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What is Computational Reproducibility

Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems
The ability to re-run specified code on the same original data to get the same results as in the original manuscript.
Published in Chapter:
Data Stewards, Curators, and Experts: Library Data Engagement at Samuel J. Wood Library at Weil Cornell Medicine
Peter R. Oxley (Weill Cornell Medicine, USA), Sarah Ben Maamar (Weill Cornell Medicine, USA), and Terrie Wheeler (Weill Cornell Medicine, USA)
DOI: 10.4018/978-1-7998-9702-6.ch014
Research data management practices continue to evolve as data become more connected, distributed, granular, and continuous. While keeping their mandate to serve the academic community, libraries are seeking to foster knowledge creation, learning, and information access in an ever more data-driven and online environment. In this chapter, the authors describe their perspectives that shape the library's mandate, roles, and technology. They detail specific roles that have been created to foster data engagement: a secure enclave data core, an institutional data catalog, scientific software management, bioinformatics and research reproducibility support, data integrity, and community engagement. A constant focus on customer service has shaped each role, built the library's reputation, and contributed to high-impact services.
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