Publication Type
Presentation
Version
publishedVersion
Publication Date
9-2019
Abstract
In recent years, there has been growing interest on Research Data Management, not only from the academic community but also from governments, funders, publishers and research institutions. Research data is increasingly recognized as a valuable output arising out of research activities therefore an asset. It is recognized as a critical evidence in supporting and validating published research claims in the light of an imminent ‘reproducibility crisis’ in some scientific disciplines.
In this presentation, we will share the experiences and learnings in developing and supporting the implementation of a Research Data Policy at Singapore Management University (SMU) in collaboration with our research office and campus IT. An overview of the national and institutional context for RDM will be covered in the presentation. We will also discuss the findings from a series of faculty interviews conducted to understand their research workflow, data characteristics, current practices, etc. We hope that our experiences and reflections will help other institutions that are considering or planning to adopt an RDM policy.
Keywords
research data policy, RDM, Singapore, research data management
Discipline
Library and Information Science | Scholarly Communication
Publication
CODATA 2019: Towards next-generation data-driven science: policies, practices and platforms
Embargo Period
9-28-2022
Citation
DONG, Danping and Yeo, Pin Pin.
Towards an institutional research data policy: Taking a journey at Singapore Management University. (2019). CODATA 2019: Towards next-generation data-driven science: policies, practices and platforms.
Available at: https://ink.library.smu.edu.sg/library_research/201
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.