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Institutional and Individual Influences on Scientists' Data Sharing Behaviors

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Institutional and Individual Influences on Scientists' Data Sharing Behaviors Syracuse University SURFACE School of Information Studies - Dissertations School of Information Studies (iSchool) 2013 Institutional and Individual Influences on Scientists' Data Sharing Behaviors Youngseek Kim Follow this and additional works at: https://surface.syr.edu/it_etd Part of the Library and Information Science Commons Recommended Citation Kim, Youngseek, "Institutional and Individual Influences on Scientists' Data Sharing Behaviors" (2013). School of Information Studies - Dissertations. 85. https://surface.syr.edu/it_etd/85 This Dissertation is brought to you for free and open access by the School of Information Studies (iSchool) at SURFACE. It has been accepted for inclusion in School of Information Studies - Dissertations by an authorized administrator of SURFACE. For more information, please contact [email protected]. Abstract Institutional and Individual Influences on Scientists’ Data Sharing Behaviors by Youngseek Kim In modern research activities, scientific data sharing is essential, especially in terms of data-intensive science and scholarly communication. Scientific communities are making ongoing endeavors to promote scientific data sharing. Currently, however, data sharing is not always well-deployed throughout diverse science and engineering disciplines. Disciplinary traditions, organizational barriers, lack of technological infrastructure, and individual perceptions often contribute to limit scientists from sharing their data. Since scientists’ data sharing practices are embedded in their respective disciplinary contexts, it is necessary to examine institutional influences as well as individual motivations on scientists’ data sharing behaviors. The objective of this research is to investigate the institutional and individual factors which influence scientists’ data sharing behaviors in diverse scientific communities. Two theoretical perspectives, institutional theory and theory of planned behavior, are employed in developing a conceptual model, which shows the complementary nature of the institutional and individual factors influencing scientists’ data sharing behaviors. Institutional theory can explain the context in which individual scientists are acting; whereas the theory of planned behavior can explain the underlying motivations behind scientists’ data sharing behaviors in an institutional context. i This research uses a mixed-method approach by combining qualitative and quantitative methods: (1) interviews with the scientists in diverse scientific disciplines to understand the extent to which they share their data with other researchers and explore institutional and individual factors affecting their data sharing behaviors; and (2) survey research to examine to what extent those institutional and individual factors influence scientists’ data sharing behaviors in diverse scientific disciplines. The interview study with 25 scientists shows three groups of data sharing factors, including institutional influences (i.e. regulative pressures by funding agencies and journals and normative pressure); individual motivations (i.e. perceived benefit, risk, effort and scholarly altruism); and institutional resources (i.e. metadata and data repositories). The national survey (with 1,317 scientists in 43 disciplines) shows that regulative pressure by journals; normative pressure at a discipline level; and perceived career benefit and scholarly altruism at an individual level have significant positive relationships with data sharing behaviors; and that perceived effort has a significant negative relationship. Regulative pressure by funding agencies and the availability of data repositories at a discipline level and perceived career risk at an individual level were not found to have any significant relationships with data sharing behaviors. ii Institutional and Individual Influences on Scientists’ Data Sharing Behaviors Youngseek Kim B.A., Seoul National University, 2006 M.S., Syracuse University, 2008 Dissertation Submitted to the Graduate School of Syracuse University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Information Science and Technology June 2013 iii © Youngseek Kim, 2013 All Rights Reserved iv Acknowledgements First of all, I would like to thank all those who participated in this dissertation research, including 25 interviewees, 8 subject matter experts, 29 pretest participants, 34 pilot-test participants, and 2,470 national survey participants. This dissertation would not have been possible or completed without their support. In addition, I would like to acknowledge the CoS (Community of Scientists) Pivot for allowing me to use their scholar database in recruiting the survey participants. I wish to express my sincere gratitude to my advisor, Dr. Ping Zhang, for her support and encouragement throughout my doctoral study and this dissertation work. She always provided a prompt response and constantly encouraged me to finish this dissertation. I would also like to offer special thanks to Dr. Jeffrey Stanton for his invaluable advice and guidance in this dissertation research. His research philosophy as well as insightful feedback significantly influenced this dissertation. I am very grateful to my other committee members, Dr. Kevin Crowston, Dr. Jian Qin, Dr. Charles Driscoll, Dr. Paul Morarescu, and Dr. James Bellini, for their valuable comments and suggestions, which helped me improve the quality of my dissertation. I am also grateful to Dr. Murali Venkatesh for assisting me in understanding institutional theory, which is a critical part of the theoretical framework of this dissertation. I would like to thank my doctoral colleagues, professors, and staff members in the iSchool at Syracuse University for their care and motivation during my graduate studies. I especially would like to thank Ms. Bridget Crary for making my doctoral study and v dissertation process smoother. Additionally, I also would like to acknowledge Ms. Diane Stirling for proofreading and editing this dissertation. Finally, I wish to express my warmest and utmost gratitude to my parents, HongJin Kim and BongSoo Aeo, for their priceless and infinite love. Their recognition of the importance of education enabled me to have academic curiosity and pursue my doctoral degree. Most importantly, I would like to recognize the invaluable support and patience of my wife, HyoKyung Kwak. Her encouragement and support throughout my dissertation work allowed me to finish this dissertation and achieve my doctoral degree. vi Table of Contents Abstract ............................................................................................................................ i Acknowledgements ......................................................................................................... v List of Tables ................................................................................................................ xiii List of Figures .............................................................................................................. xvi List of Appendices ...................................................................................................... xvii 1. Problem Statement .......................................................................................................... 1 1.1. Background .............................................................................................................. 1 1.2. Motivation ................................................................................................................ 4 1.3. Definitions of Terms ................................................................................................ 8 1.4. Research Objective and Questions ......................................................................... 10 1.5. Theoretical Perspective .......................................................................................... 12 1.6. Significance of the Study ....................................................................................... 14 1.7. Summary ................................................................................................................ 17 2. Literature Review.......................................................................................................... 20 2.1. Scientists’ Norms and Values ................................................................................ 20 2.1.1. Nature of Science ............................................................................................. 20 2.1.2. Norms of Science............................................................................................. 22 2.1.3. Counter Norms ................................................................................................ 25 2.1.4. Values of Science ............................................................................................ 27 vii 2.2. Scholarly Communication ...................................................................................... 29 2.3. Data Sharing/Withholding ..................................................................................... 32 2.3.1. Prevalence of Data Sharing/Withholding ........................................................ 33 2.3.2. Factors Influencing Data Sharing/Withholding ............................................... 36 2.3.3. Consequences of Data Sharing ........................................................................ 52 2.4. Data Reuse.............................................................................................................
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