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Based on our record, Every Noice at Once seems to be a lot more popular than GeaCron. While we know about 422 links to Every Noice at Once, we've tracked only 33 mentions of GeaCron. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There was a website called GeaCron which allowed you to enter any year since 3000 BC and instantly see an interactive world map that depicted the borderes and regions of the year. Source: 10 months ago
GeaCron can show you the changing of borders every year across the world for the last 5000 years, since 3000 BC. Source: 11 months ago
This website goes all the way from 3000 BCE to now. Source: about 1 year ago
In this context, I didn't include Canada and Australia. I used Geacron map: http://geacron.com/home-en/. Source: about 1 year ago
Used this website to generate the map. Don't know how accurate it is but it's probably a good starting point to figure out which faction would be where in history. Source: over 1 year ago
I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / about 1 month ago
Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / about 2 months ago
The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 5 months ago
This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 6 months ago
Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 6 months ago
Time Maps - Time Maps is an online encyclopedia that provides a huge collection of books of maps of the modern era and historical maps.
Last.fm - The world's largest online music service. Listen online, find out more about your favourite artists, and get music recommendations, only at Last.fm
World History Atlas - World History Atlas is an app that provides a pictorial representation of history and its events in an intuitive graphical manner.
Rate Your Music - Rate, list, and catalog music, videos, concerts, etc.
Omniatlas - Omniatlas is a website that provides a world map with extreme details and a wide range of accurate information.
RadioGarden - An interactive map of live radio stations across the globe.