Team Formation

The foundation for building collaborative science teams begins with thoughtful design of the funding solicitation and an awareness of the multiple administrative roles needed to support collaboration.

Project Solicitation

Collaborative team building begins with the writing of the funding solicitation. Traditionally, researchers respond to a solicitation by gathering together a small handful of trusted colleagues. They write a proposal aimed at convincing the funding agency that their group is best equipped, and has the best ideas, to solve the problem at hand, and should therefore be funded. By funding several such teams in any particular round of funding, the idea is that at least one or two teams will generate enough new ideas to move the field forward. This funding model has generated a lot of high impact science over the years.

But what if a resarch problem is too broad or complex for a single team to address? Many program managers have recognized the need for building connections across the handful of teams that get funded in a project. This is usually motivated by a desire to reduce duplication of effort and to advance the science in ways that cannot be done in isolation.

A well crafted solicitation (click here for a good example) can set the stage for this collaboration to occur. The following elements are critical:

Motivate the collaboration

Scientists are trained to work for long hours in isolation to accomplish highly complex tasks. They usually share this work with a small set of trusted colleagues, based on relationships formed over many years. Asking them to rapidly connect with a large group of new researchers takes effort that should be clearly justified.

A well crafted solicitation will provide a vision for what could be achieved through the extra effort invested in collaboration. Specific examples should be provided, for example the linking of modeling studies with field observations that will lead to improved validation and calibration. In our view, researchers should be encouraged to bring their specialty to the table (in this example, either modeling or field expertise) while describing how they would interface with teams having different expertise. One challenge we have identified is that every team, perhaps in an effort to increase their chances to be funded, proposed to do every part of the collaboration pipeline, leaving us with multiple teams "trying to do it all". We would rather see each team bringing a unique set of skills to the table that can then be integrated with other teams to produce something that could not have been achieved in isolation.

Provide clear expectations

Research scientists who spend time writing proposals get very good at estimating how much time they should request in their budgets to cover the work that needs to get done. But when cross-team collaboration is added to the mix, it gets harder to know how much extra time this will take. Researchers may wonder, should I roll the collaboration in to the amount of time I would have asked for in a less-collaborative proposal? Should I double my request? Am I expected to do the collaboration on the side? A good solicitation will offer some parameters to aid in this decision process. Providing specific guidelines, for example that some percent of effort should be dedicated to collaboration, and to plan budgets accordingly, is ideal.

Provide reporting and reward structures

Building and maintaining collaborations takes time that might otherwise be dedicated to writing papers and advancing one's own individual science objectives. Teams that engage most in a collaborative process may find themselves with fewer academic products such as numbers of papers published. A solicitation that truly wishes to build collaboration should describe other metrics for rewarding collaborations. This might include numbers of datasets shared, participation in leading sub-group activities or numbers of contributions to open-source software repositories. There should also be clear guidelines on how to report on these less traditional academic performance metrics.

Team Selection and Composition

Every agency has its own merit-based system for evaluating proposals that include metrics such as intrinsic scientific merit, relevance to the solicitation and appropriateness of the budget. These systems are designed to evaluate the potential success or failure of individual projects, but to our knowledge there are no formal metrics in place for evaluating a team's collaborative potential and likelihood for building connections across projects. One way this might be improved is by asking proposers to demonstrate how they have approached collaboration in past efforts. Specific examples could include contributions to multi-institution research articles or community open-source software packages.

Once the panel review is complete the successfully-funded projects are notified. A typical solicitation funds 10 to 15 different teams, each of which is led by one lead Principal Investigator (PI) based out of a host institution who manages that particular award. Each of these PI groups often includes several co-investigators, graduate students, postdoctoral researchers and technicians. Therefore the total size of the team involved in the collaboration can be anywhere from 50 to 100 people.

Administrative Roles

Managing and facilitating highly collaborative scientific research requires investment in a variety of administrative roles. We suggest the following positions represent a minimum level of administrative support needed to foster scientific collaboration:

Program Manager

The role of the program manager is to write the solicitation, guide the proposal peer-review process, allocate funds and provide big-picture guidance to the teams. For a high collaborative effort we recommend close coordination between the program manager and other administrative support described below, especially the science team lead. This will help ensure clear communication of high level programmatic needs to the broader group.

Project Manager

There should be a dedicated Project Manager who takes care of logistics, schedules meetings, keeps records of team membership, tracks publications, organizes in-person meetings and facilitates cross-team communications. The best project managers will have some working understanding of the broad research objectives of the teams so that they can be on the lookout for potential collaborative opportunities as they arise.

Science Team Lead

The Science Team Lead is selected from the pool of Principal Investigators who applied to be in this role. In the past this person has been expected to lead their own projects, guide the overall collaboration across teams, and handle logistics associated with data sharing and meeting planning. We feel that allowing the Science Team Lead to focus primarily on facilitating cross-team collaboration creates significant new opportunities. Ideally this person can learn enough of the details of projects across the entire team so that they can unleash the widest range of possibilities for innovative and high-impact research to occur.

We believe top-down, hierarchical leadership approaches applied to this role are not well suited to the complex and shifting research environments typical of highly collaborative teams. We instead advocate for adaptive leadership that enables complex networks of scientists to respond with innovation and creativity as new challenges arise (Uhl-Bien et al., 2007). A modern example of the role of team lead includes that of "science integrator" (Brugger et al., 2016), a person who condenses large amounts of information and distills this to decision makers and stakeholders.

Team Facilitator

Successful collaboration hinges on effective communication. With everyone facing greater demands on their time, meetings between scientists need to be designed to maximize opportunities for connection and exchange of ideas. We believe that partnering with professional facilitators helps achieve these goals. A good facilitator will offer methods for structuring remote and in-person interactions in ways that challenge participants to bring their best ideas to the table, makes the most efficient use of everyone's time, and provides a framework for managing challenging discussions about authorship and data sharing.

Project Data Coordinator

As datasets become increasingly large and complex it has become more difficult for teams to share data across groups. Challenges include a lack of community standards with respect to data formatting and units, institutional firewalls that limit or block the transfer of large datasets, and a wide variety of available programming languages and tools. While many agencies do provide repositories for hosting data for distribution after a publication, collaborative teams also require infrastructure for sharing preliminary results and working products prior to publication. A Project Data Coordinator should be available to facilitate data sharing on secure, flexible platforms that enable file sharing across institutions. This person should also assist in creating consistent metadata, manage data sharing agreements, develop educational material for navigating technical challenges, and be an interface between researchers and the data archival centers.

Principal Investigators

Principal Investigators are responsible for leading their own teams. Within the scope of a collaborative effort, they also have a responsibility to represent their team's work in coordination discussions with the Science Team Lead. Principal Investigators should also play a role in facilitating communication between their team and the broader group.