QDR (Qualitative Data Repository)

The Qualitative Data Repository (QDR) is a domain repository built specifically for archiving and sharing digital data from qualitative and multi-method social science research — interview transcripts, fieldnotes, focus-group recordings, ethnographic records, and other unstructured data that don’t fit the row-and-column deposit model most general-purpose repositories assume. It is hosted by the Center for Qualitative and Multi-Method Inquiry at Syracuse University’s Maxwell School of Citizenship and Public Affairs, and has received funding support from the National Science Foundation, the Robert Wood Johnson Foundation, the Alfred P. Sloan Foundation, the Institute for Museum and Library Services, and the Mellon Foundation.

What makes QDR a domain repository, not a generalist one

A domain repository is built around the specific data types, confidentiality concerns, and documentation conventions of a particular research community, in contrast to a generalist repository that accepts data from any discipline with minimal format-specific tooling. QDR’s curation workflow, metadata fields, and access-control options are shaped around problems that come up disproportionately in qualitative fieldwork: interview and fieldnote data almost always contain identifiable information about human subjects, provenance and context matter as much as the raw content, and the underlying data often needs to stay partially or fully restricted even when the resulting scholarship is published openly. General data repositories and social-science repositories such as ICPSR or generalist platforms such as Dryad can and do host some qualitative material, but QDR’s tooling — curation checklists, redaction support, tiered access controls, and its own annotation format — is purpose-built for it in a way generalist infrastructure typically is not.

Annotation for Transparent Inquiry (ATI)

QDR is closely associated with Annotation for Transparent Inquiry (ATI), a data-citation and annotation approach it developed to address a transparency problem specific to qualitative and interpretive research: unlike a regression table or a summary statistic, a claim grounded in an interview quote or an archival passage can be hard to trace back to its specific source without reading the entire underlying dataset. ATI lets researchers attach analytic annotations directly to specific passages of a published article, each linking to the precise excerpt of underlying data — an interview transcript segment, a fieldnote entry, an archival document — that supports the claim being made at that point in the text. A reader can click through from a specific sentence in the article to the exact evidence behind it, without QDR having to publish the entire underlying dataset in the open if some or all of it needs to stay access-restricted. This directly answers a criticism sometimes raised about qualitative research transparency: that closed or restricted underlying data makes claims effectively unverifiable. ATI is one implementation of the broader idea of source-level, claim-level data citation in qualitative and interpretive social science, and QDR is the repository most associated with building and maintaining the tooling for it.

Deposit and access workflow

Depositing in QDR is a curated process, not a self-service upload: submissions go through QDR’s own review for documentation completeness, de-identification of human-subjects data, licensing clarity, and file-format suitability before publication. Depositors can apply tiered access controls appropriate to sensitive qualitative material — open access, restricted access requiring an application and QDR review, or embargoed access for a defined period — rather than an all-or-nothing open/closed choice. Published deposits receive a persistent identifier (a DataCite DOI) that can be cited in a manuscript’s data-availability statement in the same way a quantitative dataset’s DOI would be, satisfying the Findable requirement of the FAIR data principles even where the underlying data itself remains restricted, per FAIR’s own Accessible sub-principle that metadata should stay discoverable regardless of the access status of the data it describes. QDR has also reported CoreTrustSeal certification as a trustworthy digital repository, a voluntary certification social-science and general data repositories use to demonstrate they meet baseline standards for preservation, governance, and access practices.

Who uses QDR and why it matters for a data management plan

QDR is aimed at qualitative and multi-method researchers across political science, sociology, anthropology, public health, and adjacent social-science fields who need a repository able to handle interview- and fieldnote-type data responsibly — including researchers who must satisfy a funder’s or journal’s data-sharing expectation but whose underlying material is sensitive, identifiable, or subject to IRB-driven access restrictions. For a Data Management Plan that names a qualitative or multi-method dataset, identifying a domain repository suited to that data type — rather than defaulting to a generalist repository built primarily around quantitative or file-based deposits — is part of choosing an appropriate repository, one of the recurring elements funders and institutions expect a DMP to address.

Related repositories and further reading

See CASRAI’s entries on domain repositories generally, ICPSR (a related social-science domain repository with a broader, largely quantitative focus), Dryad and the CASRAI guide to Dryad’s costs, curation, and DMP fit for a generalist comparison point, and re3data, the registry researchers and funders use to discover a suitable repository — including domain-specific ones like QDR — by subject area and data type.