Digital Curation Interviews project with DCC

In this guest blog post, Clara Lines Diaz reports on last year’s Digital Curation Interviews with University of Edinburgh researchers, conducted by the Digital Curation Centre (DCC) on behalf of Digital Research Services.

The project was initiated by staff in the Research Data Service to gain an overview of the research data and software management practices and challenges across the University through in-depth interviews with researchers. The DCC was selected as best placed to conduct the interviews, given its expertise on the subject matter and location at University of Edinburgh. The information was collected through semi-structured interviews during Spring 2023.

2 women talking at table


Image by WOCinTech Chat, Flickr

The motivation to collect this information was to help ensure that researchers are supported in their specific needs and to contribute to shaping the research data management (RDM) services. The choice of in-depth interviews as a method was also expected to help build deeper relationships between service providers and users.

For the semi-structured interviews we had some topic blocks as below, and some prepared questions within each of those blocks. This was used more as a check list for us and we gave the interviewees space to focus on or bring up anything they considered relevant.

Topic blocks:

  • A: Introduction: Research line, projects, collaborations
  • B: Data provenance, types and reuse
  • C: Data/Software management practices
  • D: Influences on data/software management practices
  • E: Data management challenges and sources of assistance

This type of interview works well for exploratory studies like this because it allows common and maybe unexpected patterns to emerge, but also has some caveats around comparability, as not all interviews cover exactly the same topics in the same level of detail. This means that in the results we were able to indicate, for example, how many people mentioned using a particular service, but we could not infer that the others don’t use it, just because they did not mention it.

To select the participants, we contacted research support staff in the three colleges and asked them to suggest participants or send the invitation around. It felt like there was a high interest to discuss these topics and make the challenges they encounter heard, especially among researchers in the College of Science and Engineering (CSE). The interviewees were all involved in data intensive research, with a mix of senior and early career researchers. The interviews were planned to last around 45 minutes but there was some variation in the duration.

From the 14 interviews, four were with staff from the College of Medicine and Veterinary Medicine (CMVM), eight with staff from CSE and two with staff from the College of Arts, Humanities and Social Sciences (CAHSS). The oversampling of CSE interviews was intended as the service team was particularly interested to hear about their practices, which are less well known to them.

Once we had all the interview notes, we extracted the comments and classified them by themes. This was the basis for the final project report, which included a selection of the themes and possible points for action for the Research Data Service and the Research Computing Service in five key areas:

  • Data sharing and reuse was common practice, but there were challenges and areas where further support would be beneficial.
  • Code sharing and collaborative development was widespread and growing, but support and services were perceived as being less mature than that provided for data.
  • External collaboration with university-hosted services could be challenging.
  • Awareness of FAIR and open science was variable.
  • There was an appetite for more training, both for students and staff.

Sharing and reuse had a special focus in the interviews and the first two points are connected to that. Most interviewees had a lot to say about challenges related to sharing and reusing data, especially those working with sensitive data. Some extra advice to help people with those challenges would help. Most interviewees also discussed storing and, in some cases, sharing their code. GitHub is in general preferred for that. Sharing code is in general considered very time consuming.

A briefing was given to the Digital Research Services in August, 2023 and the Research Data Support team was given the transcripts and full results to inform service development.

Clara Lines Diaz
Research Data Specialist
Digital Curation Centre

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