Scaling Up: Expanding Data Repository Support for Growth in Large Datasets
Researchers are increasingly generating larger datasets thanks to improved technologies and methods, which can present a challenge for data repositories that need to scale their infrastructure and services to support publication of these datasets. The Texas Data Repository (TDR) has been working for several years on enhancing its multi-institutional service model, technical infrastructure, and data retention policy in order to better accommodate publishing of large research datasets. The TDR Steering Committee has recently approved recommendations produced by its Large Data group which will result in new work to scale support for large datasets while preserving flexibility for individual TDR member institutions. This presentation will share these recommendations, progress that has been made thus far, and our strategy for collaborating with the open source Dataverse community on codebase contributions that can also benefit other data repositories.
Institutions
- Baylor University (US)
- Southern Methodist University (US)
- Mitchell Institute (US)
- Texas Digital Library (US)
- The University of Texas at Austin (US)
- Texas A&M University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-17
- DOI
- https://doi.org/10.5281/zenodo.15758728
- Primary Topic
- Research Data Management Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00