An effective way to organize research coordination meetings

By Gemma Jiang, Diane Boghrat and Jenny Grabmeier

How can large cross-disciplinary science institutes consisting of multiple teams working on multiple research projects overcome significant challenges to research coordination? Key aspects are:

1. Visibility: how to keep different project teams informed of each other’s progress?
2. Learning: how to support cross-project learning?
3. Accountability: how to keep project teams accountable for their goals and deliverables?

Tackling these challenges requires a combination of asynchronous communications such as Slack, newsletters and emails, as well as synchronous communications such as research coordination meetings.

We describe an effective way of organizing weekly research coordination meetings in an institute bridging the gap between computer science and biology and share key reflections.

Monthly themes and weekly perspectives

Each month we select one research theme as defined by institute priorities, then utilize the institute’s recurring weekly meeting-slot to highlight a different perspective on that theme, cycling through the four types of meetings as described below.

1. Project Spotlight: This meeting type makes space for one to a few current research projects in the featured research theme to highlight their research. The main purpose is to provide visibility to ongoing projects and create opportunities for learning across projects. Meetings featuring more mature projects are findings-oriented, while those featuring projects in earlier stages are more questions-driven. Most presenters at these meetings are NextGens (Next Generation researchers, ie., students, postdocs and trainees) in order to support their professional development.
2. Cross-disciplinary bridge: This meeting type aims to bridge the gap between the computer science and biology disciplines. The main purpose is to create a safe space for exploring difficult challenges. Some meetings are led by researchers from either discipline who pose their challenges and seek input from the other discipline. Other meetings are led by bridge builders, such as data scientists, on topics of common concern such as data workflow.
3. External Speakers: This meeting type features a 20 minute presentation by an invited external speaker followed by time for breakout conversations and questions and answers. The main purpose is to build a broad intellectual base with a wider community.
4. Open Space: This meeting type has no predetermined agenda. The purpose is to offer a facilitated space for new ideas to emerge. Topics are crowdsourced from all participants at the beginning of the meeting.

Production team

Each month, a production team is responsible for hosting that month’s four meetings, with their roles described next.

1. Content experts: responsible for curating, organizing or creating content for the meetings. They are: 1) the lead faculty member in the featured research theme; 2) a faculty member from a different discipline, nominated by the lead faculty member; 3) two NextGens supervised by the two faculty members. This combination covers the expertise needed and models cross-disciplinary collaboration. Each content expert is responsible for one of the four weeks and consults with the other content experts.
2. Process expert: responsible for facilitating the meetings and helping content experts think through their meeting objectives. The three authors fill this role at our institute, with Jiang as the main facilitator.
3. Chief doing officer: accountable for the overall success of the meetings. This person assembles the production team and calls meetings, nudges on deliverables, and ensures the smooth operation of each meeting. At our institute, Jiang also serves in this role.

Content experts for each production team are assembled one month prior and generally meet twice. One week before the first meeting of the month, they share meeting descriptions with all institute members through the monthly newsletter. This helps institute members plan which meetings they will attend.

Reflections

We suggest three factors are essential to the success of the meetings.

1. Balance of structure and flexibility: the monthly themes and weekly perspectives provide a solid structure for organization, while each production team has flexibility to interpret what each weekly perspective means for them.
2. Clarity of production team roles and responsibilities: this helps to maximize the effectiveness of each team member, minimizes misunderstandings and reduces unnecessary workloads. In addition, at this institute, involving NextGens in content production addresses a long-standing challenge of low meeting engagement for this particular group.
3. Framing and expectations: weekly meetings are framed as a platform to embody a collaborative culture. Unlike most professional settings where presenters are expected to showcase their findings and talk about their successes, these meetings provide a psychologically safe space for researchers to invite input, ask for help and solve problems together.

Conclusion

This research coordination meeting design is inspired by crowdsourced ideas from all institute members and has continued to evolve in response to feedback collected after each meeting. It mainly addresses the visibility and learning challenges for research coordination. It applies adaptive pressure for the accountability challenge, however complementary efforts are needed for this challenge.

The process described here is focused on routine meetings of established cross-disciplinary teams. A different process is required to generate new cross-disciplinary projects, as described by Gemma Jiang in an earlier i2Insights contribution.

What are your experiences with organizing research coordination meetings? Does this design apply? What else have you put in place? What are your strategies for ensuring project accountability?

Acknowledgement: Funding for this research is provided by the U. S. National Science Foundation Award ID: #2118240 HDR Institute: Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning.

Biography: Gemma Jiang PhD is senior team scientist at the Institute for Research in the Social Sciences (IRISS) of Colorado State University in Fort Collins, Colorado, USA. She applies complexity leadership theory, social network analysis, and a suite of facilitation and coaching methods to enable cross-disciplinary science teams to converge upon solutions for challenges of societal importance.

Biography: Diane Boghrat is program manager for the Imageomics Institute at Ohio State University in Columbus, Ohio, USA. Her work focuses on developing complex multi- and interdisciplinary STEM (Science, Technology, Engineering and Mathematics) programs with an emphasis on cultivating relationships, community engagement, and operational success.

Biography: Jenny Grabmeier MA is research strategist and facilitator at the Ohio State University Translational Data Analytics Institute in Columbus, Ohio, USA. In her role she oversees research awards to catalyze new interdisciplinary, big data-enabled teams and projects, employs a variety of facilitation methods to support team ideation and strategic planning processes, and collaborates with other Ohio State University institutes and entities to advance large-scale interdisciplinary research initiatives.