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Collaborative Science: Designing the Future. Dr. Susan Winter University of Maryland, College Park [email protected] National Science Foundation. “ …promote the progress of science… advance the national health, prosperity and welfare… secure the national defense… ”

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collaborative science designing the future

Collaborative Science: Designing the Future

Dr. Susan Winter

University of Maryland, College Park

[email protected]

national science foundation
National Science Foundation

“…promote the progress of science… advance the national health, prosperity and welfare… secure the national defense…”

National Science Foundation Act of 1950

EPSCoR goals

stimulate sustainable improvements in participants’ R&D capacity and competitiveness

advance science and engineering capabilities in EPSCoR jurisdictions

us r d fragmented difficult to influence much less control
US R&D Fragmented: Difficult to Influence, Much Less Control

Universities Inherently Parochial

Government Jurisdictional Issues

Private Sector Competitors

advance science and engineering capacity
Advance Science and Engineering Capacity

Complex intellectual challenges

Multi-disciplinary collaboration among diverse teams sharing common resources

Distributed Geographically

Virtual Organizations!

organization of scientific work
Organization of Scientific Work

Old Science

Lab, Researcher + Assistants

Division of Labor

Narrow Focus of Work

New Science

Complex Problems

Shared Resources

Interdisciplinary Teams

Global Operations, Distributed, Asynchronous

  • Infrastructure Development
    • Enabling Technologies
  • Organization of Work
    • Exploitation of Capability
principles for designing collaborative science organizations
Principles for Designing Collaborative Science Organizations
  • Informed and Reflective Choices
    • General Principles
    • Understand Specific Contexts
  • Likelihood of Success for Kinds of Alliances
  • Knowledge-based Alliances Least Likely
  • Leadership and Processes are Important
  • Silos are Hard
  • Interactions
  • Incentives
  • Insights
    • Building Cultures
    • Building Spanning Roles
knowledge management group and team science
Knowledge Management/ Group and Team Science
    • Trust is Key
    • Absorptive Capacity
  • Tacit vs. Explicit Knowledge
sociotechnical systems
Sociotechnical Systems
  • “If You Build it, They Will Come” Myth
  • Crowdsourcing/Social Participation
    • Citizen Science
    • Prizes/Contests/Competitions
    • Gamification
  • Incentives NOT well understood
3 aspects of scientific work
3 Aspects of Scientific Work
  • Assets
    • What do you have to work with?
  • Knowledge Flows
    • Who tells who about what and when?
  • Governance
    • Who can make what decisions?
    • What are the incentives?
3 aspects of scientific work1
3 Aspects of Scientific Work


Collaboration Success

Knowledge-based Alliances vs. Sharing Equipment or Data

Silos Impede Knowledge Flows

Mandating Use vs. Incentives

  • Assets
  • Knowledge Flows
  • Governance
types of collaborations
Types of Collaborations
  • Lifecycle and Endurance
    • Temporary, Recurring, Permanent
  • Boundedness
    • Problem-focused vs. Group-enabling
  • Scale and Scope
    • 2 vs. 2,000 Scientists
determinants of enablers
Determinants of Enablers
  • Degree of Shared Context
    • Discipline, Department, Organization, Country, Language, Culture
  • Task and Actor Interdependence
    • Divisible, Serial Dependence, Co-creation
determinants of enablers1
Determinants of Enablers
  • Regulatory Environments
    • Degrees of Freedom?
  • Technical and Human Infrastructure
    • Tools
      • Custom, Off-the-Shelf, End-User Developed
      • Heterogeneous Environments (Platforms, Networks)
      • Poor Fit to Tasks
      • Technical Difficulties are the Norm!
    • Human
      • Large Gaps in Expertise on Teams
mix modalities to enable knowledge flows
Mix Modalities to Enable Knowledge Flows
  • Oral
    • Face-to-Face, videoconference, phone
  • Written
    • Manuals/Wikis, Contracts, Journal Articles Pictures/Graphics (drawing boards), Meta-data, MOUs, email, Text Messages, Blogs, Tweets
is this easy no
Is this easy? No!
  • Hitting a Moving Target
    • Will Eventually Sort it Out
    • Goal = Accelerate Process so Get Sorted Faster
  • Hard and Persistent Problems even with the Help of the Organizational Sciences
  • Resources are Sparsely Distributed and Poorly Connected (Who do you call for help?)
    • Hard to Disseminate Lessons Learned
problems are tractable if
Problems Are Tractable If
  • Committed & Not Easily Discouraged
  • In It for the Long Run
    • Issues Play out Over Time
    • Iterative Process of Doing & Learning
    • Synthesis Across Instances for Patterns
  • Know why you are invested in this
    • Complementary Assets
  • Engage Really Good People to Work on Them
designing collaborative research organizations smart learning by doing
Designing Collaborative Research Organizations: Smart Learning by Doing
  • Bring Assets to Bear on the Problem
    • Research Evidence
    • Industry Lessons Learned
    • Assessment for Continuous Improvement
  • Support Leaders and Members for Knowledge Transfer/Deployment
    • Workshops, Manuals, Online Resources
    • More Research/Translation to Practice

Research Evidence:


Understanding Innovation Communities

Translational science

Realizing the Potential

Building Innovation Communities

Tailored suite of materials:

- Practices, tools, processes…

- Scale, Disciplinarity, Pedagogy


Good Practices

Human Capital