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Objective: The purpose of this study is to examine the usability of the Texas Data Repository (TDR) for the data depositors who are unfamiliar with its interface and use the results to improve user experience. Methods: This mixed-method research study collected qualitative and quantitative data through a pre-survey, a task-oriented usability test with a think-aloud protocol, and an exit questionnaire. Analysis of the quantitative (i.e., descriptive statistics) and qualitative data (e.g., content analysis of the thinking-aloud protocols) were employed to examine the TDR’s usability for first-time data depositors at Texas A&M University. Results: While the study revealed that the users were generally satisfied with their experience, the data suggest that a majority of the participants had difficulty understanding the difference between a dataverse collection and dataset, and often found adding or editing metadata overwhelming. The platform’s tiered model for metadata description is core to its function, but many participants did not have an accurate mental model of the platform, which left them scrolling up and down the page or jumping back and forth between different tabs and pages to perform a single task. Based on the results, the authors made some recommendations. Conclusions: While this paper relies heavily on the context of the Harvard Dataverse repository platform, the authors posit that any self-deposit model, regardless of platform, could benefit from these recommendations. We noticed that completing various metadata fields in the TDR required participants to pivot their mindset from a data creator to that of a data curator. Moreover, the methods used to investigate the usability of the repository can be used to develop additional studies in a variety of repository and service model contexts.

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