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eBird: A citizen-based bird observation network in the biological sciences
Abstract
New technologies are rapidly changing the way we collect, archive, analyze, and share scientific data. For example, over the next several years it is estimated that more than one billion autonomous sensors will be deployed over large spatial and temporal scales, and will gather vast quantities of data. Networks of human observers play a major role in gathering scientific data, and whether in astronomy, meteorology, or observations of nature, they continue to contribute significantly. In this paper we present an innovative use of the Internet and information technologies that better enhances the opportunity for citizens to contribute their observations to science and the conservation of bird populations. eBird is building a web-enabled community of bird watchers who collect, manage, and store their observations in a globally accessible unified database. Through its development as a tool that addresses the needs of the birding community, eBird sustains and grows participation. Birders, scientists, and conservationists are using eBird data worldwide to better understand avian biological patterns and the environmental and anthropogenic factors that influence them. Developing and shaping this network over time, eBird has created a near real-time avian data resource producing millions of observations per year.
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“Citizen science can also enable dataset collection at a scale impossible in individual studies [93,533,634,767].”
From Tackling climate change with machine learning (2023) · cites this paper as [767]
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Metadata
- Authors
- Sullivan, B. L., Wood, C. L., Iliff, M. J., Bonney, R. E., Fink, D., & Kelling, S.
- Affiliations
- Cornell Lab of Ornithology (US)
- Corresponding author
- Sullivan, Brian L.
- Venue
- Biological Conservation
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 142
- Issue
- 10
- Pages
- 2282-2292
- ISSN
- 0006-3207 (ISSN-L)
- OpenAlex
- W2085154695
- Cited by
- 2,017
- References
- 32
- Citations by year
- 2026: 168 · 2025: 208 · 2024: 185 · 2023: 199 · 2022: 175 · 2021: 198 · 2020: 164 · 2019: 152 · 2018: 128 · 2017: 123 · 2016: 77 · 2015: 73 · 2014: 46 · 2013: 39 · 2012: 38
- FWCI
- 23.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biological Conservation (publishedVersion)
- Funders
- Cornell Lab of Ornithology
- Topics
- Physical Sciences › Environmental Science › Ecology › Avian ecology and behavior
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Keywords
- eBird, citizen science, bird observations, birdwatchers, online data collection, biodiversity data sharing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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