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Data from: Revealing biases in insect observations a comparative analysis between academic and citizen science data

NIAID Data Ecosystem2026-05-02 收录

昆虫观测偏差

公民科学数据质量

数据链接：

https://zenodo.org/record/10045222 数据链接链接失效反馈

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资源简介：

Data and code used in the article "Revealing biases in insect observations a comparative analysis between academic and Citizen Science data".

应用场景：

创建时间：

2024-12-04

传粉昆虫监测

公民科学数据质量

Background Recently there has been increasing focus on monitoring pollinating insects, due to concerns about their declines, and interest in the role of volunteers in monitoring pollinators, particula

NIAID Data Ecosystem70

Do Carefully-timed Email Messages Increase Accuracy and Precision in Citizen Scientists' Reports of Events?

公民科学数据质量

物候观测数据收集

Periodic messages are a commonly used tactic for reminding citizen science program participants to take a desired action such as collecting observations. In this study, we evaluate the impact of such

NIAID Data Ecosystem40

Comparison of vegetation cover, height and seed count data collected by children and scientists.

植被监测

公民科学数据质量

Comparison of vegetation cover, height and seed count data collected by children and scientists.

NIAID Data Ecosystem20

Growing completeness of multi-taxon biodiversity occurrence information is associated with long-term socioeconomic advance in China

生物多样性监测

公民科学数据质量

The absence of comprehensive species distribution data may hinder our understanding of biogeographic patterns and the development of effective conservation strategies. Although citizen science data on

DataCite Commons2025-05-26 更新60

Data for "How does young citizen scientists’ age, gender and attitudes affect the quality of data collected in ecological research project?"

公民科学数据质量

生态研究参与式监测

Data for "How does young citizen scientists’ age, gender and attitudes affect the quality of data collected in ecological research project?" The metadata can be found in the file.

Figshare2022-04-12 更新30

Data from: Revealing biases in insect observations a comparative analysis between academic and citizen science data

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