Social scientists’ data sharing behaviors: Investigating the roles of individual motivations, institutional pressures, and data repositories

Kim, Youngseek; Adler, Melissa

doi:10.1016/j.ijinfomgt.2015.04.007

Cited by 76 publications

(115 citation statements)

References 83 publications

(77 reference statements)

Supporting

Mentioning

104

Contrasting

Unclassified

Order By: Relevance

“…A similar expansion can be observed in Genomics or Astronomy (Borgman, 2012). On the other hand, social sciences and the humanities have thus adopted these new practices at a slower pace than STEM fields (Doorn, Dillo, & van Horik, 2013;Kim & Adler, 2015).…”

Section: Introductionmentioning

confidence: 62%

DataCite as a novel bibliometric source: Coverage, strengths and limitations

Robinson-García

Mongeon

Jeng

et al. 2017

Journal of Informetrics

View full text Add to dashboard Cite

This paper explores the characteristics of DataCite to determine its possibilities and potential as a new bibliometric data source to analyze the scholarly production of open data. Open science and the increasing data sharing requirements from governments, funding bodies, institutions and scientific journals has led to a pressing demand for the development of data metrics. As a very first step towards reliable data metrics, we need to better comprehend the limitations and caveats of the information provided by sources of open data. In this paper, we critically examine records downloaded from the DataCite's OAI API and elaborate a series of recommendations regarding the use of this source for bibliometric analyses of open data. We highlight issues related to metadata incompleteness, lack of standardization, and ambiguous definitions of several fields. Despite these limitations, we emphasize DataCite's value and potential to become one of the main sources for data metrics development.

show abstract

Section: Introductionmentioning

confidence: 62%

DataCite as a novel bibliometric source: Coverage, strengths and limitations

Robinson-García

Mongeon

Jeng

et al. 2017

Journal of Informetrics

View full text Add to dashboard Cite

show abstract

“…Previously, the reward system in science was associated with the publication of research as a scholarly communication practice, but it could be extended to the publication of research data as well (Borgman, ). Prior studies in data sharing found that perceived career benefits of data sharing positively increased the overall attitude toward data sharing and the norm of data sharing (Kim & Adler, ; Kim & Zhang, ). Therefore, this research hypothesizes:…”

Section: Research Model and Hypothesis Developmentmentioning

confidence: 99%

Reputation, trust, and norms as mechanisms leading to academic reciprocity in data sharing: An empirical test of theory of collective action

Kim

2018

Proc. Assoc. Info. Sci. Tech.

Self Cite

View full text Add to dashboard Cite

This research investigated how scientists' academic reputation, community trust, and norms regarding data sharing all influence their academic reciprocity in data sharing, which eventually leads to the scientists' data sharing intentions. This research employed Ostrom's (2003) theory of collective action to better understand scientists' data sharing behaviors from the perspective of cooperation in a community. This research empirically evaluated the research model and related hypotheses by using the Structural Equation Modeling (SEM) method on a total of 456 survey responses from biologists in the U.S. The results suggest that biologists' perceived academic reputation significantly increases their perceived community trust, norm of data sharing, and academic reciprocity. Along with perceived academic reputation, both perceived community trust and norms of data sharing also significantly increases biologists' academic reciprocity in data sharing. This research also found that biologists' academic reciprocity and norms of data sharing significantly affect their data sharing intentions. The results of this research show that the theory of collective action provides new insight to scientists' data sharing behaviors. These results suggest how we can facilitate scientists' data sharing behaviors within a research community by increasing academic reciprocity through the mechanisms of reputation, trust, and norm.

show abstract

“…While there are needs for a common (spatial) data repository for data and document exchange from a researchers and research center perspective, there have been recently strong voices for opening up research data (Michener, 2015;Kim andAdler, 2015, Welle Donker et al, 2016) and procedures (e.g., Morin et al, 2012;Rey, 2014;Singleton et al, 2016) due to a series of publications that falsified and fudged data. For instance, the journal Nature has put in place new rules that require authors "to include information on whether and how others can access the underlying data" (Nature Editorial, 2016).…”

Section: Introduction -Need and Good Will (At Least For Now)mentioning

confidence: 99%

BUILDING A GEOGRAPHIC DATA REPOSITORY FOR URBAN RESEARCH WITH FREE SOFTWARE – LEARNING FROM Observatorio.CEDEUS.cl

Steiniger

Fuente

Fuentes

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:The recent trend towards open data and open science as well as a demand for holistic and interdisciplinary research requires platforms that allow the distribution and exchange of research data, including geographic information. While the requirements and benefits of data exchange are widely discussed, there are few proposals on how to implement data platforms that not only permit the exchange of research data among researchers, but also permit to distribute research results and data to the interest public. We elaborate what points are important for implementing a (geographic) data repository and propose then to adopt the concept of Spatial Data Infrastructures (SDI) as a solution for the implementation of research data repositories. We present as a case study the geographic data and document repository of the Chilean research Centre on Sustainable Urban Development (CEDEUS), the CEDEUS Observatory. Besides the infrastructure to host and distribute data, communication tools are an important component of such a data repository service. For this case study we analyse which things have worked well and which things have not worked well based on the experiences collected during three years of operation. We close with some recommendations for the implementation of data repositories for research.

show abstract

Social scientists’ data sharing behaviors: Investigating the roles of individual motivations, institutional pressures, and data repositories

Cited by 76 publications

References 83 publications

DataCite as a novel bibliometric source: Coverage, strengths and limitations

DataCite as a novel bibliometric source: Coverage, strengths and limitations

Reputation, trust, and norms as mechanisms leading to academic reciprocity in data sharing: An empirical test of theory of collective action

BUILDING A GEOGRAPHIC DATA REPOSITORY FOR URBAN RESEARCH WITH FREE SOFTWARE – LEARNING FROM Observatorio.CEDEUS.cl

Contact Info

Product

Resources

About