Developing the tasks-toward-transparency (T3) model for research transparency in open science using the lifecycle as a grounding framework

Abstract An increasingly data-intensive research environment has highlighted the need for greater research transparency to facilitate integrity and trust in open science and in the conduct of research more widely. The initial findings of faculty researchers' behaviors and practices toward research transparency, using the research data lifecycle as a grounding framework are reported. Four focus group sessions were conducted with faculty researchers in different disciplines, including natural sciences, social sciences, engineering, and different transparency practices were captured using the researchers' own language. Four generic transparency components were identified: action verb, object, task, and stage in the research lifecycle. The inter-relationships between specific transparency components were visualized using network visualizations. The network visualizations suggest that the lifecycle stages of Process/Visualize/Analyze and Publish/Preserve/Archive are key points for transparency, where ‘data’ play a critical role demonstrated by the multiple node-edge relationships. Based on the findings, a conceptual model, termed the Tasks-Toward-Transparency (T3) Model, was developed. This model may inform researcher practices and support research stakeholders whose role is to articulate and deliver transparency advocacy, policy, training programs, and services.

[1]  Xiao Hu,et al.  Creating a knowledge map for the Research Lifecycle , 2014 .

[2]  Sarah The Lifecycle of Data Management , 2012 .

[3]  Susann Fiedler,et al.  Badges to Acknowledge Open Practices: A Simple, Low-Cost, Effective Method for Increasing Transparency , 2016, PLoS biology.

[4]  Richard A. Krueger,et al.  Focus groups : a practical guide for applied research / by Richard A. Krueger , 1989 .

[5]  Marc Ortegren,et al.  Gender Differences in Ethics Research: The Importance of Controlling for the Social Desirability Response Bias , 2011 .

[6]  C. Glenton,et al.  What about N? A methodological study of sample-size reporting in focus group studies , 2011, BMC medical research methodology.

[7]  Ben Jann,et al.  Plagiarism in Student Papers: Prevalence Estimates Using Special Techniques for Sensitive Questions , 2011 .

[8]  J. Fox,et al.  The uncertain relationship between transparency and accountability , 2007 .

[9]  Sarah Higgins The DCC Curation Lifecycle Model , 2008, Int. J. Digit. Curation.

[10]  Wei Jeng,et al.  Transparency : A Preliminary Study of Disciplinary Conceptualisation , Drivers , Tools and Support Services , 2017 .

[11]  Liz Lyon eBank UK: Building the Links Between Research Data, Scholarly Communication and Learning , 2003 .

[12]  Earl R. Babbie,et al.  The Basics Of Social Research , 1998 .

[13]  S. Vaughn,et al.  Focus Group Interviews in Education and Psychology , 1996 .

[14]  A. H. Ball,et al.  Review of Data Management Lifecycle Models , 2012 .

[15]  Liz Lyon,et al.  Transparency: the emerging third dimension of Open Science and Open Data , 2016 .

[16]  David Moher,et al.  Promote scientific integrity via journal peer review data , 2017, Science.

[17]  Brian A. Nosek,et al.  Promoting an open research culture , 2015, Science.

[18]  Ben Shneiderman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction , 1998 .

[19]  John P. A. Ioannidis,et al.  A manifesto for reproducible science , 2017, Nature Human Behaviour.

[20]  Peter Fox,et al.  Is Data Publication the Right Metaphor? , 2013, Data Sci. J..

[21]  D L Morgan,et al.  Practical Strategies for Combining Qualitative and Quantitative Methods: Applications to Health Research , 1998, Qualitative health research.

[22]  Elizabeth R. Peterson,et al.  How to Get Focus Groups Talking: New Ideas that will Stick , 2007 .