Data reusers' trust development

Abstract

Data reuse refers to the secondary use of data—not for its original purpose but for studying new problems. Although reusing data might not yet be the norm in every discipline, the benefits of reusing shared data have been asserted by a number of researchers, and data reuse has been a major concern in many disciplines. Assessing data for trustworthiness becomes important in data reuse with the growth in data creation because of the lack of standards for ensuring data quality and potential harm from using poor‐quality data. This research explores many facets of data reusers' trust in data generated by other researchers focusing on the trust judgment process with influential factors that determine reusers' trust. The author took an interpretive qualitative approach by using in‐depth semistructured interviews as the primary research method. The study results suggest different stages of trust development associated with the process of data reuse. Data reusers' trust may remain the same throughout their experiences, but it can also be formed, lost, declined, and recovered during their data reuse experiences. These various stages reflect the dynamic nature of trust.

Social scientists' data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories

“…Several recent studies have investigated data reuse practices and behaviors in the social sciences (Daniels, Faniel, Fear, & Yakel, 2012;Faniel, Kriesberg, & Yakel, 2012;Faniel, Kriesberg, & Yakel, 2016;Niu, 2009;Yoon, 2014bYoon, , 2016Yoon, , 2017 as part of a broader drive to understand data practices within the social sciences. While these studies have captured some of the contexts and characteristics of social science data reuse by focusing on specific aspects of data reuse practices, which may overlap with other disciplinary contexts, fewer studies have used theoretical approaches or models to explain social scientists' data reuse behaviors.…”

“…Reusers assess data for a good fit for the purpose of their study (Faniel, Kansa, Kansa, Barrera-Gomez, & Yakel, 2013), for data quality (Cragin & Shankar, 2006;Van House, 2002), or generally for reusability (Faniel & Jacobsen, 2010). Social scientists are also concerned with choosing good quality, trustworthy data and avoiding data with errors (Yoon, 2014a(Yoon, , 2016(Yoon, , 2017. Assessing data for each of these qualities requires different criteria; some important assessment factors which have been identified include data producers' ability to generate trustworthy data, other reusers' positive experiences using the data, and soundness of methodology used to produce data (Faniel & Jacobsen, 2010;Faniel, Kansa, Kansa, Barrera-Gomez, & Yakel, 2013;Yoon, 2017;Zimmerman, 2008).…”

“…Data reusers often search for additional information when documentation is insufficient, consulting various sources, including data producers and experts (Birnholtz & Bietz, 2003;Bishop, 2009;Faniel et al, 2013;Markus, 2001;McCall & Appelbaum, 1991). Yoon (2017) found that social science data reusers also sought external help from data reuser groups, repository staff, and data producers when they encountered problems. Faniel, Kriesberg, and Yakel (2012) reported that human scaffolding, particularly the use of faculty advisors, was an effective technique for novice social science data reusers to manage complex issues that arose during data reuse.…”

“…Yoon, Y. Kim Library and Information Science Research 39 (2017) 224-233 disciplines, only a few studies try to explain or understand data reusers' behaviors from theoretical perspectives or using a theoretical model (e.g., Yoon, 2017). This study develops an integrated theoretical framework to explore social scientists' data reuse behaviors.…”

Role of communication in data reuse

“…Because data reusers build their work on other researchers' findings, the process of data reuse involves these interactions and communications with other relevant parties. Most commonly, previous research has found that data reusers contact data producers (the original investigators of the project in which the data for reuse were created) with questions (Niu, 2009;Yoon, 2016aYoon, , 2017. Sometimes mentors have been involved in locating and understanding data (Kriesberg, Frank, Faniel, & Yakel, 2013;Rolland & Lee, 2013).…”