Interdisciplinary research data: Challenges & observations from a data steward’s perspective
Throwback to the Research Data Alliance (RDA) 17th Plenary meeting in Edinburgh! On 21st April, Yan Wang, Inna Kouper, Eva Méndez and Connie Clare co-chaired a Bird of a Feather (BOF) session about the Challenges of Curating Data from Interdisciplinary and Collaborative Research.
Aims of the session:
- To share experiences of working with interdisciplinary research teams and their data.
- To share examples of different approaches to discipline-specific data stewardship provision.
- To examine data discovery in an interdisciplinary research context.
- To identify the emergent themes from the discussion and transform them into action items for a potential working group or interest group to address.
The agenda
Check out the presentations:
- Interdisciplinary and highly collaborative research (IHCR) by Inna.
- Interdisciplinary research data – challenges & observation from a data steward’s perspective by Yan and Connie.
- FAIRsFAIR … and the challenge of interdisciplinary research (when the F of Findable, become a D of Discoverable) by Eva.
A session summary by Yan
Interdisciplinary research is receiving more and more attention due to the increasing complexity of societal challenges and the decreasing communication barrier across different research fields. Managing interdisciplinary studies and data becomes a new and important issue that poses many questions when it comes to research data management.
There is still confusion about the difference between interdisciplinary and multidisciplinary research. Having researchers from various disciplines working together on one project does not imply interdisciplinarity, unless they integrate the knowledge, methods and data via a synthesized approach.
We had questions about what exactly interdisciplinary data is…
- Is it a new type of data?
- Is it the application of data in a new domain?
- Is it a new method of processing data?
From the perspective of data stewards, we made a few observations about FAIR interdisciplinary data which brought us more questions and points for discussion with the community.
Findability
The challenge regarding data findability is two-fold. The first challenge relates to the data collection process. Before searching for suitable data, it can be difficult to define the scope and boundary of data sources in interdisciplinary research. This is due to the fact that many interdisciplinary research projects are new and have an exploratory nature which are often proposed in response to specific funding calls. This means that interdisciplinary projects are often temporary, lasting for a limited period of time. In addition, it’s difficult to synthesize expertise and data sources from multiple disciplines. This makes it challenging to create a comprehensive overview of data sources.
Another second challenge relates to the data sharing process. Due to the exploratory and temporary characteristics mentioned above, it’s often unclear as to where the data should be published. Who are the target audiences for data reuse? Would a generic repository be sufficient or would a discipline-specific repository help to reach the relevant audience(s)?
Accessibility
Cross-disciplinary data use and access require additional efforts. For example, medical data is not necessarily limited for reuse in medical fields, but is becoming increasingly important for social and humanities research fields. However, accessing such data usually requires extra procedures to ensure its secure and responsible reuse.
It’s also possible that data is not available for use outside its research discipline. Reasons for this vary from case to case. If an interdisciplinary project demands data collection from multiple disciplinary sources, the accessibility requirements and considerations for all sources need to be considered. This is not an easy task.
Interoperability
Compared to disciplinary research, the creation of data from conducting interdisciplinary research does not always have a clear approach to follow. Following the arguments above regarding the exploratory nature of interdisciplinary research, there are less standard procedures, guidelines and practices in place. Whilst there may be standards for those disciplines involved in the interdisciplinary project, it’s uncertain which of these standards should be adopted or integrated to ensure the interoperability of such data.
Reusability
In general, reusability of data can be difficult to measure since its added value is often not certain until post-publication and so can only be estimated at the moment of publication. Therefore, the reusability of interdisciplinary data is based on hypothesis. Furthermore, mentioned in the discussion about data findability, the target audience for interdisciplinary data is not always clear which makes it even hard to assess reusability.
Ask the audience
In order to clarify some of our thoughts and perspectives on interdisciplinary data, we asked the BOF session participants the following questions during a discussion using Mentimeter:
- What is your professional role?
- What is your research discipline/field of expertise?
- What is interdisciplinary study/data?
- Do you have specific examples to share?
- Do you create/handle/advise on interdisciplinary study/data?
- What is the added value of interdisciplinary study/data?
- What are the challenges of interdisciplinary study/data?
- do you know of any communities that are involved in interdisciplinary study/data?
The session brought many new ideas and positive thoughts about interdisciplinary data. We look forward to following up on these discussions in the future.
Written by Yan Wang (TU Delft)
Edited by Connie Clare (4TU.ResearchData)
