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Lessons from citizen science: Assessing volunteer-collected plant phenology data with Mountain Watch
Citizen science has the potential to expand the scope of data collection, engage the public in research, and answer big scientific questions. But, the quality of volunteer-collected data is often called into question, and citizen science programs must find ways to assess the validity of this concern...
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Published in: | Biological conservation 2017-04, Vol.208, p.121-126 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Citizen science has the potential to expand the scope of data collection, engage the public in research, and answer big scientific questions. But, the quality of volunteer-collected data is often called into question, and citizen science programs must find ways to assess the validity of this concern. Here, we review five years of volunteer-collected data from an alpine flower monitoring citizen science project and present our efforts to investigate the quality of the volunteer-collected data. We found disparity between citizen scientists' self-assessed and actual plant species identification skills, indicating error in either true plant identification or reported location, consequently limiting the use of this dataset. Citizen science programs, including this project, must assess their data, and then make adjustments — in training, data collection methods, or goals — in order to produce quality data consistent with their scientific intentions. Indeed, this project now relies only on observations from seasonal trained staff and a handful of skilled volunteers in light of these findings.
•Assessing volunteer-collected data is important for citizen science.•We need examples of assessment methods for programs with limited resources.•Here, volunteers were unable to gauge their own ability to identify alpine plants.•This assessment led to adjustments in the data collecting model and volunteer pool. |
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ISSN: | 0006-3207 1873-2917 |
DOI: | 10.1016/j.biocon.2016.07.027 |