Open Data for Citizen Science: A Discussion on GLOBE Observer Quality Flags

Since its founding in 1995, the Global Learning and Observations to Benefit the Environment (GLOBE) Program has amassed more than 230 million geospatial observations. GLOBE Observer, the official GLOBE mobile app, allows anyone in GLOBE countries to submit observations of clouds, mosquito habitats, land cover, and tree height. Like most big data, it is prudent to conduct quality checks on GLOBE Observer data before using the data for downstream purposes like research. Potential data concerns included observations submitted as a test, typos in manually entered data, measurements that are likely to be inaccurate, and repeated data fields or photos. This project focused on the implementation of new quality flags for this citizen science dataset. Using Python 3.9.13 and the GLOBE API, quality flags marking 1) integer latitude or longitude, 2) matching latitude and longitude, 3) observations that may have been taken over a lake, 4) 8 or more out of 10 cloud types indicated as present, and 5) duplicate photos within the same observation were created. While not removing any observations from the dataset, flags guide researchers by indicating which data may warrant further examination and/or may be candidates for inclusion or exclusion in downstream analyses. Most observations were not flagged. Of note, duplicate photo flags were primarily raised by Clouds and Land Cover observations, while the lakes flag was primarily raised by Clouds observations. Quality flags provide insight into how users interact with the GLOBE Observer app and allow researchers to better leverage the work of citizen scientists.