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Complex Adaptive Systems Framework to Evaluate Virtual Research Collaborations

This article discusses the application of a Complex Adaptive Systems (CAS) framework to evaluate virtual research collaborations (VRCs). It compares traditional collaborations to VRCs, highlighting their differences in terms of communication, structure, and flexibility. The article explores various concepts and theories related to CAS, including catastrophe theory, autopoiesis, chaos, and dissipative structures. It also examines the role of feedback, emergence, and self-organization in VRCs. The article concludes by discussing the factors that contribute to successful VRCs and raises important questions for further exploration.

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Complex Adaptive Systems Framework to Evaluate Virtual Research Collaborations

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  1. Complex Adaptive Systems Framework toEvaluate Virtual Research Collaborations Arsev U. Aydinoglu NASA Postdoctoral Program Fellow NASA Astrobiology Institute arsev.u.aydinoglu@nasa.gov

  2. Agenda Traditional vs. Virtual Research Collaborations (VRC) Complex Adaptive Systems (CAS) Application of CAS framework to VRCs Conclusion

  3. Traditional vs. Virtual Collaboration • Distributed • Bottom-up (but not leaderless) • Heavy use of Information and Communication Technology • Fluid, flexible, adaptive • More disciplines, institutions, people • Localized • Top-down • Face-to-facecommunication • Structured, rigid

  4. Complex Adaptive Systems catastrophe autopoiesis chaos dissipative structures autocatalyctic process attractors multi-agent systems thresholds and transformational processes fractal geometry fuzzy logic systems theory

  5. Complex Adaptive Systems Framework

  6. Large number of components/agents NASA Astrobiology Institute, 2011

  7. Diversity & variation MIT Astrobiology Node, 2011

  8. Interaction & interdependence DataONE Organization Chart

  9. Feedback – Nonlinearity Unpredictability

  10. Far from the equilibriumThe edge of chaos

  11. Emergence – Self Organization Strange Attractors

  12. Emergence & Self Organization Publications Relationships Grant proposals New projects WGs Roles Tasks RQs Others

  13. Adaptation to environment/context – Learning – Pattern recognition DataONE Working Group structure Superconducting Super Collider Sandbox by NSF

  14. Co-evolution

  15. Virtual Collaboration CAS framework • Distributed • Bottom-up • Heavy use of Information & Communication Technology • Fluid, flexible, adaptive • More • Components • Emergence • Interaction, feedback, coevolution • Far from equilibrium, adaptation, coevolution • Diversity, interdependence • Localized • Top-down • Face-to-facecommunication • Structured, rigid

  16. Successful VRCs Team composition Leadership Organizational structure Environment Co-evolution

  17. Questions? arsev.u.aydinoglu@nasa.gov arsevu@gmail.com

  18. Information Technology Working Group Composed of IT enthusiasts from each team across both institutes Meets virtually Share lessons learned and knowledge Test hardware, software and integration Promote local adoption of technology and participation Immersed and tightly integrated with the community

  19. DataONE

  20. Why traditional might have failed? The challenge vs. available resources Know-all vs. power of the masses Geeks vs. Social Scientists Funding environment External & internal changes

  21. DataONE

  22. Chart to help select the best collaboration technology and advice for it’s use From RAND Report, “Challenges in Virtual Collaboration”

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