We decided to take the title of the challenge quite literally - by making the data hearable though music. We decided to sort satellite data into country territories, so that we could hear the planetary data change and listen to how that corresponds to the rise and fall of COVID-19 cases and mobility data. The resulting symphonies can be heard by selecting the regions on the map.
We've taken data from various sources, and use that to generate and modulate music. At the same time, some of us are working on gathering this data based on regions/countries, so that for each selected datatype and country, a symphony of melodies will play. We can then tie that together into a prototype web-app!
The app is live at www.thesoundofsilence.biz and you can view a demo at https://youtu.be/B1tv1QL-_8k.
References:
covid_19_cases.csv: Contains the number of COVID-19 cases per country as reported on the respective day. This data is provided by the European Union.mobility_data.csv: Contains the change in visits to six areas of daily life in percent versus baseline. Since six areas are added up, the minimum is -600. This data is provided by Google.co_data.csv: Contains measurements of carbon monoxide (CO) in the troposphere in exa-moles (i.e. 10^18) per cubic centimetre as reported by Measurements Of Pollution In The Troposphere (MOPITT) by the Canadian Space Agency. The data is pre-processed to an average per country per day, using the geo-location data as contained in the ../resources/countries.geojson file.no2_data.csv: Contains measurements of nitrogen dioxide (NO2) in the troposphere in exa-molecules (i.e. 10^18) per square centimetre as reported by the Ozone Monitoring Instrument (OMI). The data is pre-processed to an average per country per eight days, using the geo-location data as contained in the ../resources/countries.geojson file.evi_data.csv: Contains measurements of the enhanced vegeatation index as reported by the Suomi National Polar-orbiting Partnership of NASA. The data is pre-processed to an average per country per day, using the geo-location data as contained in the ../resources/countries.geojson file.