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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.

A central tenet in support of research reproducibility is the ability to uniquely identify research resources, i.e., reagents, tools, and materials that are used to perform experiments. However, current reporting practices for research resources are insufficient to allow humans and algorithms to identify the exact resources that are reported or answer basic questions such as \"What other studies used resource X?\" To address this issue, the Resource Identification Initiative was launched as a pilot project to improve the reporting standards for research resources in the methods sections of papers and thereby improve identifiability and reproducibility. The pilot engaged over 25 biomedical journal editors from most major publishers, as well as scientists and funding officials. Authors were asked to include Research Resource Identifiers (RRIDs) in their manuscripts prior to publication for three resource types: antibodies, model organisms, and tools (including software and databases). RRIDs represent accession numbers assigned by an authoritative database, e.g., the model organism databases, for each type of resource. To make it easier for authors to obtain RRIDs, resources were aggregated from the appropriate databases and their RRIDs made available in a central web portal ( www.scicrunch.org/resources). RRIDs meet three key criteria: they are machine readable, free to generate and access, and are consistent across publishers and journals. The pilot was launched in February of 2014 and over 300 papers have appeared that report RRIDs. The number of journals participating has expanded from the original 25 to more than 40. Here, we present an overview of the pilot project and its outcomes to date. We show that authors are generally accurate in performing the task of identifying resources and supportive of the goals of the project. We also show that identifiability of the resources pre- and post-pilot showed a dramatic improvement for all three resource types, suggesting that the project has had a significant impact on reproducibility relating to research resources.

The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function.

Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the advantages or disadvantages of Open Access at multiple levels. This review aims to to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas of impact: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic case for Open Access is less well-understood, although it is clear that access to the research literature is key for innovative enterprises, and a range of governmental and non-governmental services. Furthermore, Open Access has the potential to save publishers and research funders considerable amounts of financial resources. The social case for Open Access is strong, in particular for advancing citizen science initiatives, and leveling the playing field for researchers in developing countries. Open Access supersedes all potential alternative modes of access to the scholarly literature through enabling unrestricted re-use, and long-term stability independent of financial constraints of traditional publishers that impede knowledge sharing. Open Access remains only one of the multiple challenges that the scholarly publishing system is currently facing. Yet, it provides one foundation for increasing engagement with researchers regarding ethical standards of publishing. We recommend that Open Access supporters focus their efforts on working to establish viable new models and systems of scholarly communication, rather than trying to undermine the existing ones as part of the natural evolution of the scholarly ecosystem. Based on this, future research should investigate the wider impacts of an ecosystem-wide transformation to a system of Open Research.

Protein S-palmitoylation is a reversible post-translational modification that regulates many key biological processes, although the full extent and functions of protein S-palmitoylation remain largely unexplored. Recent developments of new chemical methods have allowed the establishment of palmitoyl-proteomes of a variety of cell lines and tissues from different species.  As the amount of information generated by these high-throughput studies is increasing, the field requires centralization and comparison of this information. Here we present SwissPalm ( http://swisspalm.epfl.ch), our open, comprehensive, manually curated resource to study protein S-palmitoylation. It currently encompasses more than 5000 S-palmitoylated protein hits from seven species, and contains more than 500 specific sites of S-palmitoylation. SwissPalm also provides curated information and filters that increase the confidence in true positive hits, and integrates predictions of S-palmitoylated cysteine scores, orthologs and isoform multiple alignments. Systems analysis of the palmitoyl-proteome screens indicate that 10% or more of the human proteome is susceptible to S-palmitoylation. Moreover, ontology and pathway analyses of the human palmitoyl-proteome reveal that key biological functions involve this reversible lipid modification. Comparative analysis finally shows a strong crosstalk between S-palmitoylation and other post-translational modifications. Through the compilation of data and continuous updates, SwissPalm will provide a powerful tool to unravel the global importance of protein S-palmitoylation.

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.

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.

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

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.

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.