Module 09 - Developing data management culture in research teams¶

It is vital to ensure the continuity of data management throughout the research life cycle. Data management is most effective when pursued as a team, with a consistent and cohesive long-term plan and some division of labour. A little effort early in the process can go a long way! Here we highlight two strategies to support research teams in achieving their data management aspirations.

Documenting data management guidelines for research teams¶

We recommend that research teams develop clear documentation around on- and off-boarding procedures and daily data management practices. This will streamline the process of joining the team, provide guidance on the options for and constraints around data transfer, storage, and access. This also paves a clear pathway for ongoing access to data, or the packaging of data and metadata for long-term storage upon departure.

Documentation of team guidelines can be hugely beneficial, both for the team leader in setting out expectations, and for members in understanding their obligations. Such guidelines are best co-developed by the team, with team members bringing the knowledge of the day-to-day minutiae required to meet the expectations set out by the team leader, while leaders can provide the deeper understanding of the structural and institutional limitations the team are working within. Further, to ensure balance within the team, it is important for all members to recognise that these expectations can be bi-directional. Not only does the team leader have expectations for the conduct and contributions of team members, but team members also will have expectations for their team leader. By clearly documenting these expectations, open conversations can be had at an early stage in the development of these relationships to guide interpersonal interactions among the research team.

We do not intend to dictate what these relationships and interactions should look like, but merely highlight some aspects that research teams may wish to address and clarify in a research team strategy or other documentation, and specifically those aspects pertaining to data management. Clarity around expectations will be key in developing unified strategies, and emphasis can be made that data management is a responsibility of all team members. Daily data management practices can be described through a series of 'How To' guides. Topics for these 'How To' guides may include:

tracking samples and managing inventories
recording and maintaining metadata
data decision-making processes (including access to and use of relevant data storage options across the research life cycle)
developing and managing DMPs
data sharing consistent with DMPs
documenting analysis and using version control
maintaining an up-to-date list of key people within the team and institute.

These guidelines can be documented in a research team manual that clearly lays out on- and off-boarding processes, bi-directional expectations for interpersonal relationships, relevant ethical considerations and expectations, and any institutional requirements that may arise across the research life cycle. Some examples of these include, but are not limited to completing student-supervisor agreements, project proposals, human or animal ethics applications, and funding applications to support research or conference travel.

Implementing a self-reflective retrospective following project completion¶

Self-reflective retrospectives are commonly used as part of agile meeting practices. A self-reflective retrospective process can be used following project completion to help identify which aspects went according to plan, where needs changed over time, and where limitations or challenges occurred due to institutional or infrastructure constraints. An example format could be:

List 3 things that worked well when developing and/or actioning the project’s DMP.
List 3 things that created limitations and challenges when developing and/or actioning the project’s DMP.
List 3 things you might do differently next time to improve the process.

The team can then come together to discuss, or the project leader can collate the feedback from these self-reflective retrospectives to identify where there are opportunities for improving processes.

Establishing a research data management culture in your team¶

To ensure consistency despite the potential for frequent turnover within the team, we suggest that research teams establish a data management champion to oversee the onboarding and training of new members and ensure the implementation of consistent data management practices across the research team. While anyone can take on this transferable role, a data management champion will ideally have a mid- to long-term position within the research team, hold a deep understanding of the unique characteristics of each research project, and have the necessary level of autonomy to operate independently as a leader in this role. Succession planning for this role will be essential to ensure consistency and continuity.

This person can also operate as a conduit between the research team and eResearch and libraries staff, and so excellent people skills will be advantageous. By engaging regularly and often with their institute’s support structures, they can ensure that eResearch and libraries staff are kept up to date with the changing needs of the team, and ensure access to the latest services and support.

Navigating conflicting perspectives¶

Navigating high risk, high consequence (whether perceived or real) situations is stressful and can place a significant strain on working relationships. This is compounded in situations with imbalanced power dynamics, which can have particularly severe consequences for those holding less power (e.g., early career researchers (ECRs)).

Below we outline a hypothetical scenario between Taylor and a fellow PhD student, Yana, that demonstrates some of the challenges that may arise due to conflicting perspectives around data management, followed by two dichotomous outcomes. This hypothetical scenario does not seek to address all issues relating to interpersonal relationships and conflict. We acknowledge that individuals in such situations experience unique and complex challenges, requiring tailored problem-solving.

Taylor and Yana met at a conference after Yana saw Taylor present on their research which used similar methods to Yana’s project, and included discussion of their process of engagement with Indigenous research partners. Despite being based at different institutions, they have a lot in common, and have become good friends. However, they are experiencing different research cultures in their teams.

The research culture in Yana’s team is competitive but friendly, with other students addressing different questions within the same system. The Research Team Leader (RTL) is highly motivated to publish, and places a great emphasis on rapid outputs, especially publications. Beyond dissemination to the wider scientific community, he does not consider science communication with the wider public a priority for the research team. Yana is excited to be part of such a fast-moving research team, but has recently become concerned about potential Indigenous data sovereignty needs for data generated during their PhD. The RTL has said that their focal species is not culturally significant. However, Yana has learnt that a number of samples were collected from several sites on land of cultural importance to an Indigenous group, and that there has been no engagement or consultation with the Indigenous community to date. Through ongoing conversations with Taylor, Yana is now questioning the research practices of her RTL and how they may impact the wider team, especially because a lot of the samples she is using are shared across multiple projects.

Yana: Hey Taylor! I’m struggling with something that I’ve been wanting to talk to you about for a while now. Have you got time to talk?

Taylor: Sure! How can I help?

Yana: I’ve tried to have a conversation with my RTL about Indigenous engagement related to some of the samples that I’m using in my thesis that were collected at several culturally significant sites. It did not go well. He basically encouraged me not to get distracted from the research.

Taylor: I’m sorry to hear that friend. It sounds like it was a hard conversation to have.

Yana: I would like to engage with the local Indigenous community about our work and find out if they have data management needs for these samples. But I’m worried my RTL thinks I am making trouble. I realise that engagement takes time, and I don’t want to hold up the whole team.

Taylor: That’s such a hard position to be in. I know your team puts a lot of their focus on publications, so the pressure is real. But, ultimately, something I’ve learned from Prof Nepia is that it’s the RTL’s role to lead Indigenous engagement. Have you shared your concerns with the wider team?

Yana: No, it’s never come up. But I could try to start a conversation and see what they think.

Taylor: Definitely, you may be surprised - it’s possible that others share your concerns, but felt hesitant to speak up.

Yana: I hadn’t thought of it that way. Thanks Taylor!

Outcome A¶

Following her conversation with Taylor, Yana learned that members of her research team shared many of the same concerns but were similarly intimidated by the idea of raising the issue with their RTL. With support and encouragement from the team, Yana raised this topic for discussion during a team meeting. The RTL was surprised to learn of the team’s concerns, as he was unfamiliar with the developing awareness within the field of biodiversity genomics of the need to engage with Indigenous communities. He was grateful to have these developments raised by the team. He is now learning about Indigenous data sovereignty and the CARE Guiding Principles, and gaining support from his academic and professional colleagues with experience working with Indigenous communities.

Outcome B¶

Following her conversation with Taylor, Yana’s conversations with her research team do not go well. Although some share her concerns, none felt comfortable discussing them with the RTL. Unsure of what to do next, Yana goes back to Taylor.

Yana: I talked to my teammates, but no-one feels comfortable trying to approach our RTL with me. I tried to speak to my RTL about my concerns again, but he got frustrated with me. I don’t know what to do next.

Taylor: Would you like me to reach out to my Supervisor, Professor Nepia, for some advice?

Yana: Yeah! I think that would be great.

Professor Nepia encourages Yana to seek support at her institution. For example, at the departmental level, she could reach out to a trusted academic for confidential advice, or seek support from a graduate advisor on how to approach these conversations with her RTL. Beyond her department, Yana could reach out to the graduate school, or the graduate students' association. Dedicated support services like these are best equipped to provide institution-specific advice and support. Professor Nepia is keen to hear how it goes, and offers to provide additional advice if needed.

Both outcomes rely on ECRs having access to a supportive research environment within their teams, departments and institutions.