Crowdsourcing the identification of organisms: a case-study of iSpot
- Submitting institution
-
The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1453313
- Type
- D - Journal article
- DOI
-
10.3897/zookeys.480.8803
- Title of journal
- ZooKeys
- Article number
- -
- First page
- 125
- Volume
- 480
- Issue
- -
- ISSN
- 1313-2989
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2015
- URL
-
http://zookeys.pensoft.net/articles.php?id=4633
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
7
- Research group(s)
-
-
- Citation count
- 67
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper reports on the citizen science platform iSpot, taking a multidisciplinary approach. iSpot's novel reputation system was shown to be efficient at achieving taxonomic identification (92% identified, 50% within 1hr), improving precision of identification, and rejecting over-precise identification. By careful design, the reputation system successfully connected experts to beginners, building a long-lasting social network into a strong learning community with 76,000 users making 813,000 observations. iSpot was supported by Big Lottery Fund, Wolfson Foundation and British Council. Altmetrics scored this paper in the top 5% of all research outputs (https://www.altmetric.com/details/3239226, Feb 2021).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -