“The creatures can see where each star has been and where it is going, so that the heavens are filled with rarefied, luminous spaghetti. And Tralfamadorians don’t see human beings as two-legged creatures, either. They see them as great millepedes—“with babies’ legs at one end and old people’s legs at the other,” says Billy Pilgrim.
-Kurt Vonnegut, Slaughterhouse-Five, 1969
I thought it might be cool to see my life like a Tralfamadorian.
The goal is to, given a position in time and using all data available, consistently infer the following:
-Position in 3D space
-Orientation in 3D space
-Time specific 3D model for character
-Environment
The following data is available:
Personal:
-Geolocation data exported from Google Maps “Timeline.” This forms the core dataset, but is not the only source of truth for position data without additional processing
-Geotagged photos with timestamps
-Financial transactions
-Timestamped emails, texts, phonecalls, whatsapps, google drive files, google chats,
-Browser history/Search History
Environment:
-Almanac style data on weather, sunrise/sunset
-Other news: sports scores, entertainment, technology, politics, stock market, Wikipedia “what happened on this day” style
-Gas prices, CPI
-Internet Wayback machine
-Calendar Events
-Average traffic data
-https://worldview.earthdata.nasa.gov/
-Google Earth’s temporal data (go back in time)
-Timestamped media (blogs, podcasts, etc)
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