Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 27, issue 19
Articles | Volume 27, issue 19
https://doi.org/10.5194/hess-27-3565-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-3565-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 27, issue 19
Research article
 | 
09 Oct 2023
Research article |  | 09 Oct 2023

A Bayesian model for quantifying errors in citizen science data: application to rainfall observations from Nepal

Jessica A. Eisma, Gerrit Schoups, Jeffrey C. Davids, and Nick van de Giesen

Viewed

Total article views: 1,444 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,139 242 63 1,444 31 29
  • HTML: 1,139
  • PDF: 242
  • XML: 63
  • Total: 1,444
  • BibTeX: 31
  • EndNote: 29
Views and downloads (calculated since 15 May 2023)
Cumulative views and downloads (calculated since 15 May 2023)

Viewed (geographical distribution)

Total article views: 1,444 (including HTML, PDF, and XML) Thereof 1,462 with geography defined and -18 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 21 Nov 2024
Download
Short summary
Citizen scientists often submit high-quality data, but a robust method for assessing data quality is needed. This study develops a semi-automated program that characterizes the mistakes made by citizen scientists by grouping them into communities of citizen scientists with similar mistake tendencies and flags potentially erroneous data for further review. This work may help citizen science programs assess the quality of their data and can inform training practices.
Read more