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.
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Open Source Tools for Scaling Data Curation at QDR
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.
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- Award ID(s):
- 1823950
- NSF-PAR ID:
- 10219835
- Date Published:
- Journal Name:
- The code4lib journal
- Issue:
- 49
- ISSN:
- 1940-5758
- Page Range / eLocation ID:
- https://journal.code4lib.org/articles/15436
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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