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Complex Adaptive Systems Theory Applied to Virtual Scientific Collaborations: the Case of Dataone University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Doctoral Dissertations Graduate School 8-2011 Complex adaptive systems theory applied to virtual scientific collaborations: The case of DataONE Arsev Umur Aydinoglu [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss Part of the Communication Technology and New Media Commons, Library and Information Science Commons, and the Organizational Behavior and Theory Commons Recommended Citation Aydinoglu, Arsev Umur, "Complex adaptive systems theory applied to virtual scientific collaborations: The case of DataONE. " PhD diss., University of Tennessee, 2011. https://trace.tennessee.edu/utk_graddiss/1054 This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a dissertation written by Arsev Umur Aydinoglu entitled "Complex adaptive systems theory applied to virtual scientific collaborations: The case of DataONE." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the equirr ements for the degree of Doctor of Philosophy, with a major in Communication and Information. Suzie Allard, Major Professor We have read this dissertation and recommend its acceptance: Carol Tenopir, Virginia Kupritz, Heather Douglas Accepted for the Council: Carolyn R. Hodges Vice Provost and Dean of the Graduate School (Original signatures are on file with official studentecor r ds.) Complex Adaptive Systems Theory Applied to Virtual Scientific Collaborations: The Case of DataONE A Dissertation Presented for the Doctor of Philosophy Degree The University of Tennessee, Knoxville Arsev Umur Aydinoglu August 2011 ii Copyright © 2011 by Arsev Umur Aydinoglu All rights reserved. iii Dedication I dedicate this study to my Mîr, my lives would not have a meaning without his teachings. iv Acknowledgements I would never have been able to finish (maybe even able to start) my dissertation without the guidance of my committee members; help from my friends; and support from my family. I would like to express my deepest gratitude to my advisor, Dr. Suzie Allard, for encouraging me to think outside the box and to try new approaches in my doctoral education. Without her guidance, intellectual contribution, practical solutions, and sense of humor, writing this dissertation would be painful at best. Her patience towards my wild ideas deserves special thanks. I would like to thank Dr. Carol Tenopir, who supported me since the beginning of my graduate education and provided me with the opportunities to be involved in first class research. I would also like to thank to Dr. Heather Douglas who contributed not only to my dissertation but also my intellectual development with her infinite knowledge on the philosophy of science. Dr. Virginia Kupritz‘s experience and knowledge on mixed method studies helped me to find my way in the labyrinths of abundant data I collected. I am grateful to the members of DataONE. They have accepted me to their meetings, agreed to be interviewed by me, and shared their thoughts and passion on one v of the biggest problems of today‘s science –data. Without their contribution this dissertation would not happen. My very old friend Emine Yetgin for directing me to pursue a PhD and my colleagues Dr. Lei Wu and Dr. Katerina Spasovska for preventing me from derailing to pursue a PhD deserve a huge thank you. Finally, I would like to thank my wife, Pinar. She was always there cheering me up and stood by me through the good times and bad. She also took very good care of my daughter, Neva Isik, when I was immersed in doctoral work and unable to help her. vi Abstract This study is the exploration of the emergence of DataONE, a multidisciplinary, multinational, and multi-institutional virtual scientific collaboration to develop a cyberinfrastructure for earth sciences data, from the complex adaptive systems perspective. Data is generated through conducting 15 semi-structured interviews, observing three 3-day meetings, and 51 online surveys. The main contribution of this study is the development of a complexity framework and its application to a project such as DataONE. The findings reveal that DataONE behaves like a complex adaptive system: various individuals and institutions interacting, adapting, and coevolving to achieve their own and common goals; during the process new structures, relationships, and products emerge that harmonize with DataONE‘s goals. DataONE is quite resilient to threats and adaptive to its environment, which are important strengths. The strength comes from its diversified structure and balanced management style that allows for frequent interaction among members. The study also offers insights to PI(s), managers, and funding institutions on how to treat complex systems. Additional results regarding multidisiplinarity, library and information sciences, and communication studies are presented as well. vii Table of Contents Chapter 1 Introduction ........................................................................................................ 1 Chapter 2 Literature Review ............................................................................................ 10 Scientific Collaborations ............................................................................................... 10 a. Scientometrics ....................................................................................................... 11 b. Qualitative Case Studies ....................................................................................... 14 Complexity Theory ....................................................................................................... 28 Emergence..................................................................................................................... 51 Chapter 3 Background for DataONE ............................................................................... 54 About DataONE ............................................................................................................ 54 NSF the Office of Cyberinfrastructure ......................................................................... 55 The Fourth Paradigm: Data-intensive scientific discovery ........................................... 56 Sustainable Digital Data Preservation and Access Network Partners (DataNet) ......... 57 Data Conservancy ......................................................................................................... 58 The Data Observation Network for Earth (DataONE) ................................................. 58 Chapter 4 Methods ........................................................................................................... 68 viii Case study ..................................................................................................................... 68 Rationale for qualitative inquiry ............................................................................... 70 Sampling ................................................................................................................... 71 Rationale for selecting DataONE.............................................................................. 72 Data collection .............................................................................................................. 74 1. Semi-structured interviews ................................................................................... 75 2. Naturalistic observations ....................................................................................... 79 3. Survey ................................................................................................................... 81 Data Integration, Evaluative Criteria, and Analysis ..................................................... 81 Chapter 5 Results .............................................................................................................. 86 1. Large number of components and counteracting forces: .......................................... 88 2. Variation and Diversity ............................................................................................. 91 3. Connectivity, interdependence, and interaction ...................................................... 103 Interdependency & Working Groups ...................................................................... 105 Communication behaviors ...................................................................................... 113 4. Feedback ................................................................................................................. 116 5. Unpredictability ...................................................................................................... 116 ix 6. The edge of chaos ................................................................................................... 117 7. Self-organization, emergence, and strange attractors ............................................. 117 8. Adaptation to environment (context) / pattern recognition / learning .................... 122 a. The management ................................................................................................
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