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The 2019 coronavirus disease (COVID-19) pandemic increased efforts for rapid data sharing and dissemination among researchers as well as to data repositories. Researchers and studies prioritized data sharing, which increased understanding of SARS-CoV-2's pathology. Eventually, this effort to maximize collaboration and data dissemination, led to the development of mRNA vaccines. This successful effort has highlighted the importance of data sharing and the implementation of data management policies, including the National Institutes of Health's (NIH) Data Sharing Policy of 2023. Moreover, programs such as the National Institute of Allergy and Infectious Diseases (NIAID) funded Collaborative Influenza Vaccine Innovation Centers (CIVICs), have beta-tested this policy, with the help of the Statistical, Data Management and Coordination Center (SDMCC) and its data standards, and deemed it useful. However, the process has also initiated pertinent discussion on potential improvements and optimizations for the future of data sharing. Here, I use the CIVICs data sharing reporting standards and process as a data sharing example, and suggest logistical improvements to propose a better-equipped model for the vaccinology community.

PurposeThis survey-based study aims to explore the research data dissemination and requesting practices of Arab researchers. It investigates the reasons, types, methods, barriers and motivations associated with data sharing and requesting in the Arab research community.Design/methodology/approachA cross-sectional survey was conducted with 205 Arab researchers representing various disciplines and career stages. Descriptive statistics were used for data analysis.FindingsThe study found that 91.2% of Arab researchers share data, while 56.6% access data from others. Reasons for sharing include promoting transparency and collaboration while requesting data is driven by the need to validate findings and explore new research questions. Processed/analysed data and survey/questionnaire data are the most commonly shared and requested types.Originality/valueThis study contributes to the literature by examining data sharing and requesting practices in the Arab research community. It provides original insights into the motivations, barriers and data types shared and requested by Arab researchers. This can inform future research and initiatives to promote regional data sharing.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2023-0283

The international sharing of virus data is critical for protecting populations against lethal infectious disease outbreaks. Scientists must rapidly share information to assess the nature of the threat and develop new medical countermeasures. Governments need the data to trace the extent of the outbreak, initiate public health responses, and coordinate access to medicines and vaccines. Recent outbreaks suggest, however, that the sharing of such data cannot be taken for granted – making the timely international exchange of virus data a vital global challenge. This article undertakes the first analysis of the Global Initiative on Sharing All Influenza Data as an innovative policy effort to promote the international sharing of genetic and associated influenza virus data. Based on more than 20 semi‐structured interviews conducted with key informants in the international community, coupled with analysis of a wide range of primary and secondary sources, the article finds that the Global Initiative on Sharing All Influenza Data contributes to global health in at least five ways: (1) collating the most complete repository of high‐quality influenza data in the world; (2) facilitating the rapid sharing of potentially pandemic virus information during recent outbreaks; (3) supporting the World Health Organization's biannual seasonal flu vaccine strain selection process; (4) developing informal mechanisms for conflict resolution around the sharing of virus data; and (5) building greater trust with several countries key to global pandemic preparedness. Impact Statement The rapid spread of lethal infectious diseases is a global challenge potentially affecting any person around the world. To protect populations against such deadly outbreaks, it is critical that scientists and governments rapidly share information about the pathogens causing them. Without access to such information, it will be very difficult to properly assess the risk posed to global health, to develop new medical countermeasures, and to mount a commensurate international response. However, recent outbreaks suggest several impediments to the rapid sharing of virus data. Scientist may wish to withhold data until their scholarly studies are published; governments are fearful about the repercussions of being associated with a major new outbreak, and it remains challenging to fund global public goods like an international database to host such data. Through the first study of the Global Initiative on Sharing All Influenza Data (GISAID), this article shows how it is possible to encourage the greater international sharing of such data through the careful design of new sharing mechanisms. GISAID has now developed a successful track‐record in the field of influenza that may also serve as a useful blueprint for managing other diseases and global challenges requiring the international sharing of sensitive data.

PurposeTo improve supply chain performance, companies are now exploring new pathways including industry-wide data sharing initiatives along complex supply chains. The purpose of this paper is to stimulate research in this field by describing the benefits, obstacles and the governance required for supply chain data sharing initiatives.Design/methodology/approachBased on publicly available information complemented by interviews with practitioners, the authors describe how companies are establishing ambitious data sharing infrastructure and initiatives along their supply chains.FindingsThe authors describe how data sharing along supply chains is becoming increasingly important for many companies and how the automotive sector is working towards establishing a digital infrastructure for data sharing that could support a wide range of use cases. The article emphasises the importance of studying the governance of data ecosystems using new theoretical approaches. Finally, the authors suggest three areas for future research on data ecosystems, including their governance, the learning dynamics that will drive their adoption and their relationship with broader system-level changes.Originality/valueThis paper is the first, to the authors’ knowledge, that depicts how industry-wide data-sharing initiatives are expected to have an impact on supply chain performance. The authors highlight factors that affect the development and implementation of these initiatives along supply chains.

To identify the similarities and differences in data-sharing policies for clinical trial data that are endorsed by biomedical journals, funding agencies, and other professional organizations. Additionally, to determine the beliefs, and opinions regarding data-sharing policies for clinical trials discussed in articles published in biomedical journals. Two searches were conducted, a bibliographic search for published articles that present beliefs, opinions, similarities, and differences regarding policies governing the sharing of clinical trial data. The second search analyzed the gray literature (non–peer-reviewed publications) to identify important data-sharing policies in selected biomedical journals, foundations, funding agencies, and other professional organizations. A total of 471 articles were included after database search and screening, with 45 from the bibliographic search and 426 from the gray literature search. A total of 424 data-sharing policies were included. Fourteen of the 45 published articles from the bibliographic search (31.1%) discussed only advantages specific to data-sharing policies, 27 (27/45; 60%) discussed both advantages and disadvantages, and 4 (4/45; 8.9%) discussed only disadvantages specific. A total of 216 journals (of 270; 80%) specified a data-sharing policy provided by the journal itself. One hundred industry data-sharing policies were included, and 32 (32%) referenced a data-sharing policy on their website. One hundred and thirty-six (42%) organizations (of 327) specified a data-sharing policy. We found many similarities listed as advantages to data-sharing and fewer disadvantages were discussed within the literature. Additionally, we found a wide variety of commonalities and differences—such as the lack of standardization between policies, and inadequately addressed details regarding the accessibility of research data—that exist in data-sharing policies endorsed by biomedical journals, funding agencies, and other professional organizations. Our study may not include information on all data sharing policies and our data is limited to the entities’ descriptions of each policy. •This scoping review contributes to better understanding the interplay between journals, foundations, funding agencies, and professional organizations' current data-sharing policies and the commonalities and differences between them.•Most articles favor a discussion about the advantages of data-sharing more so than the disadvantages of data sharing.•A wide variety of commonalities and differences—such as the lack of standardization between policies, and inadequately addressed details regarding the accessibility of research data—exists in data-sharing policies endorsed by biomedical journals, funding agencies, and other professional organizations.•Updates to data-sharing policies should strive to provide clearer and more comprehensive instruction based on existing theoretical frameworks, the further development of accessibility of research data, and inclusion of detailed methods to prevent barriers to data-sharing.•It is important to identify and address key factors that contribute to the endorsement of and resistance to data-sharing, and to ameliorate the reproducibility of research results to ensure a solid foundation for safe and effective patient care.

PurposeThis study investigates the multifaceted barriers and facilitators affecting research data sharing across the research data lifecycle. It aims to broaden the understanding of data sharing beyond the publication phase, emphasizing the continuous nature of data sharing from generation to reuse.Design/methodology/approachEmploying a mixed-methods approach, the study integrates the Theory of Planned Behavior, the Technology Acceptance Model, and the Institutional Theory to hypothesize the influence of various factors on data sharing behaviors across the lifecycle. A questionnaire survey and structural equation modeling are utilized to empirically test these hypotheses.FindingsThis study identifies critical factors influencing data sharing at different lifecycle stages, including perceived behavioral control, perceived effort, journal and funding agency pressures, subjective norms, perceived risks, resource availability, and perceived benefits. The findings highlight the complex interplay of these factors and their varying impacts at different stages of data sharing.Research limitations/implicationsThis study illuminates the dynamics of research data sharing, offering insights while recognizing its scope might not capture all disciplinary and cultural nuances. It highlights pathways for stakeholders to bolster data sharing, suggesting a collaborative push towards open science, reflecting on how strategic interventions can bridge existing gaps in practice.Practical implicationsThis study offers actionable recommendations for policymakers, journals, and institutions to foster a more conducive environment for data sharing, emphasizing the need for support mechanisms at various lifecycle stages.Originality/valueThis study contributes to the literature by offering a comprehensive model of the research data lifecycle, providing empirical evidence on the factors influencing data sharing across this continuum.

[Purpose/Significance] Public access policy plays a crucial role in raising the awareness of openness, promoting scientific progress and innovation development. Studying the current situation of scientific data sharing in international countries can provide a reference for the practice and development of scientific data sharing activities in China. [Method/Process] Over the past 15 years, an increasing number of funding agencies in the United States have responded to national policy calls to require funded projects to share the research results in order to improve the effectiveness of the grant implementation and to promote scientific development. To this end, many academic institutions have established and provided a variety of data support facilities and services, but these facilities and services are often scattered across different administrative departments. Data management and sharing activities under this model suffer from organizational deficiencies, fragmented activities, overlapping services, inaccessibility, and others that reduce the efficiency of public access to scientific data. In order to understand the reality of scientific data sharing, ARL conducted a fact-based study named the RADS initiative on the scientific data sharing model, with survey respondents coming from six research-intensive universities in the United States, who are involved in scientific data management and sharing, resulting in a relatively comprehensive survey. The article adopts the network research method and literature analysis method, through the interpretation of the first phase of ARL's RADS Initiative series of reports and materials, to comprehensively understand the composition of the entire life cycle of scientific data management and sharing activities, service content and implementation costs of the U.S. academic institutions under the public access policy. We also analyze the behavioral characteristics of the two main actors of the U.S. colleges and universities involved in the practice of scientific data sharing, the characteristics of the activities and support services, and summarize the real problems of scientific data management. The practical problems of scientific data sharing include inter-departmental coordination and linkage, gaps in supply and demand between disciplines, boundaries between disciplines, inadequate cost-benefit evaluation, and the availability of shared data to the public. [Results/Conclusions] On the basis of summarizing the successful experiences and shortcomings of the RADS Initiative, and taking into account the current situation of scientific data sharing in China, this paper puts forward the construction ideas and quality enhancement suggestions to promote the implementation of scientific data sharing activities in China at each level with an emphasis on public participation, We propose to integrate the coordinated development and optimize cost-effectiveness, foster the data literacy and emphasize user feedback, focus on the public access, and construct the core clusters.

In 2011, an Advanced Notice of Proposed Rulemaking proposed that de-identified human data and specimens be included in biobanks only if patients provide consent. The National Institutes of Health Genomic Data Sharing policy went into effect in 2015, requiring broad consent from almost all research participants. We conducted a systematic literature review of attitudes toward biobanking, broad consent, and data sharing. Bibliographic databases included MEDLINE, Web of Science, EthxWeb, and GenETHX. Study screening was conducted using DistillerSR. The final 48 studies included surveys (n = 23), focus groups (n = 8), mixed methods (n = 14), interviews (n = 1), and consent form analyses (n = 2). Study quality was characterized as good (n = 19), fair (n = 27), and poor (n = 2). Although many participants objected, broad consent was often preferred over tiered or study-specific consent, particularly when broad consent was the only option, samples were de-identified, logistics of biobanks were communicated, and privacy was addressed. Willingness for data to be shared was high, but it was lower among individuals from under-represented minorities, individuals with privacy and confidentiality concerns, and when pharmaceutical companies had access to data. Additional research is needed to understand factors affecting willingness to give broad consent for biobank research and data sharing in order to address concerns to enhance acceptability.

Data sharing statements are considered routine in clinical trial reporting and represent a step toward data transparency. The International Committee of Medical Journal Editors (ICMJE) required clinical trials to publish data sharing statements. We aimed to assess the requirement for data sharing statements of individual participant data by biomedical journals and explore associations between journal characteristics and journal requirements for data sharing statements. In this cross-sectional study, we included all biomedical journals that published clinical trials from January 1, 2019, to December 31, 2022, and that were indexed by the Journal Citation Reports. The study outcome was the journal requirement for data sharing statements. Multivariable logistic regression analysis was used to assess the relationship between journal characteristics and requirement for data sharing statements. Of the 3229 biomedical journals included in the analysis, 2345 (72.6%) required authors to include data sharing statements. Journals published in the UK (OR, 3.19 [95% CI, 2.43-4.22]) and endorsing the Consolidated Standards of Reporting Trials (OR, 3.30 [95% CI, 2.78-3.92]) had greater odds of requiring data sharing statements. Journals that were open access, non-English language, in the Journal Citation Reports group of clinical medicine, and on the ICMJE list had lower odds of requiring data sharing statements, with ORs ranging from 0.18 to 0.81. Despite ICMJE recommendations, more than 27% of the biomedical journals that published clinical trials did not require clinical trials to include data sharing statements, highlighting room for improved transparency.

There is increasing support for sharing individual-level data generated by medical and public health research. This scoping review of empirical research and conceptual literature examined stakeholders’ perspectives of ethical best practices in data sharing, particularly in low- and middle-income settings. Sixty-nine empirical and conceptual articles were reviewed, of which, only five were empirical studies and eight were conceptual articles focusing on low- and middle-income settings. We conclude that support for sharing individual-level data is contingent on the development and implementation of international and local policies and processes to support ethical best practices. Further conceptual and empirical research is needed to ensure data sharing policies and processes in low- and middle-income settings are appropriately informed by stakeholders’ perspectives.