Youngseek Kim

Norms of data sharing in biological sciences

Institutional environments, comprising regulative pressures by funding agencies and journal publishers, and institutional resources, including the availabilities of data repositories and standards for metadata, function as important determinants in scientists’ data-sharing norms, attitudes and behaviours. This research investigates how these functions influence biological scientists’ data-sharing norms and how the data-sharing norms influence their data-sharing behaviours mediated by attitudes towards data sharing. The research model was developed based on the integration of institutional theory and theory of planned behaviour. The proposed research model was validated based on a total of 608 responses from a national survey conducted in the USA. The Partial Least Squares (PLS) was employed to analyse the survey data. Results show how institutional pressures by funding agencies and journals and the availabilities of data repository and metadata standards all have significant influences on data-sharing norms, which have significant influences on data-sharing behaviours, as mediated by attitudes towards data sharing.

Fostering scientists data sharing behaviors via data repositories, journal supplements, and personal communication methods

The purpose of this study is to examine how institutional pressures, individual motivations, and resources all affect scientists diverse data sharing behaviors, including (a) making data accessible through data repositories, (b) submitting data as journal supplements, and (c) providing data via personal communication methods upon request. A combined theoretical framework integrating institutional theory and theory of planned behavior was used to create a research model which presents how scientists make the decision to share data in diverse ways, and how the data sharing factors differ across diverse data sharing behaviors. A survey method was employed to evaluate the research model by using multivariate regression analysis technique with a total of 2172 survey responses in the U.S. The results of this research show the dynamic relationships between diverse data sharing factors and different forms of data sharing behaviors. For data sharing via data repository, journal pressure, perceived effort, and availability of data repositories are significant factors; for data sharing through journal supplement, journal pressure, perceived career benefit, perceived effort, and availability of data repository are significant factors; for personal data sharing, funding agency pressure, normative pressure, perceived career risk, perceived effort, and availability of data repositories are significant factors. This research suggests that funding agencies, journal publishers, and scientific communities that different strategies need to be employed to promote different forms of data sharing behaviors.

Attitudinal, normative, and resource factors affecting psychologists’ intentions to adopt an open data badge: An empirical analysis

Abstract The purpose of this research is to investigate the attitudinal, normative, and resource factors affecting psychologists’ adoption of an open data badge. The theory of planned behavior was employed to demonstrate how these factors influence behavioral intentions to adopt an open data badge. This research used a survey method to examine to what extent those attitudinal, normative, resource factors influence psychologists’ behavioral intentions to adopt an open data badge, and therefore engage in data sharing behaviors. A national survey (n = 341) across the field of psychology showed that perceived benefit and perceived risk had significant positive and negative relationships with attitude toward the open data badge respectively. Furthermore, attitude toward open data badge and norm of data sharing had significant positive influences on psychologists’ behavioral intentions to adopt the open data badge. Perceived effort had a significant negative relationship with the behavioral intention to adopt the open data badge, but had no effect toward attitudes surrounding the badge. However, this research found that the availability of a data repository and pressure from an open science journal did not have any significant relationship with behavioral intention to adopt the open data badge. The discussion includes implications for psychologists from both practical and theoretical perspectives. Additionally, future directions for gauging psychologists’ adoption of the open data badge and increasing data sharing behaviors are discussed.

An exploratory study of health scientists’ data reuse behaviors: Examining attitudinal, social, and resource factors

Purpose The purpose of this paper is to examine how health scientists’ attitudinal, social, and resource factors affect their data reuse behaviors. Design/methodology/approach A survey method was utilized to investigate to what extent attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. The health scientists’ data reuse research model was validated by using partial least squares (PLS) based structural equation modeling technique with a total of 161 health scientists in the USA. Findings The analysis results showed that health scientists’ data reuse intentions are driven by attitude toward data reuse, community norm of data reuse, disciplinary research climate, and organizational support factors. This research also found that both perceived usefulness of data reuse and perceived concern involved in data reuse have significant influences on health scientists’ attitude toward data reuse. Research limitations/implications This research evaluated its newly proposed research model based on the theory of planned behavior using a sample from the community of scientists’ scholar database. This research showed an overall picture of how attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. This research is limited due to its sample size and low response rate, so this study is considered as an exploratory study rather than a confirmatory study. Practical implications This research suggested for health science research communities, academic institutions, and libraries that diverse strategies need to be utilized to promote health scientists’ data reuse behaviors. Originality/value This research is one of initial studies in scientific data reuse which provided a holistic map about health scientists’ data sharing behaviors. The findings of this study provide the groundwork for strategies to facilitate data reuse practice in health science areas.

Engineering researchers’ data reuse behaviours: a structural equation modelling approach

Purpose The purpose of this research is to investigate the factors that influence engineering researchers’ data reuse behaviours. Design/methodology/approach The data reuse behaviour model of engineering researchers was investigated by using a survey method. A national survey was distributed to engineering researchers in the USA, and a total of 193 researchers responded. Findings The results showed that perceived usefulness, perceived concerns and norms of data reuse have significant relationships with attitudes toward data reuse. Also, attitudes toward data reuse and the availability of data repositories were found to have significant influences on engineering researchers’ intention to reuse data. Research limitations/implications This research used a combined theoretical framework by integrating the theory of planned behaviour (TPB) and the technology acceptance model (TAM). The combination of the TPB and the TAM effectively explained engineering researchers’ data reuse behaviours by addressing individual motivations, norms and resource factors. Practical implications This research has practical implications for promoting more reliable and beneficial data reuse in the engineering community, including encouraging positive motivations toward data reuse, building community norms of data reuse and setting up more data repositories. Originality value As prior research on data reuse mainly used interviews, this research used a quantitative approach based on a combined theoretical framework and included diverse research constructs which were not tested in the previous research models. As one of the initial studies investigating data reuse behaviours in the engineering community, the current research provided a better understanding of data reuse behaviours and suggested possible ways to facilitate engineering researchers’ data reuse behaviours.