Accessible Data Curation and Analytics for International-Scale Citizen\n Science Datasets

The Covid Symptom Study, a smartphone-based surveillance study on COVID-19\nsymptoms in the population, is an exemplar of big data citizen science. Over\n4.7 million participants and 189 million unique assessments have been logged\nsince its introduction in March 2020. The success of the Covid Symptom Study\ncreates technical challenges around effective data curation for two reasons.\nFirstly, the scale of the dataset means that it can no longer be easily\nprocessed using standard software on commodity hardware. Secondly, the size of\nthe research group means that replicability and consistency of key analytics\nused across multiple publications becomes an issue. We present ExeTera, an open\nsource data curation software designed to address scalability challenges and to\nenable reproducible research across an international research group for\ndatasets such as the Covid Symptom Study dataset.\n