Strengthening the ecosystem for effective team science: A case study from University of California, Irvine, USA

Community member post by Dan Stokols, Judith S. Olson, Maritza Salazar and Gary M. Olson

Dan Stokols (biography)

How can an ecosystem approach help in understanding and improving team science? How can this work in practice?

An Ecosystem Approach

Collaborations among scholars from different fields and their community partners are embedded in a multi-layered ecosystem ranging from micro to macro scales, and from local to more remote regions. Ecosystem levels include:

Judith S. Olson (biography)
  • individual members of teams;
  • the teams to which they belong viewed as organizational units;
  • the broader institutional contexts (eg., universities, research institutes) that support multi-team systems; and,
  • their community and societal milieus (eg., science policies and priorities established by national and international agencies and foundations).
Maritza Salazar (biography)

The success of team-based scholarly and translational initiatives depends on circumstances and events at each of these ecosystem levels and the extent to which they are aligned. For instance, the capacity of a science team to create and apply new knowledge is dependent on the task-specific abilities, interpersonal skills, training, and diverse attributes that individuals bring to their teams. Similarly, the viability and productivity of the team is impacted by the support it receives from institutional leaders and research funding agencies.

Gary M. Olson (biography)

The Team Science Acceleration Lab at the University of California, Irvine

We focus especially on the university-institutional level of the ecosystem and describe an initiative at the University of California, Irvine, USA designed to promote successful cross-disciplinary collaboration on our campus.

We recognize the interdependencies that exist among initiatives undertaken at an institutional level and other facets of the ecosystem, including the importance of articulating university team science programs with the concerns and priorities of community partners and national organizations. The national level is illustrated by the fact that many funding agencies now require cross-disciplinary applicant teams to submit collaboration plans as part of their research proposals. These multiple facets of the team science ecosystem are shown in the figure below.

Key facets of the team science ecosystem, including individual core competencies (orange), a team and its immediate socio-spatial environment (yellow), the institutional contexts of spatially distributed multi-team systems (blue), and broader community and societal influences on team science (green). Links between institutional and societal levels of the ecosystem are denoted by the bi-directional green arrows connecting a particular team (Team 1 or T1) at the center of the diagram with its local environmental, institutional and societal contexts (the yellow, blue, and green circles, respectively). Interdependencies between the team and its immediate socio-spatial environment are shown by the bi-directional purple arrows connecting the orange and yellow circles. In some collaborations, a team must coordinate with spatially removed partners located either at the same institution or at others (eg., multi-team systems spanning two or more universities at the institutional level, and non-academic partners situated in the outermost green circle). These multi-team transactions are denoted in the diagram by the bi-directional pink arrows linking Teams 1, 2, 3, and 4 (T1, T2, T3, T4) (Copyright: Dan Stokols, Judith Olson, Maritza Salazar and Gary Olson).

Establishing a campus culture that supports cross-disciplinary team research requires a comprehensive approach—one that eliminates potential barriers to effective collaboration, and creates structural supports to incentivize inter-departmental, inter-school, and university-community partnerships. From an ecological systems perspective, there are several different “leverage points” within institutional settings that can be aligned so that, together, they exert a positive synergistic influence on faculty and administrators’ efforts to promote cross-disciplinary team science. Six facets of the university-institutional ecosystem that we are initially targeting are:

  1. Ensuring that campus-wide long-range plans emphasize excellence in team science as a strategic institutional goal;
  2. Implementing new promotion and tenure criteria that recognize and reward collaborative contributions to scholarship and translational research, and tools to assist faculty candidates in articulating their contributions to collaborative research as an integral part of personnel reviews;
  3. Establishing equitable criteria for sharing credit among multiple investigators on inter-departmental and inter-school extramural grants;
  4. Allocating seed funding to support the development of new team science initiatives and research centers;
  5. Consulting with facilities planners on the design of team research spaces; and,
  6. Designing and implementing team science workshops and certification courses for faculty and students.

Specific examples of our activities at the Team Science Acceleration Lab include:

  • Working with the university’s Task Force on Interdisciplinarity to ensure that excellence in team science is reflected in the allocation of graduate research and teaching stipends to doctoral candidates working with interdisciplinary research centers and training programs on campus;
  • Planning a campus-wide “Team Science Celebration” event to draw attention to the importance of collaborative scholarship and translational research;
  • Consulting with campus planners on the design of a collaborative research building for the Applied Innovation Institute, which promotes university-community partnerships;
  • Helping develop and implement equitable credit-sharing accounting strategies to incentivize faculty participation in the development of inter-departmental extramural grant proposals and research centers;
  • Developing a new website of team science resources for faculty, students, and administrators;
  • Creating and evaluating a Collaborative Contributions List to help faculty engaged in collaborative scholarship articulate the ways that they’ve contributed to team-based projects as they compile their dossiers for promotion and tenure reviews; and,
  • Presenting team science workshops and courses for departmental and school research directors, members of cross-disciplinary centers and teams (both existing and emerging), and other interested faculty, graduate students, and postdoctoral trainees.

Conclusion

By adopting an ecosystem model for advancing successful team science, we hope to achieve greater synergy toward establishing a campus culture that supports cross-disciplinary discovery, teaching, and translational research. Do you have relevant experience to share? Do you have suggestions for a longitudinal, multi-method study that we’re planning to assess our institution’s cumulative progress toward strengthening cross-disciplinary scholarship, training, and implementation research? We welcome your comments and suggestions.

Further reading:
Bennett, L. M., Gadlin, H. and Marchand, C. (2018). Collaboration and team science field guide. 2nd ed. National Cancer Institute, Bethesda, Maryland, United States of America. Online: https://www.cancer.gov/about-nci/organization/crs/research-initiatives/team-science-field-guide

Börner, K., Contractor, N., Falk-Krzesinski, H. F., Fiore, S. M., Hall, K. L., Keyton, J., Spring, B., Stokols, D., Trochim, W. and Uzzi, B. (2010). A multi-level perspective for the science of team science. Science Translational Medicine, 2, 45

Hall, K., Crowston, K. and Vogel, A. (2014). How to write a collaboration plan. Online: https://www.teamsciencetoolkit.cancer.gov/Public/TSResourceBiblio.aspx?tid=3&rid=3119

Klein, J. T. and Falk-Krzesinski, H. J. (2017). Interdisciplinary and collaborative work: Framing promotion and tenure practices and policies. Research Policy, 46, 6: 1055–61

Zaccaro, S. J., Marks, M. and DeChurch, L. (2012). Multi-team systems: An introduction. In, S. J. Zaccaro, L. DeChurch and M. Marks (Eds).  Multiteam systems: An organization form for dynamic and complex environments, Routledge-Taylor and Francis: London, United Kingdom: pp. 3-32

Acknowledgement:
We thank University of California, Irvine’s Office of Research, Office of Academic Affairs, and Institute for Clinical and Translational Science for their support of this initiative.

Biography: Dan Stokols is Chancellor’s Professor Emeritus at the University of California, Irvine, USA and served as founding Dean of the university’s School of Social Ecology. His research spans the fields of social ecology, environmental and ecological psychology, public health, and transdisciplinary team science. He is author of Social ecology in the digital age and co-author of Enhancing the effectiveness of team science.

Biography: Judith S. Olson is the Donald Bren Professor of Information and Computer Sciences Emerita in the Department of Informatics at the University of California, Irvine, USA. For over 20 years, she has researched teams whose members are not collocated. She co-authored (with Gary Olson) Working together apart: Collaboration over the internet.

Biography: Maritza Salazar is an assistant professor at the Paul Merage School of Business at the University of California, Irvine, USA. Her research focuses on learning and innovation in teams and organizations, especially enhancing the competitiveness of firms, the effectiveness of teams, and the quality of the work experience for individuals. She serves as President of the International Network for the Science of Team Science (INSciTS).

Biography: Gary M. Olson is Professor Emeritus and formerly Donald Bren Professor of Information and Computer Sciences at the University of California, Irvine, USA. The focus of his work has been on how to support small groups of people working on difficult intellectual tasks, particularly when the members of the group are geographically distributed. He co-edited (with Ann Zimmerman and Nathan Bos) Scientific collaboration on the internet.

 

5 thoughts on “Strengthening the ecosystem for effective team science: A case study from University of California, Irvine, USA

  1. […] A crucial goal of cross-disciplinary research teams is the creation of new ideas and conceptual frameworks that advance knowledge within and across fields. The idea tree has proven useful as a brainstorming tool in cross-disciplinary training and research settings. The exercise is especially helpful in prompting novel links between disparate ideas, although the processes of prioritizing, refining and integrating insights derived from the idea tree require longer-term collaborative discussion and metacognition, as described in Machiel Keestra’s recent blog post. Not all of the ideas gathered through the exercise will be deemed sufficiently novel and useful to warrant further development. However, the more time and effort allocated by research teams to knowledge creation and integration activities, the better their prospects for achieving cross-disciplinary insights that trigger scientific and societal advances. The idea tree can be used by research teams at repeated intervals to build their capacity for knowledge discovery and integration. The idea tree is one of the methods used in our research and training initiatives at University of California, Irvine’s Team Science Acceleration Lab described in our previous blog post on strengthening the ecosystem for effective team science. […]

  2. Wonderful depiction of key components of “Team Science Ecosystem”. There needs to be an education awareness campaign at academic institutions and teaching hospitals, industrial partners (Big Pharma), community based organizations to come together and build a “Idea Tree” as to how all these stakeholders can actively enagge in a profound manner to yield more efficient products and services for the greater good of the communities thay intend to serve. Team science and collaborations already take place in small incubator settings with like minded individuals across trans-disciplinary settings, the need is to bring forward this “team science collaborative” mindset as a discipline in itself in a larger platform. The stakeholders have to elaborate the tangible outcomes and how this approach is far better than the conventional methodology where we loose essential time in logitudinal studies and bring in valuable partners at the culmination of the project. It will require a significant behavioral and mindset change from “silos” to “collective” thinking to provide solution oriented end results with mutual respect and greater credit and profit (dollars, patents, and Nobel prize) sharing among partnering team science workgroup members.

    • Anil, thanks for your comments on our article. Your point about the need to scale-up the “team science collaborative mindset” from small incubator settings to broader institutional supports is well-taken. We concur also with your points about the importance of developing appropriate evaluative criteria and research designs to assess the outcomes of multi-pronged efforts to promote more effective cross-disciplinary collaboration at organizational and institutional levels.

  3. Susan, thank you for your thoughtful comments on our post. We appreciate your mentioning Midgley’s work on multi-scale learning, action and accountability; Torbert et al.’s chapter on action research and multi-layered learning systems; and Gergen’s ideas about learning processes and structures. We look forward to consulting these works and to incorporating learning system ideas into our ecosystem analysis of cross-disciplinary team science.

  4. Very sensible and very timely – great approach for thinking through boundaries of responsibility, permeability of boundaries , the value systems that operate at those boundaries, and the dynamics of multi-scale learning, knowing, action and accountability (Midgley, 2001). Resonant of Torbert, Reason and Heron, McNiff and Whitehead’s work (e.g.: 2005 All you need to know about action research. London, UK: London, UK: Sage. pp. 3–5) with regard to First, Second and Third Person learning systems… which could also be useful in this set up: each layer having all three learning dimensions plus the fourth of critical systems thinking and learning. Useful I think to bring the learning dimension into this structural analysis (given structure is slow [learning] process, and process is fast [learning] structure – Gergen, 2015).

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