Data Sharing in Biomedical Sciences: A Systematic Review of Incentives

Devriendt, Thijs; Shabani, Mahsa; Borry, Pascal

doi:10.1089/bio.2020.0037

Cited by 24 publications

(19 citation statements)

References 41 publications

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“…The findings convey the impression that when prizes such as cash money, national recognition, or awards are offered as an appreciation for their involvement, government agencies appear to be more driven to OGD. The same sentiment was expressed by Devriendt, et al [109] and Elixmann and Jarke [83], who suggested that the data owners were discouraged from sharing their data due to limited rewards. A study by Zhang, et al [110] further underlined the importance of incentives, claiming that rewards for government officials may help to reduce resistance to OGD.…”

Section: Incentivesmentioning

confidence: 67%

Factors influencing open government data post-adoption in the public sector: The perspective of data providers

Mustapa

Hamid²,

Nasaruddin³

2022

PLoS ONE

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Providing access to non-confidential government data to the public is one of the initiatives adopted by many governments today to embrace government transparency practices. The initiative of publishing non-confidential government data for the public to use and re-use without restrictions is known as Open Government Data (OGD). Nevertheless, after several years after its inception, the direction of OGD implementation remains uncertain. The extant literature on OGD adoption concentrates primarily on identifying factors influencing adoption decisions. Yet, studies on the underlying factors influencing OGD after the adoption phase are scarce. Based on these issues, this study investigated the post-adoption of OGD in the public sector, particularly the data provider agencies. The OGD post-adoption framework is crafted by anchoring the Technology–Organization–Environment (TOE) framework and the innovation adoption process theory. The data was collected from 266 government agencies in the Malaysian public sector. This study employed the partial least square-structural equation modeling as the statistical technique for factor analysis. The results indicate that two factors from the organizational context (top management support, organizational culture) and two from the technological context (complexity, relative advantage) have a significant contribution to the post-adoption of OGD in the public sector. The contribution of this study is threefold: theoretical, conceptual, and practical. This study contributed theoretically by introducing the post-adoption framework of OGD that comprises the acceptance, routinization, and infusion stages. As the majority of OGD adoption studies conclude their analysis at the adoption (decisions) phase, this study gives novel insight to extend the analysis into unexplored territory, specifically the post-adoption phase. Conceptually, this study presents two new factors in the environmental context to be explored in the OGD adoption study, namely, the data demand and incentives. The fact that data providers are not influenced by data requests from the agency’s external environment and incentive offerings is something that needs further investigation. In practicality, the findings of this study are anticipated to assist policymakers in strategizing for long-term OGD implementation from the data provider’s perspective. This effort is crucial to ensure that the OGD initiatives will be incorporated into the public sector’s service thrust and become one of the digital government services provided to the citizen.

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Section: Incentivesmentioning

confidence: 67%

Factors influencing open government data post-adoption in the public sector: The perspective of data providers

Mustapa

Hamid²,

Nasaruddin³

2022

PLoS ONE

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“…The conventional approach to this well-known problem is to reward data sharing, reduce professional incentives for data hoarding, and enshrine data sharing as an institutional and cultural norm. There are many examples of efforts that have adopted this approach, including the use of sharing badges by journals and data advertising by consortia to enhance the visibility of data sets and reputational credit of their creators (Devriendt et al, 2021 ). One of our interviewees, however, wondered whether these approaches are necessary given the popularity of open science norms among scientists who have pursued advanced degrees “within the last 10 years.” They explained: “I actually see this as a problem that's going to be taken care of by the natural course of familiarity with a new way of working, which is digital, and that it's correcting itself.” To those asking how to accelerate this change, the interviewee continued, “I'd probably answer back: is it worth trying to accelerate, or is it worth just promoting, helping those people that are operating in the new model be successful?”…”

Section: Incentives: Focusing Efforts On New Generations Of Scientistsmentioning

confidence: 99%

Section: Incentives: Focusing E Orts On New Generations Of Scientistsmentioning

confidence: 99%

Fresh takes on five health data sharing domains: Quality, privacy, equity, incentives, and sustainability

et al. 2023

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As entities around the world invest in repositories and other infrastructure to facilitate health data sharing, scalable solutions to data sharing challenges are needed. We conducted semi-structured interviews with 24 experts to explore views on potential issues and policy options related to health data sharing. In this Perspective, we describe and contextualize unconventional insights shared by our interviewees relevant to issues in five domains: data quality, privacy, equity, incentives, and sustainability. These insights question a focus on granular quality metrics for gatekeeping; challenge enthusiasm for maximalist risk disclosure practices; call attention to power dynamics that potentially compromise the patient's voice; encourage faith in the sharing proclivities of new generations of scientists; and endorse accounting for personal disposition in the selection of long-term partners. We consider the merits of each insight with the broad goal of encouraging creative thinking to address data sharing challenges.

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“…Discussions are still underway regarding the best strategies to incentivize data sharing, such as data or software attributions . In the interim, researchers should make their data available in repositories in standardized, nonproprietary formats, with digital object identifiers whenever feasible, and with clear guidelines for use.…”

Section: Vision For the Future: Toward Ehs Data Harmonizationmentioning

confidence: 99%

Enhancing Data Integration, Interoperability, and Reuse to Address Complex and Emerging Environmental Health Problems

Heacock

Lopez²,

Amolegbe

et al. 2022

Environ. Sci. Technol.

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Environmental health sciences (EHS) span many diverse disciplines. Within the EHS community, the National Institute of Environmental Health Sciences Superfund Research Program (SRP) funds multidisciplinary research aimed to address pressing and complex issues on how people are exposed to hazardous substances and their related health consequences with the goal of identifying strategies to reduce exposures and protect human health. While disentangling the interrelationships that contribute to environmental exposures and their effects on human health over the course of life remains difficult, advances in data science and data sharing offer a path forward to explore data across disciplines to reveal new insights. Multidisciplinary SRP-funded teams are well-positioned to examine how to best integrate EHS data across diverse research domains to address multifaceted environmental health problems. As such, SRP supported collaborative research projects designed to foster and enhance the interoperability and reuse of diverse and complex data streams. This perspective synthesizes those experiences as a landscape view of the challenges identified while working to increase the FAIR-ness (Findable, Accessible, Interoperable, and Reusable) of EHS data and opportunities to address them.

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Data Sharing in Biomedical Sciences: A Systematic Review of Incentives

Cited by 24 publications

References 41 publications

Factors influencing open government data post-adoption in the public sector: The perspective of data providers

Factors influencing open government data post-adoption in the public sector: The perspective of data providers

Fresh takes on five health data sharing domains: Quality, privacy, equity, incentives, and sustainability

Enhancing Data Integration, Interoperability, and Reuse to Address Complex and Emerging Environmental Health Problems

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