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The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.

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.

The work required to collect, clean and publish biodiversity datasets is significant, and those who do it deserve recognition for their efforts. Researchers publish studies using open biodiversity data available from GBIF—the Global Biodiversity Information Facility—at a rate of about two papers a day. These studies cover areas such as macroecology, evolution, climate change, and invasive alien species, relying on data sharing by hundreds of publishing institutions and the curatorial work of thousands of individual contributors. With more than 90 per cent of these datasets licensed under Creative Commons Attribution licenses (CC BY and CC BY-NC), data users are required to credit the dataset providers. For GBIF, it is crucial to link these scientific uses to the underlying data as one means of demonstrating the value and impact of open science, while seeking to ensure attribution of individual, organizational and national contributions to the global pool of open data about biodiversity. Every single authenticated download of occurrence records from GBIF.org is issued a unique Digital Object Identifier (DOI). These DOIs each resolve to a landing page that contains details of the search parameters used to generate the download a quantitative map of the underlying datasets that contributed to the download a simple citation to be included in works that rely on the data the search parameters used to generate the download a quantitative map of the underlying datasets that contributed to the download a simple citation to be included in works that rely on the data When used properly by authors and deposited correctly by journals in the article metadata, the DOI citation establishes a direct link between a scientific paper and the underlying data. Crossref—the main DOI Registration Agency for academic literature— exposes such links in Event Data, which can be consumed programmatically to report direct use of individual datasets. GBIF also records these links, permanently preserving the download archives while exposing a citation count on download landing pages that is also summarized on the landing pages of each contributing datasets and publishers. The citation counts can be expanded to produce lists of all papers unambiguously linked to use of specific datasets. In 2018, just 15 per cent of papers based on GBIF-mediated data used DOIs to cite or acknowledge the datasets used in the studies. To promote crediting of data publishers and digital recognition of data sharing, the GBIF Secretariat has been reaching out systematically to authors and publishers since April 2018 whenever a paper fails to include a proper data citation. While publishing lags may hinder immediate effects, preliminary findings suggest that uptake is improving—as the number of papers with DOI data citations during the first part of 2019 is up more than 60 per cent compared to 2018. Focusing on the value of linking scientific publications and data, this presentation will explore the potential for establishing automatic linkage through DOI metadata while demonstrating efforts to improve metrics of data use and attribution of data providers through outreach campaigns to authors and journal publishers.

There has been major progress over the last two decades in digitising historical knowledge of biodiversity and in making biodiversity data freely and openly accessible. Interlocking efforts bring together international partnerships and networks, national, regional and institutional projects and investments and countless individual contributors, spanning diverse biological and environmental research domains, government agencies and non-governmental organisations, citizen science and commercial enterprise. However, current efforts remain inefficient and inadequate to address the global need for accurate data on the world's species and on changing patterns and trends in biodiversity. Significant challenges include imbalances in regional engagement in biodiversity informatics activity, uneven progress in data mobilisation and sharing, the lack of stable persistent identifiers for data records, redundant and incompatible processes for cleaning and interpreting data and the absence of functional mechanisms for knowledgeable experts to curate and improve data. Recognising the need for greater alignment between efforts at all scales, the Global Biodiversity Information Facility (GBIF) convened the second Global Biodiversity Informatics Conference (GBIC2) in July 2018 to propose a coordination mechanism for developing shared roadmaps for biodiversity informatics. GBIC2 attendees reached consensus on the need for a global alliance for biodiversity knowledge, learning from examples such as the Global Alliance for Genomics and Health (GA4GH) and the open software communities under the Apache Software Foundation. These initiatives provide models for multiple stakeholders with decentralised funding and independent governance to combine resources and develop sustainable solutions that address common needs. This paper summarises the GBIC2 discussions and presents a set of 23 complementary ambitions to be addressed by the global community in the context of the proposed alliance. The authors call on all who are responsible for describing and monitoring natural systems, all who depend on biodiversity data for research, policy or sustainable environmental management and all who are involved in developing biodiversity informatics solutions to register interest at https://biodiversityinformatics.org/ and to participate in the next steps to establishing a collaborative alliance. The supplementary materials include brochures in a number of languages (English, Arabic, Spanish, Basque, French, Japanese, Dutch, Portuguese, Russian, Traditional Chinese and Simplified Chinese). These summarise the need for an alliance for biodiversity knowledge and call for collaboration in its establishment.

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.

Standards set up by Biodiversity Information Standards-Taxonomic Databases Working Group (TDWG), initially developed as a way to share taxonomical data, greatly facilitated the establishment of the Global Biodiversity Information Facility (GBIF) as the largest index to digitally-accessible primary biodiversity information records (PBR) held by many institutions around the world. The level of detail and coverage of the body of standards that later became the Darwin Core terms enabled increasingly precise retrieval of relevant records useful for increased digitally-accessible knowledge (DAK) which, in turn, may have helped to solve ecologically-relevant questions. After more than a decade of data accrual and release, an increasing number of papers and reports are citing GBIF either as a source of data or as a pointer to the original datasets. GBIF has curated a list of over 5,000 citations that were examined for contents, and to which tags were applied describing such contents as additional keywords. The list now provides a window on what users want to accomplish using such DAK. We performed a preliminary word frequency analysis of this literature, starting at titles, which refers to GBIF as a resource. Through a standardization and mapping of terms, we examined how the facility-enabled data seem to have been used by scientists and other practitioners through time: what concepts/issues are pervasive, which taxon groups are mostly addressed, and whether data concentrate around specific geographical or biogeographical regions. We hoped to cast light on which types of ecological problems the community believes are amenable to study through the judicious use of this data commons and found that, indeed, a few themes were distinctly more frequently mentioned than others. Among those, generally-perceived issues such as climate change and its effect on biodiversity at global and regional scales seemed prevalent. The taxonomic groups were also unevenly mentioned, with birds and plants being the most frequently named. However, the entire list of potential subjects that might have used GBIF-enabled data is now quite wide, showing that the availability of well-structured data has spawned a widening spectrum of possible use cases. Among them, some enjoy early and continuous presence (e.g. species, biodiversity, climate) while others have started to show up only later, once a critical mass of data seemed to have been attained (e.g. ecosystems, suitability, endemism). Biodiversity information in the form of standards-compliant DAK may thus already have become a commodity enabling insight into an increasingly more complex and diverse body of science. Paraphrasing Tennyson, more things were wrought by data than TDWG dreamt of.

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