Data sharing in the sciences

Kowalczyk, Stacy; Shankar, K.

doi:10.1002/aris.2011.1440450113

Cited by 74 publications

(63 citation statements)

References 132 publications

(184 reference statements)

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“…The authors demand that a patient "needs to have the ability to think about his or her choice to participate or not and the ability to actually act on that decision". De Wolf et al [84], Harding et al [85], Mennes et al [86], Sheather [87] and Kowalczyk and Shankar [88] take the same line regarding the necessity of informed consent between researcher and study subject. Axelsson and Schroeder [63] describe the maxim to act upon public trust as an important precondition for database research.…”

Section: Ethical Normsmentioning

confidence: 99%

What Drives Academic Data Sharing?

2014

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Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher's point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.

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Section: Ethical Normsmentioning

confidence: 99%

What Drives Academic Data Sharing?

2014

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“…At the same time research is becoming a more and more collaborative exercise (Kowalczyk and Shankar 2011). There are fields where the required resources go beyond the scale of individual grants.…”

Section: Reputation Vs Collaborationmentioning

confidence: 99%

Data as Social Capital and the Gift Culture in Research

Klump¹

2017

Data Science Journal

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The value of making research data available is broadly accepted. Policies concerning the open access to research data try to implement new norms calling for researchers to make their data more openly available. These policies either appeal to the common good or focus on publication and citation as an incentive to bring about a cultural change in how researchers share their data with their peers. But when we compare the total number of publications in the fields of science, technology and medicine with the number data publications from the same time period, the number of openly available datasets is rather small. This indicates that current policies on data sharing are not effective in changing behaviours and bringing about the wanted cultural change. By looking at research communities that are more open to data sharing we can study the social patterns that influence data sharing and point us to possible points for intervention and change.

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“…It has been widely recognized that sharing research data encourages collaboration and multiple perspectives, and supports knowledge exchange between researchers working in different disciplines (Kowalczyk and Shankar 2011). However, by sharing, researchers may feel that they are relinquishing control over their data.…”

Section: Literature Reviewmentioning

confidence: 99%

Data sharing practices, information exchange behaviors, and knowledge discovery dynamics: a study of natural resources and environmental scientists

Shen

2017

Environ Syst Res

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Background: This paper presents a deep-dive examination of the cross-boundary data practices of natural resources and environmental scientists in the context of Virginia Tech's institutional visioning and strategic development efforts. The goal is to understand scientists' actual data information behaviors, their communication and exchange dynamics, and their knowledge discovery mechanisms for effective and productive data sharing and reuse. A focus group and multiple individual interviews were conducted using critical incident, story telling, and scenario building techniques. Results:The results reveal the subtle importance of interpersonal communication and interactive discussion in deciphering nuances, discovering novelty, and revealing insights in data, all of which enable productive exchange and effective reuse. In the new transformative and disruptive research environments, novel discoveries are catalyzed by scientific knowledge, driven and inspired by research curiosity and creativity, and enabled by unique and rich data collections. Conclusions:As such, an integrated view of social and technical factors must be figured into the holistic design of data repository, discovery, and learning system. Libraries have significant roles to play to advance both social and technical infrastructures of a research data ecosystem in a strategic, targeted, and synchronized fashion.

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Data sharing in the sciences

Cited by 74 publications

References 132 publications

What Drives Academic Data Sharing?

What Drives Academic Data Sharing?

Data as Social Capital and the Gift Culture in Research

Data sharing practices, information exchange behaviors, and knowledge discovery dynamics: a study of natural resources and environmental scientists

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