Engaging and rewarding researchers for good data management – what’s important?

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Written by: Marta Teperek

On 23 November 2017 I participated in the launch of the Austrian chapter of Research Data Alliance (RDA Austria). It was an all day long event organised and hosted jointly by colleagues from the University of Vienna, TU Wien and RDA. Fourteen national and international presenters spoke about various aspects of research data management: from infrastructure support, through data publication and citation, and all the way through to data management and data stewardship. In my opinion, the event was highly successful, and I highlighted two interesting discussions which took part during the conference:

  • Discussion about engaging with researchers and what’s important – this blog post (below)
  • Discussion about the challenges for data services and the outlook for the future – separate blog post

Is engagement with researchers important?

In my talk about Data Stewardship at TU Delft, I mentioned that it was important to work closely with local Data Champions in order to deliver tailored disciplinary solutions for research data. Data Champions are researchers who are good at managing and sharing their research data and who voluntarily act as advocates for their local communities. This idea sparked an interesting discussion.

Some people thought that those offering research data support do not have sufficient time to look for Data Champions and to engage with them. They thought that involvement in bottom-up activities drains the energy out of service providers and offers little return on investment. It was suggested that efforts should be invested instead in doing the actual work and collaborating with other service providers. Others questioned the idea of Data Champions and suggested that unless researchers are paid for this, they will not be willing to spend their time advocating about the benefits of data management and sharing.

To be relevant, service providers should not forget about their users

The argument of time investment is an important one. Research data support services are quite new and most of the time they are not yet fully embedded within institutions and the exact scope and priorities are often not well-defined. Therefore, pressures on data service providers tend to be high and the choices on where to invest precious time can be quite hard.

However, the following ‘why’ questions can be asked: “Why do you provide data support services? Why do you want to help researchers manage their data better?”. After some discussion, everyone usually agrees that the core mission of data support services is to help researchers do better research and to improve research integrity. So everyone agrees that the primary users (customers) of the data support services at research institutions are researchers (data creators) themselves.

Now, I might be personally biased as I worked for 6 months for a start-up company and I appreciate the Lean Startup methodology, but I strongly agree with one of the attendees who stated: if service providers wish to develop useful services, they need to talk to their customers. There are numerous examples of companies which failed because they developed products which were not of interest to their customers. Therefore, in my opinion, it is key that as data service providers, we speak with researchers, understand their needs, their problems, and provide solutions which solve these problems. This is essential not only to develop products which are useful to the research community but also to tailor the language used in promoting these services to what the community is indeed interested in hearing.

Of course, one cannot spend all the time just engaging and it is key there is a balance between reaching out to end users and doing the actual work. In addition, it needs to be stated that engagement work at research institutions is not easy. One needs to have good communication skills, high level of empathy, and at the same time understand the researcher, the research they are doing and research data they are collecting. The latter is often necessary to find the common language with the researcher and to even start communication. Such mixture of the different skills might be not easy to find and might mean hiring dedicated people. In fact, when looking to appoint Data Stewards at TU Delft, we primarily searched for people with relevant research background (at least with a PhD degree) and with good communication skills, reasoning that as long as they are interested in data management, we can teach them the information and skills they require.

Searching for Data Champions

Another question was about the effort required to find Data Champions and how to motivate them to do this extra work. Kevin Ashley said that sometimes to find Data Champions it is sufficient to simply know the research community a little bit. Kevin explained that many researchers are already doing excellent good data management work and advocate for better practice within their communities anyway. Those researchers might appreciate a formal reward for their efforts by being officially recognised as Champions.

So are financial rewards necessary to motivate researchers for good data management? This is another important question. Nicole Janz, who champions good research data management, explained that her commitment to reproducible working helped her secure lectureship position. In addition, some people say that researchers are already paid to do research and that doing research equals caring about research integrity and good data management. When (in my previous job) I interviewed David Savage, Principal Investigator at the University of Cambridge, he said that it was “the responsibility of every researcher to the profession to try to produce data which is robust”.

I personally think that the lack of dedicated financial rewards should not justify the lack of good data management practices. Yet, it is one thing to adhere to data management practices, and another to advocate within own research community, which requires time and resources. I think that the latter needs to be formally recognised and appropriately rewarded. However, in order for this to be sustainable, the whole academic rewards system should be drastically revised. Currently, researchers tend to be rewarded for the number of high impact factor publications, rather than quality research and good data management.

Thankfully, the European Commission’s Working Group on Open Science Rewards published the report “Evaluation of Research Careers fully acknowledging Open Science Practices”, which proposes that researchers should be rewarded for their commitment to practising Open Science. The report also contains a very useful matrix with evaluation criteria for assessing Open Science activities and suggests that the commitment to practising Open Science should be implemented in FP9 funding scheme (the successor of H2020). In addition, the report proposes that research performing organisations should use these criteria in their hiring and promotion practices.

So I strongly believe that change is coming (and hopefully in not too long).

Acknowledgement

I would like to thank Raman Ganguly, Paolo Budroni, Kevin Ashley, Barbara Sanchez Solis, Aude Dieude and Rainer Stotzka for inspiring discussions on the topic.

Additional resources

For those interested in rolling out Data Champions programmes at their institutions, the University of Cambridge published the materials used to promote their Data Champions initiative: https://doi.org/10.17863/CAM.7417

One comment

  1. Pingback: Working together for better data – is the future dim or bright? | Open Working

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