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Organization
[The Archive], [The University]
<p>[The Archive] holds decades of irreplaceable social science data. The data exists. Researchers need it. The system between them was built to preserve data, not to surface it — and a preservation-first architecture is the opposite of a discovery-first product.</p><p></p><p>[The Archive]'s data archive contains over 50,000 datasets spanning 70+ years of social, behavioral, and economic research. For much of the archive's history, finding data was addressed by search and metadata fields that worked for expert users with precise queries — and failed for researchers exploring a problem space rather than looking for a specific dataset.</p>
Reframing the User
<p>The archive historically served two user types well: depositors (researchers putting data in) and expert retrievers (data librarians with strong metadata literacy). The user it served poorly was the <strong>exploring researcher</strong> — a PhD student or early-career scientist who knows their research question but not which datasets could answer it.</p><p>Redesigning for the exploring researcher required a fundamental reframing of the information architecture. Archive-first IA organizes by collection, provenance, and metadata schema. Product-first IA organizes by research question, topic, and use case.</p>
Design Approach: Surfacing Context
<p>Researchers weren't failing to find datasets because search didn't work. They were failing because they didn't know what datasets existed, what questions those datasets could answer, or whether a dataset that looked relevant was actually usable for their purposes.</p><p>The design response: instead of leading with metadata fields, redesigned dataset pages lead with research context — what questions this data was collected to answer, what findings it has already produced, and what researchers with similar questions have used it for. Discovery pathways were redesigned around research topics and methods. The catalog search — also the front door for ResearchDataGov — supports keyword, topic, agency, and variable-level search with progressively revealed metadata filters.</p>
Outcome
<p>The Archive as a Product project was a product strategy exercise applied to an institution that didn't think of itself as having a product. Archives preserve; products serve users. The design work demonstrated that those goals are not in conflict. Preservation without access is not a complete mission.</p>
Takeaways
<p>This project is where my background in data and my institutional design work intersect most directly. Datasets in [The Archive] are data artifacts with measurable usage patterns, discovery trajectories, and access rates. Approaching the archive with an analytics lens — which datasets are underused relative to their relevance? which discovery paths are dead ends? — produces design priorities that a purely qualitative approach misses. The archive is a data product. It should be designed and measured like one.</p>
Latest Works
Federal UX · Service Design · Dual Persona · Section 508 Accessibility
Multi-product suite · Responsive, Accessible, Themable · Also base system across the Archive's products
Pipeline UX · Multi-User Workflow Design · React Component Library · Data Preservation