Qualitative Data Repository 2018-2021

Syracuse University, Syracuse NY

Investigators

Abstract

The Qualitative Data Repository (QDR) curates, preserves, publishes, and enables the download of digital data arising from qualitative research in the social sciences, and from multi-method research in which qualitative data and analyses play a significant role. QDR is the first domain repository in the United States dedicated to working with such data. The repository also develops, disseminates, and promotes standards and techniques for managing, sharing, and reusing qualitative data, and for pursuing research transparency. NSF funding supports QDR?s efforts to increase its data holdings and to develop additional functionality (emphasizing scaling, interoperability, and tools for transparency). The foundation's support also enables QDR to organize customized workshops and training sessions for researchers and data librarians in an effort to expand expertise in qualitative data management and to encourage instruction on qualitative data-management skills. Additionally, the project seeks to further integrate QDR into the academic ecosystem, facilitating interaction with Institutional Review Boards and the social science publication infrastructure, developing new ways for scholars to provide ready access to the data and materials that underpin their publications. QDR expects to receive CoreTrustSeal certification by the end of 2018. The repository is hosted by Amazon Web Services (AWS) and employs the open-source repository software Dataverse. In conjunction with the Dataverse development community, QDR is designing features and functionality that will allow Dataverse to capture the strengths of qualitative data. QDR?s membership in a consortium of U.S. social sciences data archives (Data Preservation Alliance for the Social Sciences [Data-PASS]) guarantees continuous access to QDR data; QDR is also a member of the Data Preservation Network (DPN), which provides distributed long-term preservation for QDR?s data. During the grant period, QDR will introduce several features to further enhance its service to qualitative and multi-method research communities, including: augmented discoverability of QDR data; data curation at the file-level; automated embargoes; custom subsetting; large file transfer; preview of multimedia data; full-text indexing; a message and log system to capture provenance and curation; and a redesigned user interface. QDR is also developing Annotation for Transparent Inquiry (ATI), a solution for rendering qualitative research more rigorous and persuasive that should revolutionize how such research is represented and received. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.