GSTDTAP  > 资源环境科学
DOI10.1073/pnas.2018093118
Data integration enables global biodiversity synthesis
J. Mason Heberling; Joseph T. Miller; Daniel Noesgaard; Scott B. Weingart; Dmitry Schigel
2021-02-09
发表期刊Proceedings of the National Academy of Sciences
出版年2021
英文摘要

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.

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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/313953
专题资源环境科学
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J. Mason Heberling,Joseph T. Miller,Daniel Noesgaard,et al. Data integration enables global biodiversity synthesis[J]. Proceedings of the National Academy of Sciences,2021.
APA J. Mason Heberling,Joseph T. Miller,Daniel Noesgaard,Scott B. Weingart,&Dmitry Schigel.(2021).Data integration enables global biodiversity synthesis.Proceedings of the National Academy of Sciences.
MLA J. Mason Heberling,et al."Data integration enables global biodiversity synthesis".Proceedings of the National Academy of Sciences (2021).
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