Reusing Scientific Data: How Earthquake Engineering Researchers Assess the Reusability of Colleagues’ Data

Abstract

Investments in cyberinfrastructure and e-Science initiatives are motivated by the desire to accelerate scientific discovery. Always viewed as a foundation of science, data sharing is appropriately seen as critical to the success of such initiatives, but new technologies supporting increasingly data-intensive and collaborative science raise significant challenges and opportunities.

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

“…Discovering relevant data may be challenging for scientists across disciplines (e.g., Faniel & Jacobsen, 2010;Zimmerman, 2008), but it is especially difficult for social scientists because data are distributed among various sources and systems (Yoon, 2015). Easy access to data was one of the most influential factors in determining social scientists' satisfaction with data reuse (Faniel, Kriesberg, & Yakel, 2016).…”

“…Data reusers need to assess data before reusing it because they are usually unfamiliar with the details of the data. 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.…”

“…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 repositories can reduce perceived effort, enhance positive attitudes, and influence the actual behaviors of social scientists regarding data reuse. In the social science context, data repositories play an important role in data sharing and reuse, although data reuse also still occurs through personto-person exchange and interaction (e.g., Faniel & Jacobsen, 2010;Yoon, 2014a). Social science data repositories contribute to data reuse, not just through easy access to data, but also by providing value-added services which ensure current and future use of that data, such as managing provenance, correcting errors, and providing supporting documentation, all of which reduce the effort expectancy required for data reuse (Daniels et al, 2012;Fear & Donaldson, 2012).…”

“…This study reinforces the importance of data repositories in the data reuse landscape and calls for their more active involvement in data reuse. Despite the work of data repositories in data sharing and reuse, many researchers still reported some common difficulties in reusing data, including: not all data being deposited in repositories, issues with documentation, and even not knowing how to search data (Faniel & Jacobsen, 2010;Sands, Borgman, Wynholds, & Traweek, 2012). While some repositories, like ICPSR, are well known across different social science fields, other repositories may need to reach out to research communities to broadcast their services and datasets.…”