Taking a ‘Big Data’ approach to data quality in a citizen science project Article Swipe
Steve Kelling
,
Daniel Fink
,
Frank A. La Sorte
,
Alison Johnston
,
Nicholas E. Bruns
,
Wesley M. Hochachka
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1007/s13280-015-0710-4
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1007/s13280-015-0710-4
Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a 'Big Data' approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird's data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a 'sensor calibration' approach to measure individual variation in eBird participant's ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s13280-015-0710-4
- https://link.springer.com/content/pdf/10.1007/s13280-015-0710-4.pdf
- OA Status
- hybrid
- Cited By
- 162
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1885828288
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W1885828288Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s13280-015-0710-4Digital Object Identifier
- Title
-
Taking a ‘Big Data’ approach to data quality in a citizen science projectWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-10-27Full publication date if available
- Authors
-
Steve Kelling, Daniel Fink, Frank A. La Sorte, Alison Johnston, Nicholas E. Bruns, Wesley M. HochachkaList of authors in order
- Landing page
-
https://doi.org/10.1007/s13280-015-0710-4Publisher landing page
- PDF URL
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https://link.springer.com/content/pdf/10.1007/s13280-015-0710-4.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s13280-015-0710-4.pdfDirect OA link when available
- Concepts
-
Citizen science, Data science, Big data, Data quality, Computer science, Data collection, Scalability, Population, Geography, Data mining, Statistics, Database, Mathematics, Engineering, Demography, Botany, Biology, Operations management, Metric (unit), SociologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
162Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 17, 2024: 16, 2023: 19, 2022: 18, 2021: 23Per-year citation counts (last 5 years)
- References (count)
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42Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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