Teaming and Collaboration

Charter

This Working Group supports the Grand Challenges (GCs) and the Bridge Center to enable team science across the Consortium. It builds synergies that empower members to work effectively in a cross-disciplinary environment by implementing a dynamic suite of evidence-based approaches that foster collaboration. Our practices help ensure that the consortium works effectively to deliver reproducible, interoperable, and AI‑ready data resources.

Overview

The Bridge2AI Teaming and Collaboration Working Group facilitates the development of a shared team identity and a collective mental model for how Bridge2AI operates as an interdisciplinary and welcoming consortium.

Our work is grounded in the 10 foundational pillars of team science[1]:

Trust
Self-awareness
Vision
Leadership
Mentoring
Communication
Conflict and disagreement
Team evolution and dynamics
Recognition and sharing success
Navigating and leveraging networks and systems

These pillars guide how we design, implement, and evaluate collaborative structures.

Core Focus Areas

1. Evaluation and Reporting

We systematically assess the uptake and effectiveness of consortium methods and collaborative interventions.

This includes:

Reporting on adoption of best practices
Implementing evaluation plans to measure Bridge2AI’s impact
Monitoring governance effectiveness and team functioning
Using evidence-based metrics to improve team effectiveness over time

Cyclical monitoring, evaluation, and refinement ensure that all voices are heard and that interventions are demonstrably effective.

2. Team Science Development

This focus area emphasizes the creation of methodologies for interdisciplinary research across the consortium. It includes producing training materials, facilitating seminars and workshops, and generating measures to assess team science success across Bridge2AI. These efforts support the development of structured, measurable, and sustainable approaches to collaboration.

3. Community and Landscape Assessment

We assess community alignment and readiness to support sustained collaboration across Bridge2AI.

Activities include:

Evaluating community agreement on governance processes
Conducting landscape analyses of team science practices
Identifying strengths, opportunities, and gaps in collaboration structures

This ensures that governance and teaming structures remain responsive, transparent, and aligned with consortium needs.

4. Cross-Grand Challenge Support

This focus area centers on identifying common challenges across the Grand Challenges teams and working collaboratively to support and enhance solutions for all working groups. Through shared problem-solving and coordinated efforts, the Working Group strengthens alignment and promotes collective progress across the consortium.

How we work

Our goal is to promote authentic, interdisciplinary research that brings together stakeholders across disciplines in pursuit of new knowledge. We lead the collaborative development and annual revision of Bridge2AI governance processes, disseminate toolkits for best research practices, and implement structured mentoring and leadership strategies.

Through continuous evaluation, structured feedback loops, and data-informed decision-making, we generate empirically tested models for teaming success and intervention strategies for common challenges in AI-driven consortia.

This integrated approach ensures that collaboration within Bridge2AI is intentional, measurable, inclusive, and continuously improving.

[1] Collaboration and Team Science Field Guide – Center for Research Strategy. In: National Cancer Institute [Internet]. 2018 [cited 15 Jan 2020]. Available: https://www.cancer.gov/about-nci/organization/crs/research-initiatives/team-science-field-guide/collaboration-team-science-guide.pdf