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What is Reproducibility

Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems
An approach to sharing methods and workflows to repeat scientific research.
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Transforming RDM Conversations Into Collaborations: From Projects to Programs to Policy
Plato L. Smith II (University of Florida, USA), Erik Deumens (University of Florida, USA), Matthew A. Gitzendanner (University of Florida, USA), Christopher P. Barnes (University of Florida, USA), Ying Zhang (University of Florida, USA), and Chelsea Johnston (University of Florida, USA)
DOI: 10.4018/978-1-7998-9702-6.ch013
This chapter explores the development of university-wide research data management conversations and collaborations involving key stakeholders at a Research 1 (R1) higher education institution in the southeastern United States of America. Research data management conversations led to collaborations of several key stakeholders across campus (i.e., university, office of research, research compliance office, information technology [IT], researchers, academic units, library) resulting in the development of an inaugural Supporting Data Management at University of Florida (UF) Proposal to the Office of Research draft document in 2019. Funding agencies, research foundations, and research associations increasingly request plans outlining how scientific data from funded research will be annotated, managed, shared, and stored. The National Institutes of Health (NIH) new Policy on Data Management and Sharing becomes effective January 25, 2023. The authors employed a participatory action research method to explore evolving aspects of the data science ecosystem, including research data management.
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Supporting Data-Intensive Analysis Processes: A Review of Enabling Technologies and Trends
Full replication refers to independently repeating a piece of research from scratch in order to obtain the same results. Where replication is not possible or impractical, research artifacts (e.g., data, process records, and code) can be made available as a means to reproduce the same results when the artifacts are analyzed again. Hence, reproducibility of scientific results offers a stepping stone towards full replication, where the more artifacts are made available, the closer we can get towards full replication.
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Making Data Right: Embedding Ethics and Data Management in Data Science Instruction
The ability to come up with the same results produced by another independently using the same data and tools.
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Reproducible Computing
An important principle of the scientific method. It relates to the fact that certain research-related actions can be replicated by others in order to verify/falsify published results or to re-use prior research in new studies.
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“The Future Depends on What You Do Today”: The Library as a Leader in Open Science
An Open Science movement which emphasizes transparency in methods, analysis and outputs and the importance of being able to replicate findings
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