A study of the roles of metadata standard and data repository in science, technology, engineering and mathematics researchers' data reuse

PurposeThis research investigates how the availabilities of both metadata standards and data repositories influence researchers' data reuse intentions either directly or indirectly as mediated by the norms of data reuse and their attitudes toward data reuse.Design/methodology/approachThe theory of planned behavior (TPB) was employed to develop the research model of researchers' data reuse intentions, focusing on the roles of metadata standards, data repositories and norms of data reuse. The proposed research model was evaluated using the structural equation modeling (SEM) method based on the survey responses received from 811 STEM (science, technology, engineering and mathematics) researchers in the United States.FindingsThis research found that the availabilities of both metadata standards and data repositories significantly affect STEM researchers' norm of data reuse, which influences their data reuse intentions as mediated by their attitudes toward data reuse. This research also found that both the availability of data repositories and the norm of data reuse have a direct influence on data reuse intentions and that norm of data reuse significantly increases the effect of attitude toward data reuse on data reuse intention as a moderator.Research limitations/implicationsThe modified model of TPB provides a new perspective in apprehending the roles of resource facilitating conditions such as the availabilities of metadata standards and data repositories in an individual's attitude, norm and their behavioral intention to conduct a certain behavior.Practical implicationsThis study suggests that scientific communities need to develop more supportive metadata standards and data repositories by considering their roles in enhancing the community norm of data reuse, which eventually lead to data reuse behaviors.Originality/valueThis study sheds light on the mechanism of metadata standard and data repository in researchers' data reuse behaviors through their community norm of data reuse; this can help scientific communities and academic institutions to better support researchers in their data sharing and reuse behaviors.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0431

[1]  Jordan M. Malof,et al.  Distributed solar photovoltaic array location and extent dataset for remote sensing object identification , 2016, Scientific Data.

[2]  Youngseek Kim,et al.  Internet researchers' data sharing behaviors: An integration of data reuse experience, attitudinal beliefs, social norms, and resource factors , 2018, Online Inf. Rev..

[3]  Youngseek Kim,et al.  Norms of data sharing in biological sciences: The roles of metadata, data repository, and journal and funding requirements , 2016, J. Inf. Sci..

[4]  Bradley M. Hemminger,et al.  Scientific data repositories on the Web: An initial survey , 2010, J. Assoc. Inf. Sci. Technol..

[5]  Jinfang Niu,et al.  Documentation evaluation model for social science data , 2008, ASIST.

[6]  Bradley M. Hemminger,et al.  Scientific data repositories on the Web: An initial survey , 2010 .

[7]  Carmen de Pablos Heredero,et al.  The process of open data publication and reuse , 2018, J. Assoc. Inf. Sci. Technol..

[8]  Melissa H. Cragin,et al.  Scientific Data Collections and Distributed Collective Practice , 2006, Computer Supported Cooperative Work (CSCW).

[9]  Christine L. Borgman,et al.  On the Reuse of Scientific Data , 2017, Data Sci. J..

[10]  Michael Witt,et al.  Data sharing, small science and institutional repositories , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[11]  Christopher W. Belter,et al.  Data sharing in PLOS ONE: An analysis of Data Availability Statements , 2018, PloS one.

[12]  Elizabeth Yakel,et al.  Data reuse and sensemaking among novice social scientists , 2012, ASIST.

[13]  Cecelia M. Brown.  The changing face of scientific discourse: Analysis of genomic and proteomic database usage and acceptance , 2003, J. Assoc. Inf. Sci. Technol..

[14]  Elizabeth Yakel,et al.  Trust in Digital Repositories , 2013, Int. J. Digit. Curation.

[15]  Rajiv N. Rimal,et al.  An Explication of Social Norms , 2005 .

[16]  Ayoung Yoon,et al.  Data reusers' trust development , 2017, J. Assoc. Inf. Sci. Technol..

[17]  Wynne W. Chin.  The partial least squares approach for structural equation modeling. , 1998 .

[18]  T. Ramayah,et al.  An Empirical Inquiry on Knowledge Sharing Among Academicians in Higher Learning Institutions , 2013 .

[19]  Ixchel M. Faniel,et al.  Reusing Scientific Data: How Earthquake Engineering Researchers Assess the Reusability of Colleagues’ Data , 2010, Computer Supported Cooperative Work (CSCW).

[20]  Hichang Cho,et al.  Testing an integrative theoretical model of knowledge-sharing behavior in the context of Wikipedia , 2010 .

[21]  Charlotte P. Lee,et al.  Synergizing in Cyberinfrastructure Development , 2010, Computer Supported Cooperative Work (CSCW).

[22]  Wonsuck Kim,et al.  Data management, sharing, and reuse in experimental geomorphology: Challenges, strategies, and scientific opportunities , 2015 .

[23]  Kevin Crowston,et al.  Attitudes and norms affecting scientists’ data reuse , 2017, PloS one.

[24]  Paul T. Groth,et al.  FAIR Data Reuse – the Path through Data Citation , 2020, Data Intelligence.

[25]  Lynn Yarmey,et al.  Data Stewardship: Environmental Data Curation and a Web-of-Repositories , 2009, Int. J. Digit. Curation.

[26]  Narasimha Bolloju,et al.  Explaining the intentions to share and reuse knowledge in the context of IT service operations , 2005, J. Knowl. Manag..

[27]  M StantonJeffrey,et al.  Institutional and individual factors affecting scientists' data-sharing behaviors , 2016 .

[28]  Paul F. Uhlir.  Information Gulags, Intellectual Straightjackets, and Memory Holes , 2010, Data Sci. J..

[29]  Kristin R. Eschenfelder,et al.  The Limits of sharing: Controlled data collections , 2011, ASIST.

[30]  Christine Fennema-Notestine,et al.  Enabling public data sharing: encouraging scientific discovery and education. , 2009, Methods in molecular biology.

[31]  Abdollah Homaifar,et al.  Detecting Environmental Change Using Self-Organizing Map Techniques Applied to the ERA-40 Database , 2011, Data Sci. J..

[32]  G. Zsidisin,et al.  An institutional theory perspective of business continuity planning for purchasing and supply management , 2005 .

[33]  Elizabeth Yakel,et al.  The challenges of digging data: a study of context in archaeological data reuse , 2013, JCDL '13.

[34]  Ruben C. Arslan.  How to Automatically Document Data With the codebook Package to Facilitate Data Reuse , 2019, Advances in Methods and Practices in Psychological Science.

[35]  Youngseek Kim,et al.  Institutional and individual factors affecting scientists' data‐sharing behaviors: A multilevel analysis , 2016, J. Assoc. Inf. Sci. Technol..

[36]  I. Ajzen.  The theory of planned behavior , 1991 .

[37]  Ping Zhang,et al.  Understanding data sharing behaviors of STEM researchers: The roles of attitudes, norms, and data repositories , 2015 .

[38]  Hichang Cho,et al.  Testing an integrative theoretical model of knowledge-sharing behavior in the context of Wikipedia , 2010, J. Assoc. Inf. Sci. Technol..

[39]  Libby Bishop,et al.  Ethical Sharing and Reuse of Qualitative Data , 2009 .

[40]  Elizabeth D. Dalton,et al.  Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide , 2015, PloS one.

[41]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[42]  Ann Zimmerman,et al.  Not by metadata alone: the use of diverse forms of knowledge to locate data for reuse , 2007, International Journal on Digital Libraries.

[43]  Peter McKinney,et al.  The world is all grown digital.... How shall a man persuade management what to do in such times? , 2007, Int. J. Digit. Curation.

[44]  Ayoung Yoon,et al.  Social scientists' data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories , 2017 .

[45]  Ayoung Yoon,et al.  Factors of trust in data reuse , 2019, Online Inf. Rev..

[46]  Christine L Borgman,et al.  Science friction: Data, metadata, and collaboration , 2011, Social studies of science.

[47]  Elizabeth Yakel,et al.  Social scientists' satisfaction with data reuse , 2016, J. Assoc. Inf. Sci. Technol..

[48]  I. Ajzen.  Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. , 2002 .

[49]  David Ribes,et al.  Sociotechnical Studies of Cyberinfrastructure and e-Research: Current Themes and Future Trajectories , 2010, Computer Supported Cooperative Work (CSCW).

[50]  Chao-Min Chiu,et al.  Predicting electronic service continuance with a decomposed theory of planned behaviour , 2004, Behav. Inf. Technol..

[51]  Suzie Allard,et al.  Data sharing, management, use, and reuse: Practices and perceptions of scientists worldwide , 2020, PloS one.

[52]  Erik Schultes,et al.  The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.

[53]  Ann Zimmerman,et al.  New Knowledge from Old Data , 2008 .

[54]  Andrew C. Simpson,et al.  Collaboration and Trust in Healthcare Innovation: The eDiaMoND Case Study , 2005, Computer Supported Cooperative Work (CSCW).

[55]  Helena Karasti,et al.  Digital Data Practices and the Long Term Ecological Research Program Growing Global , 2008, Int. J. Digit. Curation.

[56]  Ayoung Yoon,et al.  Scientists' data reuse behaviors: A multilevel analysis , 2017, J. Assoc. Inf. Sci. Technol..

[57]  Nicole A. Vasilevsky,et al.  Reproducible and reusable research: are journal data sharing policies meeting the mark? , 2017, PeerJ.