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Significance As anthropogenic impacts to Earth systems accelerate, biodiversity knowledge integration is urgently required to support responses to underpin a sustainable future. Consolidating information from disparate sources (e.g., community science programs, museums) and data types (e.g., environmental, biological) can connect the biological sciences across taxonomic, disciplinary, geographical, and socioeconomic boundaries. In an analysis of the research uses of the world’s largest cross-taxon biodiversity data network, we report the emerging roles of open-access data aggregation in the development of increasingly diverse, global research. These results indicate a new biodiversity science landscape centered on big data integration, informing ongoing initiatives and the strategic prioritization of biodiversity data aggregation across diverse knowledge domains, including environmental sciences and policy, evolutionary biology, conservation, and human health., The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world’s largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.

In this modern, data-driven age, governments, funders and publishers expect greater transparency and reuse of research data, as well as greater access to and preservation of the data that supports research findings. Community-developed standards, such as those for the identification1 and reporting2 of data, underpin reproducible and reusable research, aid scholarly publishing, and drive both the discovery and evolution of scientific practice. The number of these standardization efforts, driven by large organizations or at the grass root level, has been on the rise since the early 2000s. Thousands of community-developed standards are available (across all disciplines), many of which have been created and/or implemented by several thousand data repositories. Nevertheless, their uptake by the research community, however, has been slow and uneven. This is mainly because investigators lack incentives to follow and adopt standards. The situation is exacerbated if standards are not promptly implemented by databases, repositories and other research tools, or endorsed by infrastructures. Furthermore, the fragmentation of community efforts results in the development of arbitrarily different, incompatible standards. In turn, this leads to standards becoming rapidly obsolete in fast-evolving research areas.As with any other digital object, standards, databases and repositories are dynamic in nature, with a ‘life cycle’ that encompasses formulation, development and maintenance; their status in this cycle may vary depending on the level of activity of the developing group or community. There is an urgent need for a service that enhances the information available on the evolving constellation of heterogeneous standards, databases and repositories, guides users in the selection of these resources, and that works with developers and maintainers of these resources to foster collaboration and promote harmonization. Such an informative and educational service is vital to reduce the knowledge gap among those involved in producing, managing, serving, curating, preserving, publishing or regulating data. A diverse set of stakeholders-representing academia, industry, funding agencies, standards organizations, infrastructure providers and scholarly publishers— both national and domain-specific as well global and general organizations— have come together as a community, representing the core adopters, advisory board members, and/or key collaborators of the FAIRsharing resource. Here, we introduce its mission and community network. We present an evaluation of the standards landscape, focusing on those for reporting data and metadata - the most diverse and numerous of the standards - and their implementation by databases and repositories. We report on the ongoing challenge to recommend resources, and we discuss the importance of making standards invisible to the end users. We report on the ongoing challenge to recommend resources, and we discuss the importance of making standards invisible to the end users. We present guidelines that highlight the role each stakeholder group must play to maximize the visibility and adoption of standards, databases and repositories.

Type 1 diabetes is due to destruction of pancreatic β-cells. Lysine deacetylase inhibitors (KDACi) protect β-cells from inflammatory destruction in vitro and are promising immunomodulators. Here we demonstrate that the clinically well-tolerated KDACi vorinostat and givinostat revert diabetes in the nonobese diabetic (NOD) mouse model of type 1 diabetes and counteract inflammatory target cell damage by a mechanism of action consistent with transcription factor--rather than global chromatin--hyperacetylation. Weaning NOD mice received low doses of vorinostat and givinostat in their drinking water until 100-120 d of age. Diabetes incidence was reduced by 38% and 45%, respectively, there was a 15% increase in the percentage of islets without infiltration, and pancreatic insulin content increased by 200%. Vorinostat treatment increased the frequency of functional regulatory T-cell subsets and their transcription factors Gata3 and FoxP3 in parallel to a decrease in inflammatory dendritic cell subsets and their cytokines IL-6, IL-12, and TNF-α. KDACi also inhibited LPS-induced Cox-2 expression in peritoneal macrophages from C57BL/6 and NOD mice. In insulin-producing β-cells, givinostat did not upregulate expression of the anti-inflammatory genes Socs1-3 or sirtuin-1 but reduced levels of IL-1β + IFN-γ-induced proinflammatory Il1a, Il1b, Tnfα, Fas, Cxcl2, and reduced cytokine-induced ERK phosphorylation. Further, NF-κB genomic iNos promoter binding was reduced by 50%, and NF-κB-dependent mRNA expression was blocked. These effects were associated with NF-κB subunit p65 hyperacetylation. Taken together, these data provide a rationale for clinical trials of safety and efficacy of KDACi in patients with autoimmune disease such as type 1 diabetes. ispartof: Proceedings of the National Academy of Sciences of the United States of America vol:111 issue:3 pages:1055-9 ispartof: location:United States status: published