Reproducibility Needs Reshape Scientific Data Governance
Computers and Society
2024-10-18 v1
Abstract
Scientific data governance should prioritize maximizing the utility of data throughout the research lifecycle. Research software systems that enable analysis reproducibility inform data governance policies and assist administrators in setting clear guidelines for data reuse, data retention, and the management of scientific computing needs. Proactive analysis reproducibility and data governance are integral and interconnected components of research lifecycle management.
Cite
@article{arxiv.2410.12800,
title = {Reproducibility Needs Reshape Scientific Data Governance},
author = {Paul Meijer and Yousef Aggoune and Madeline Ambrose and Aldan Beaubien and James Harvey and Nicole Howard and Neelima Inala and Ed Johnson and Autumn Kelsey and Melissa Kinsey and Jessica Liang and Paul Mariz and Stark Pister and Sathya Subramanian and Vitalii Tereshchenko and Anne Vetto},
journal= {arXiv preprint arXiv:2410.12800},
year = {2024}
}