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
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
中文摘要
康奈尔大学获得一笔赠款,以支持网络基础设施,以维持eBird的持续指数增长,eBird是全球鸟类生物多样性的在线数据资源。eBird于2002年推出,开启了观鸟者实时数据收集的新时代,到2020年,该项目已成为世界上最大的生物多样性相关公民科学项目。超过500,000名贡献者提交了全球10,000多种鸟类的近7.5亿份鸟类观察报告。这些数据提供了关于全年鸟类种群在整个物种范围内的空间和时间分布的全面、高分辨率信息。eBird数据建模产生了北美鸟类状况和趋势结果,为了解物种的完整年周期提供了无与伦比的窗口,为基础生物研究和保护应用提供了宝贵的种群水平分布数据来源。所有eBird数据都是公开的,已经被学生、教育工作者、政府工作人员和研究人员下载了13万多次,产生了300多篇同行评议的科学论文。eBird一如既往地作为观鸟的重要工具,每年有超过800万来自世界各地的用户访问eBird,通过交互式探索、可视化和分析工具探索eBird数据。基础和应用生态学的大部分研究都建立在对物种分布和丰富度的描述之上。涵盖广泛空间尺度的长期、组织良好的数据对于记录变化、对其原因提出假设以及最终了解这些变化与整体生态系统健康和功能的关系是必要的。虽然收集单一物种的发生数据是一个很好理解的过程,但协调收集,管理,访问和存储这些数据并不是一项小任务。适当的结构,公开可用,并保持在一个一致的长期网络基础设施物种的发生,以及其他大规模的环境数据集已成为研究生物多样性的必要条件。eBird的数据管理基础设施的目标是提供:(1)一个单一的,一致收集和策划的数据源,是公开可用的,并广泛使用,(2)代表了全球所有鸟类物种分布的所有可用数据的很大一部分,以及(3)提供这些数据在一套增值产品,降低使用这些数据所需的数据管理门槛。有关eBird的更多信息,请访问其网站http://ebird.org.This奖项反映了NSF的法定使命,并已被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。
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.
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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
DOI:
10.1098/rspb.2023.1398
发表时间:
2023-04
期刊:
Proceedings of the Royal Society B: Biological Sciences
影响因子:
--
作者:
[Jeremy M. Cohen;D. Fink;B. Zuckerberg]
通讯作者:
Jeremy M. Cohen;D. Fink;B. Zuckerberg
共 20 条
21ENGBIO - High-Throughput Design of Novel Sensors to Help Address the Impending Phosphate Crisis
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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:
Development and experimental validation of a deep-learning based pipeline for user-centric protein design.
-
批准号:EP/S003002/1
-
项目类别:Fellowship
-
资助金额:$38.74万
-
财政年份:2018
-
负责人:Christopher Wood
-
依托单位:
SBIR Phase I: Large Aperture, Periodically-Structured Gallium Arsenide for Infrared and THz Wavelength Conversion
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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:Christopher Wood
-
依托单位:
海外基金