During 22 - 25 November I joined the 14th RDA Plenary in Helsinki with the great pleasure of being selected as one of the RDA EU domain researchers and data Experts. It was my first experience with the RDA plenary: large scale, broad scope, inspiring and professional working conference. I would like to share a few humble thoughts on interdisciplinary research based on some dedicated discussions during the week. Writing them up continued the learning process on how to provide RDM support for this type of research.
Understanding and Empathy
In the co-located event European Open Science Cloud (EOSC) meeting, I participated as the rapporteur of the breakout group discussing FAIR in practice for multidisciplinary research. A few barriers for this type of research to implementing FAIR practices were discussed:
Multi- or interdisciplinary researchers may have no clear choice when it comes to metadata standards. This is due to the lack of clear meaning of FAIR when it needs to cover multiple domains. The development of FAIR applications, approaches, and standards vary across research disciplines and countries. When they collaborate in research, it is hard to come up with concrete indicators to evaluate FAIR adoptions.
Expectations of FAIR come in various forms within specific communities. The FAIR practice coming from one field does not mean it is also a good practice in another one. Technically it is related to the interoperability of data formats and tooling. Socially it has more to do with community acceptance/adoption of specific research activities.
Clearly, when multiple domain expertise is interconnected in one research, the technical and social barriers are often intertwined. Sometimes, it seems to me that social barriers are playing an even more important role since the research culture has a big influence on the adoption of technical solutions. More empathy and attention should be paid to better understand the environment and conditions of multi- or interdisciplinary research.
It is also important for interdisciplinary researchers and RDM supporters to be more aware of the application boundaries of FAIR practices. We need to look at a broader scope when managing expectations on FAIR implementations. If it is challenging to implement FAIR practices at the data level, then a research workflow that enables researchers to become more FAIR should be highly encouraged.
Follow the data: that is where the devil hides
The question ‘what is research data’ is often asked, so was during the RDA P14 week, for instance at the start of the plenary session ‘Data as a game changer’. Data is an absolutely crucial element influencing the decision on choosing proper solutions or designing FAIR practices. From listening to what was discussed during the week, I find the following two aspects may deserve more attention for FAIR data in interdisciplinary research.
Digitizing tacit knowledge
Data is often in the form of electronic record but is definitely not just it. In the keynote presentation given by Tuuli Toivonen at the opening plenary on 23 Nov., she emphasized the importance of capturing and preserving human data in geographical spatial data analysis. This, of course, does not only appear in interdisciplinary research, but it could happen more often when multiple disciplines meet together. For instance, in the field of architecture and the built environment, it is common that physical items (e.g historic maps) or tacit knowledge (e.g. spatial interaction between citizens and the built environment) serving as important research data.
By all means, digitization helps to curate any type of data to different extents, even those originally come in non-digital format. But the difficulty in handling tacit knowledge is that it often comes in intangible format. That demands the corresponding FAIR practices to pay attention to 1) how to properly document it and 2) how to ensure the richness of the knowledge generated from this type of data which should not be hindered during digitalization processes.
Data and its application domain
One difficult question about interdisciplinary research is: what is the research field? This happens often when I was presenting research on information management as a researcher, but also nowadays when I explain the research domain of the architecture and the built environment (the faculty I am supporting as a data steward). Finding a label for research may seem to be trivial for researchers, but it might cause confusion for RDM support when considering disciplinary solutions.
Research in the built environment involves using engineering approaches to research social science and humanities topics. I wonder for these kinds of research, could the practices designed for engineering data or social science data be a good fit? Or a more proper question is which solution should be used at what stage? These are the questions I still could not find concrete answers but got some new thoughts from the RDA P14:
The current way of categorizing disciplinary RDM solutions might not fully represent the reality of research activities anymore. In the IG Research Data Management in Engineering meeting, it was indicated in the group vision that engineering research involves multiple disciplines. In addition to diverse engineering disciplines, it is interesting to see social science is also included in its scope. Can I interpret this as certain disciplinary FAIR practices in engineering research would also be suitable for some specific social science research? If this way of thinking made any sense, would it be more logical to define disciplinary RDM solution on the basis of the type of research data and its specific application domain/context?
RDM: new interdisciplinary research?
My main contribution to the RDA P14 was to present the work on Engaging Researchers with Research Data. This project was part of the Libraries for Research Data Interest Group (L4RD IG). A CookBook has been proudly produced as the first project outcome and a dedicated Birds of a Feather session: Engaging Researchers with Research Data: What Works? was organized during the P14 on 25 Nov.
Engaging researchers is how we can better understand the current status of and needs for FAIR practices and the way to achieve a culture change. Engagement activities come in various forms, from having data conversations, providing training to hiring dedicated disciplinary experts and so on (you would find more inspiring stories in the CookBook). What worth mentioning about researcher engagement is that it should not be overlooked just as a part of other RDM activities (e.g. making DMP or data deposit). RDM is, in essence, a part of research and RDM activities should be embedded in research activities. The role of RDM in research needs to be better perceived by both researchers, librarians, and other support staff.
Thinking about the role of RDM in research, perhaps at a meta-level, it can be considered as a special type of interdisciplinary research? Engagement and co-creation are by default in the nature of interdisciplinary research which involves researchers and professionals from multiple domains. In this sense, there may be a lot in common between RDM and interdisciplinary research: both (at least) try to bridge various fields and steer collaborations. I have listened to researchers and professionals presenting their collaboration on diverse subjects at the RDA P14, such as the Ethics Training for Data Scientist (Ethics and Social Aspect of Data IG), the quality of social science data (Social Science Research Data IG). The RDA participants are already researching together to find solutions to make research and research data FAIR. In addition to the above-mentioned challenges of finding proper FAIR practices for interdisciplinary research, perhaps there is also an opportunity for RDM to learn from it. I am curious to follow this up and see what would it lead to.
The 3-day conference and its co-located events provided a great opportunity to look at so many aspects of RDM and to learn from other professionals about the state-of-the-art on RDM support and FAIR practices. It was especially encouraging to know such a community that is so open, engaging and collaborative. Meanwhile, I am also happy to be back with the researchers at the faculty with all the inspirations from the RDA P14. I am very looking forward to continuing exploring the requirements and application boundaries of FAIR practices in interdisciplinary research at the local level, i.e. in the area of architecture and the built environment. More to be done!