课题基金 / 基金详情

eBird Enterprise: Maintaining the Cyberinfrastructure to Support the Collection, Storage, Archive, Analysis, and Access to a Global Biodiversity Data Resource

eBird Enterprise: Maintaining the Cyberinfrastructure to Support the Collection, Storage, Archive, Analysis, and Access to a Global Biodiversity Data Resource
eBird Enterprise:维护网络基础设施以支持全球生物多样性数据资源的收集、存储、存档、分析和访问
批准号:
1939187
负责人:
Christopher Wood
金额:
$117.15万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-03-01 至 2025-02-28

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中文摘要
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英文摘要
Cornell University is awarded a grant to support the cyberinfrastructure to sustain the continued exponential growth of eBird, an online data resource for global bird biodiversity. With its launch in 2002, eBird opened a new era of real-time data gathering by birders, and by 2020, the project has become the world’s largest biodiversity-related citizen science project. More than 500,000 contributors have submitted almost 750 million bird observations of more than 10,000 bird species globally. These data provide comprehensive, high-resolution information about the spatial and temporal distribution of bird populations across a species full range, throughout the year. Modeling eBird data has generated North American bird status and trends results that provide an unparalleled window into a species’ full annual cycle providing a valuable source of population-level distributional data for basic biological research and conservation applications. All eBird data is openly available and has been downloaded more than 130,000 times by students, educators, government staff, and researchers, resulting in more than 300 peer-reviewed scientific papers. True to its beginnings, eBird is still grounded in serving as an essential tool for birding and more than 8 million people access eBird every year from every country to explore eBird data through interactive exploration, visualization and analysis tools.Much of the research in basic and applied ecology is founded in descriptions of distribution and abundance of species. Long-term, well-organized data covering broad spatial scales are necessary for documenting change, generating hypotheses for their causes, and ultimately understanding how these changes relate to overall ecosystem health and function. While collecting a single-species occurrence datum is a well-understood process, the coordinated collection, curation, access, and storage of these data is no small task. Appropriately structured, openly available, and maintained in a consistent long-term cyberinfrastructure species occurrence, as well as other large-scale environmental datasets have become essential for studying biodiversity. The goal of eBird’s data management infrastructure is to provide a: (1) a single, consistently gathered and curated data source that is openly available and widely in use, (2) represents a substantial proportion of all available data on distribution of all bird species globally, and (3) provides these data in a suite of value-added products that lower the threshold of data management needed to use these data. For more information about eBird, visit its website at http://ebird.org.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(22)
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会议论文
DOI: 10.1111/ecog.06457
发表时间: 2023-06
期刊: Ecography
影响因子: 5.9
作者: [A. Binley;J. Bennett;R. Schuster;A. Rodewald;F. L. La Sorte;D. Fink;B. Zuckerberg;Scott Wilson]
通讯作者: A. Binley;J. Bennett;R. Schuster;A. Rodewald;F. L. La Sorte;D. Fink;B. Zuckerberg;Scott Wilson
DOI: 10.1016/j.rse.2021.112309
发表时间: 2021-03
期刊: Remote Sensing of Environment
影响因子: 13.5
作者: [David Gudex‐Cross;Spencer R. Keyser;B. Zuckerberg;D. Fink;Likai Zhu;J. Pauli;V. Radeloff]
通讯作者: David Gudex‐Cross;Spencer R. Keyser;B. Zuckerberg;D. Fink;Likai Zhu;J. Pauli;V. Radeloff
Deep learning with citizen science data enables estimation of species diversity and composition at continental extents
利用公民科学数据进行深度学习可以估计大陆范围内的物种多样性和组成
DOI: 10.1002/ecy.4175
发表时间: 2023
期刊: Ecology
影响因子: 4.8
作者: [Davis, Courtney L., Bai, Yiwei, Chen, Di, Robinson, Orin, Ruiz‐Gutierrez, Viviana, Gomes, Carla P., Fink, Daniel]
通讯作者: Fink, Daniel
DOI: 10.1111/ecog.05495
发表时间: 2021-05-04
期刊: ECOGRAPHY
影响因子: 5.9
作者: [Cohen, Jeremy M., Fink, Daniel, Zuckerberg, Benjamin]
通讯作者: Zuckerberg, Benjamin
20
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    • 批准号:
      BB/W013320/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $12.85万
    • 财政年份:
      2022
    • 负责人:
      Christopher Wood
    • 依托单位:
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    • 批准号:
      EP/S003002/1
    • 项目类别:
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    • 资助金额:
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    • 财政年份:
      2018
    • 负责人:
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    SBIR Phase I: Large Aperture, Periodically-Structured Gallium Arsenide for Infrared and THz Wavelength Conversion
    • 批准号:
      1013472
    • 项目类别:
      Standard Grant
    • 资助金额:
      $14.98万
    • 财政年份:
      2010
    • 负责人:
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    • 依托单位:
    海外基金