Community science – also known as citizen science – has enormous appeal for researchers looking to collect larger datasets and engage the public in their work. But are the data collected in this way any good?
But a key tenet of scientific data collection is accuracy and consistency. What community science offers to traditional research methods is only as good as the quality of data its participants produce. In a new study, researchers put that quality to the test.
Study author and botanist Matt von Konrat, head of plant collections at the Chicago Field Museum, says community science could change this. After viewing the tutorial, participants were shown a randomly-selected image of a liverwort specimen from the museum's collection, and asked to make their own measurement of its lobules.
To test how 'good' each community science data entry was, the researchers compared them to that of an expert using the same methods, to find if there was a statistically significant difference. The results exceeded their expectations.The researchers predicted that about 50 percent of measurements would make it through the data cleaning process, and that older age groups would be able to provide much better data than children.
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