It is important to note the linkage between Research Data Policy, Technology and Support. To promote conscious and successful use of research data, these three aspects should be offered simultaneously to researchers. | LERU, 2013
Data support is designed at various business units and at different levels. Top-down and bottom-up. To work as effectively as possible, it is useful to gain insight into the various interests, roles and responsibilities within and outside your organisation. In this section we outline the force field and invite you to think about the opportunities that exist to shape data support.
The previous chapters have made it clear that there are quite a few players and forces that you may encounter as a data supporter.
A data supporter works in a force field of:
- Laws and policy
What laws and policies do you have to deal with? Organisation-wide, national, European?
- Technical infrastructure
What tools are available? Are they accessible and user-friendly to work with? Do the tools fit in with the researcher's workflow?
Who are involved in RDM? Think of research funders, journals, data archives, etc. And who are your fellow data supporters? Think of the privacy officer, fellow data stewards, the medical ethics review committee, data protection officer, lawyers, policy makers, information security experts, data managers, etc, both in the back office and front office.
What are the prevailing research practices? How do we 'do things' over here?
What does a researcher know about storing, managing, archiving and sharing research data? What do you know and how can your knowledge complement that of the researcher and vice versa?
- Conversational skills
How do you convey what you know? Are you able to find out the question behind the question? How good are your conversational and influencing skills?
What drives a researcher? What makes him or her tick? And what makes you tick? Why are you a data supporter?
In the diagram below you can see a model of the ways in which a number of the above mentioned forces influence each other (RIDLS, 2013).
Influencing the force field
Interventions at one level affect other levels. For example, if an accessible, user-friendly way of sharing research data becomes available within a discipline, this can change the culture within a group (in the long term). Usually, however, it is not possible to draw these kinds of conclusions on a 1:1 basis and there is a 'concurrence of circumstances'. For example, research into the motivation for open sharing of research data shows that there are many visible and invisible dependencies that determine whether researchers change their behaviour (Zuiderwijk & Spiers, 2019). The video below will give you more insight into these dependencies.
Motivations for openly sharing research data and for re-using open research data are interrelated to each other in a complex manner. For instance, if researchers are demotivated because it takes great effort to interpret a particular open dataset, they may still be motivated to re-use that particular dataset if it is strongly relevant to their research. Thus, the different factors have different weights and their combinations need to be considered rather than looking at individual motivation categories in a ‘stand-alone fashion’ | Zuiderwijk & Spiers, 2019
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Zuiderwijk, A., Spiers, H. (2019). Sharing and re-using open data: A case study of motivations in astrophysics. International Journal of Information Management. Volume 49, pages 228-241. https://doi.org/10.1016/j.ijinfomgt.2019.05.024