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Foundational studies for measuring the impact, prevalence, and patterns of publicly sharing biomedical research data

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Foundational studies for measuring the impact, prevalence, and patterns of publicly sharing biomedical research data
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  FOUNDATIONAL STUDIES FOR MEASURINGTHE IMPACT, PREVALENCE, AND PATTERNSOF PUBLICLY SHARING BIOMEDICAL RESEARCH DATA by Heather Alyce Piwowar   Bachelor of Science in Electrical Engineering and Computer Science, MIT, 1995Master of Engineering in Electrical Engineering and Computer Science, MIT, 1996Master of Science in Biomedical Informatics, University of Pittsburgh, 2006Submitted to the Graduate Faculty of the School of Medicine in partial fulfillmentof the requirements for the degree of Doctor of PhilosophyUniversity of Pittsburgh2010   UNIVERSITY OF PITTSBURGHSCHOOL OF MEDICINEThis dissertation was presentedbyHeather Alyce Piwowar It was defended onMarch 24, 2010and approved byBrian B. Butler, PhD, Associate Professor,Katz Graduate School of Business, University of PittsburghEllen G. Detlefsen, PhD, Associate Professor,School of Information Sciences, University of PittsburghGunther Eysenbach, MD, MPH, Associate Professor,Department of Health Policy, Management and Evaluation, University of TorontoMadhavi Ganapathiraju, PhD, Assistant Professor,Department of Biomedical Informatics, University of PittsburghDissertation Advisor: Wendy W. Chapman, PhD, Assistant Professor,Department of Biomedical Informatics, University of Pittsburgh ii  iii   FOUNDATIONAL STUDIES FOR MEASURINGTHE IMPACT, PREVALENCE, AND PATTERNSOF PUBLICLY SHARING BIOMEDICAL RESEARCH DATA Heather A. Piwowar, PhDUniversity of Pittsburgh, 2010Many initiatives encourage research investigators to share their raw research datasetsin hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp on the prevalence or patterns of datasharing and reuse. Previous survey methods for understanding data sharing patternsprovide insight into investigator attitudes, but do not facilitate direct measurement of data sharing behaviour or its correlates. In this study, we evaluate and use bibliometricmethods to understand the impact, prevalence, and patterns with which investigatorspublicly share their raw gene expression microarray datasets after study publication.To begin, we analyzed the citation history of 85 clinical trials published between1999 and 2003. Almost half of the trials had shared their microarray data publicly onthe internet. Publicly available data was significantly (p=0.006) associated with a 69%increase in citations, independently of journal impact factor, date of publication, andauthor country of srcin.Digging deeper into data sharing patterns required methods for automaticallyidentifying data creation and data sharing. We derived a full-text query to identifystudies that generated gene expression microarray data. Issuing the query in PubMedCentral ® , Highwire Press, and Google Scholar found 56% of the data-creation studiesin our gold standard, with 90% precision. Next, we established that searching ArrayExpress and the Gene Expression Omnibus databases for PubMed ® articleidentifiers retrieved 77% of associated publicly-accessible datasets.We used these methods to identify 11603 publications that created geneexpression microarray data. Authors of at least 25% of these publications depositedtheir data in the predominant public databases. We collected a wide set of variablesabout these studies and derived 15 factors that describe their authorship, funding,  iv institution, publication, and domain environments. In second-order analysis, authorswith a history of sharing and reusing shared gene expression microarray data weremost likely to share their data, and those studying human subjects and cancer wereleast likely to share.We hope these methods and results will contribute to a deeper understanding of data sharing behavior and eventually more effective data sharing initiatives.  v TABLE OF CONTENTSPREFACE ....................................................................................................................... X   1.0   INTRODUCTION .................................................................................................... 1   1.1   BACKGROUND .............................................................................................. 2   1.1.1The potential benefits of data sharing ................................................... 4   1.1.2Current data sharing practice: forces in support .................................. 4   1.1.3   Current data sharing practice: forces in opposition .............................. 6   1.2   PREVIOUS RESEARCH ON DATA SHARING BEHAVIOR .......................... 7   1.2.1Measuring and modeling data sharing behavior ................................... 8   1.2.2Measuring and modeling data sharing attitudes and intentions ............ 8   1.2.3Identifying instances of data sharing ..................................................... 9   1.2.4Evaluating the impact of data sharing policies .................................... 10   1.2.5Estimating the costs and benefits of data sharing ............................... 10   1.2.6   Related research fields ....................................................................... 11   1.3   RESEARCH DESIGN AND METHODS ........................................................ 11   1.3.1 Aim 1: Does sharing have benefit for those who share? ..................... 11   1.3.2Aim 2: Can sharing and withholding be systematically measured? .... 12   1.3.3    Aim 3: How often is data shared? What predicts sharing?How can we model sharing behavior? ................................................ 12   1.4   RELATED RESEARCH APPLICATIONS OF METHODS ............................ 12   1.4.1Citation analysis for adoption and impact of open science ................. 12   1.4.2Natural language processing of the biomedical literature ................... 13   1.4.3   Regression and factor analysis for deriving and evaluating modelsof sharing behavior ............................................................................. 14   1.5   OUTLINE OF THE DISSERTATION ............................................................. 14  
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