Book contents
- Frontmatter
- Contents
- List of tables and figures
- 1 Introducing Research Data Management
- 2 The Social Worlds of Research
- 3 What Are Research Data?
- 4 Case Study of RDM in an Environmental Engineering Science Project
- 5 RDM: Drivers and Barriers
- 6 RDM as a Wicked Challenge
- 7 Research Data Services
- 8 Staffing a Research Data Service
- 9 Requirements Gathering for a Research Data Service
- 10 Institutional Policy and the Business Case for Research Data Services
- 11 Support and Advice for RDM
- 12 Practical Data Management
- 13 Data Management Planning
- 14 Advocacy for Data Management and Sharing
- 15 Training Researchers and Data Literacy
- 16 Infrastructure for Research Data Storage and Preservation
- 17 Evaluation of RDS
- 18 Ethics and Research Data Services
- 19 A Day in the Life Working in an RDS
- 20 Conclusion: the Skills and Mindset to Succeed in RDM
- Index
5 - RDM: Drivers and Barriers
Published online by Cambridge University Press: 21 September 2019
- Frontmatter
- Contents
- List of tables and figures
- 1 Introducing Research Data Management
- 2 The Social Worlds of Research
- 3 What Are Research Data?
- 4 Case Study of RDM in an Environmental Engineering Science Project
- 5 RDM: Drivers and Barriers
- 6 RDM as a Wicked Challenge
- 7 Research Data Services
- 8 Staffing a Research Data Service
- 9 Requirements Gathering for a Research Data Service
- 10 Institutional Policy and the Business Case for Research Data Services
- 11 Support and Advice for RDM
- 12 Practical Data Management
- 13 Data Management Planning
- 14 Advocacy for Data Management and Sharing
- 15 Training Researchers and Data Literacy
- 16 Infrastructure for Research Data Storage and Preservation
- 17 Evaluation of RDS
- 18 Ethics and Research Data Services
- 19 A Day in the Life Working in an RDS
- 20 Conclusion: the Skills and Mindset to Succeed in RDM
- Index
Summary
Aims
The aim of this chapter is to explore the forces that have led to RDM becoming important now, but also to explore why this has not led to change smoothly across every institution and for every researcher. It will prompt you to start to think about how these forces play out across particular institutions, such as one that you work for now or want to work for.
Introduction
This century has seen a gathering momentum behind the idea of research data management and open data.
Data sharing in the sciences has been common practice for many years. It is well established in such fields as meteorology, astronomy and genomics, for example. Data archives for particular fields of research have existed for half a century in many countries. For example, in the UK there has been a repository for social science-related datasets for decades, funded by the main government funder of social science research. Therefore there have also been for a while policies that mandate the deposit of material. Yet the extension of these ideas across the gamut of research is relatively new. Unravelling exactly how this has happened would probably take a book in itself, but it is instructive to explore some of the forces at work, because they pull in somewhat different directions and are still working themselves through. Some are pragmatic, some are ideological. How these arguments play out today at an institutional level will reflect the complexity of the underlying forces. Having a handle on these drivers is essential to positioning your own work effectively, in what is inevitably a rather politicised landscape.
To summarise what follows, much of the increasing stress on RDM can be traced back to the impact of digital technologies on how science is done, and particularly on the amount of data being generated in research and the potential to share it, because of the easy mobility of digital data. In addition, in some subjects there has also been a ‘crisis of reproducibility’: a loss of confidence in the integrity of scientific practice, resulting in a call for greater transparency. There is also a somewhat broader movement to reform research practice, often under the umbrella term ‘open science’.
- Type
- Chapter
- Information
- Exploring Research Data Management , pp. 41 - 56Publisher: FacetPrint publication year: 2018