We're gonna need a bigger boat: Scaling up repository support for larger data

As technologies and computational methods continue to improve, researchers are progressively producing both more data and larger datasets. These larger datasets pose challenges to maintaining the sustainability and capacity of the data repositories that researchers are increasingly expected to utilize for openly publishing their datasets. The Texas Data Repository (TDR) is one such repository currently grappling with these challenges and is, in response, working to refine its service model, technical infrastructure, and data retention policy. The Texas Digital Library which hosts the Texas Data Repository strives to develop collaborative solutions and relies upon the expertise of its service users to address community needs. Following this approach, the Texas Data Repository Steering Committee’s subgroup for Larger Data has developed recommendations for how to scale up support for large datasets while allowing control at the institutional level in our multi-institutional repository. In this presentation, we will share these recommendations, the progress that has been made so far, and our strategy for working within the open source Dataverse community to expand the system beyond our own service needs. The material covered here should be of interest not just to managers of other Dataverse instances, but to all who manage data repositories and rely on them for preserving and publishing large datasets.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-05
DOI
https://doi.org/10.5281/zenodo.15604886
Primary Topic
Orthopedic Infections and Treatments
Type
article
Field-Weighted Citation Impact
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article

We're gonna need a bigger boat: Scaling up repository support for larger data

Zenodo (CERN European Organization for Nuclear Research)
Orthopedic Infections and Treatments
article

We're gonna need a bigger boat: Scaling up repository support for larger data

article en

Abstract

As technologies and computational methods continue to improve, researchers are progressively producing both more data and larger datasets. These larger datasets pose challenges to maintaining the sustainability and capacity of the data repositories that researchers are increasingly expected to utilize for openly publishing their datasets. The Texas Data Repository (TDR) is one such repository currently grappling with these challenges and is, in response, working to refine its service model, technical infrastructure, and data retention policy. The Texas Digital Library which hosts the Texas Data Repository strives to develop collaborative solutions and relies upon the expertise of its service users to address community needs. Following this approach, the Texas Data Repository Steering Committee’s subgroup for Larger Data has developed recommendations for how to scale up support for large datasets while allowing control at the institutional level in our multi-institutional repository. In this presentation, we will share these recommendations, the progress that has been made so far, and our strategy for working within the open source Dataverse community to expand the system beyond our own service needs. The material covered here should be of interest not just to managers of other Dataverse instances, but to all who manage data repositories and rely on them for preserving and publishing large datasets.

Zenodo (CERN European Organization for Nuclear Research)
Baylor University (US), Southern Methodist University (US), Mitchell Institute (US), Texas Digital Library (US), Clinical Research Consultants (United States) (US), The University of Texas at Austin (US), Texas A&M University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 36%
Orthopedic Infections and Treatments
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We're gonna need a bigger boat: Scaling up repository support for larger data · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS