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Taking a ‘Big Data’ approach to data quality in a citizen science project

Overview of attention for article published in Ambio: A Journal of the Human Environment, October 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
2 blogs
twitter
11 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
214 Mendeley
Title
Taking a ‘Big Data’ approach to data quality in a citizen science project
Published in
Ambio: A Journal of the Human Environment, October 2015
DOI 10.1007/s13280-015-0710-4
Pubmed ID
Authors

Steve Kelling, Daniel Fink, Frank A. La Sorte, Alison Johnston, Nicholas E. Bruns, Wesley M. Hochachka

Abstract

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.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 214 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 2%
United States 4 2%
Spain 2 <1%
Canada 2 <1%
Netherlands 1 <1%
Colombia 1 <1%
Germany 1 <1%
Unknown 198 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 47 22%
Student > Ph. D. Student 46 21%
Researcher 35 16%
Unspecified 22 10%
Student > Bachelor 18 8%
Other 46 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 60 28%
Environmental Science 47 22%
Unspecified 33 15%
Computer Science 28 13%
Social Sciences 11 5%
Other 35 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 August 2017.
All research outputs
#626,772
of 12,484,416 outputs
Outputs from Ambio: A Journal of the Human Environment
#72
of 837 outputs
Outputs of similar age
#20,525
of 274,225 outputs
Outputs of similar age from Ambio: A Journal of the Human Environment
#6
of 39 outputs
Altmetric has tracked 12,484,416 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 837 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 274,225 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.