Alternative technologies exist but carry a higher technical complexity and are less accessible to many researchers. The size of the dataset means that it can no longer be readily processed using standard Python-based data analytics software such as Pandas on commodity hardware. The success of the Covid Symptom Study creates significant technical challenges around effective data curation. As of May 23rd, 2021, over 5 million participants have collectively logged over 360 million self-assessment reports since its introduction in March 2020. The Covid Symptom Study, a smartphone-based surveillance study on COVID-19 symptoms in the population, is an exemplar of big data citizen science. Installing exeteracovid installs exetera.ĮxeTeraCovid has a wiki that can be found at. ĮxeTeraCovid ExeTeraCovid is hosted at and is available through pypi via pip install exeteracovid. The code is split up into two separate projects.ĮxeTera ExeTera is hosted at and is available through pypi via pip install exetera.ĮxeTera has a wiki that can be found at. The code used to generate synthetic evalutation datasets is hosted at and the 10 million/100 million row synthetic dataset is available for download 33.Īll source code for ExeTera is made available through github under the Apache 2.0 license, at the time of writing. Access to the data is free of charge at the time of writing but HDG may in future impose cost recovery on access requests that are not related to pandemic modelling or understanding or tackling Covid-19. The dataset is accessed via a protected environment provisioned by HDG for successful applicants. Access to the data is applied for via a two-stage process through HDG. The Covid Symptom Study dataset is hosted by Health Data Research UK through the (HDG), by searching for “COVID-19 Symptom Tracker Dataset”.
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