Data Repository’s (QDR) Curation Handbook. The Handbook documents and structures curation practices at QDR. We describe the background and genesis of the Handbook and highlight some of its key content. 

Data sharing and reuse are becoming the norm in quantitative research. At the same time, significant skepticism still accompanies the sharing and reuse of qualitative research data on both ethical and epistemological grounds. Nevertheless, there is growing interest in the reuse of qualitative data, as demonstrated by the range of contributions in this special issue. In this research note, we address epistemological critiques of reusing qualitative data and argue that careful curation of data can enable what we term “epistemologically responsible reuse” of qualitative data. We begin by briefly defining qualitative data and summarizing common epistemological objections to their shareability or usefulness for secondary analysis. We then introduce the concept of curation as enabling epistemologically responsible reuse and a potential way to address such objections. We discuss three recent trends that we believe are enhancing curatorial practices and thus expand the opportunities for responsible reuse: improvements in data management practices among researchers, the development of collaborative curation practices at repositories focused on qualitative data and technological advances that support sharing rich qualitative data. Using three examples of successful reuse of qualitative data, we illustrate the potential of these three trends to further improve the availability of reusable data projects. 

The discipline of political science has been engaged in vibrant debate about research transparency for more than three decades. Over the last ten years, scholars who generate, collect, interpret, and analyze qualitative data have become increasingly involved in these discussions. The debate has played out across conference panels, coordinated efforts such as the Qualitative Transparency Deliberations (Büthe et al. 2021), articles in a range of journals, and symposia in outlets such as PS: Political Science and Politics, Security Studies, the newsletter of the Comparative Politics section of the American Political Science Association (APSA), and, indeed, QMMR. Until recently, much of the dialogue has been conducted in the abstract. Scholars have thoroughly considered the questions of whether political scientists who generate and employ qualitative data and methods can and should seek to make their work more transparent, what information they should share about data generation and analysis, and which (if any) data they should make accessible in pursuit of transparency. 

This paper describes the development of services and tools for scaling data curation services at the Qualitative Data Repository (QDR). Through a set of open-source tools, semi-automated workflows, and extensions to the Dataverse platform, our team has built services for curators to efficiently and effectively publish collections of qualitatively derived data. The contributions we seek to make in this paper are as follows: 1. We describe ‘human-in-the-loop’ curation and the tools that facilitate this model at QDR; 2. We provide an in-depth discussion of the design and implementation of these tools, including applications specific to the Dataverse software repository, as well as standalone archiving tools written in R; and 3. We highlight the role of providing a service layer for data discovery and accessibility of qualitative data. 

How can authors using many individual pieces of qualitative data throughout a publication make their research transparent? In this paper we introduce Annotation for Transparent Inquiry (ATI), an approach to enhance transparency in qualitative research. ATI allows authors to connect specific passages in their publication with an annotation. These annotations provide additional information relevant to the passage and, when possible, include a link to one or more data sources underlying a claim; data sources are housed in a repository. After describing ATI’s conceptual and technological implementation, we report on its evaluation through a series of workshops conducted by the Qualitative Data Repository (QDR) and present initial results of the evaluation. The article ends with an outlook on next steps for the project.