Named is a novel website which allows people inwards the U.K. to detect out where their surname is unusually common. The application is real slow to use. All you lot create is come inwards a surname in addition to named shows you lot a heatmap highlighting where in that place is an unusually high publish of people amongst that name.
Named likewise allows you lot to come inwards ii surnames to detect locations where both names are unusually common. The application uses information from an quondam U.K. electoral ringlet to live on out the distribution of names. The application thus entirely industrial plant for the UK.
Place Names inwards the US visualizes the spatial distribution of town & metropolis house names inwards America.
For representative you lot tin laissez passer on the axe sentiment the distribution of house names starting amongst Castilian articles (El, Los, Las) in addition to San & Santa (mainly inwards the Southwest). Alternatively you lot tin laissez passer on the axe search using suffixes. For representative the distribution of towns amongst mutual British town endings, such every bit chester, wick, wich, pool, ham, ness, port & worth (mainly inwards the Northeast).
Place Names inwards the United States has a database of roughly xxx grand towns in addition to cities inwards the United States. The house cite information used is from opengeocode.org in addition to the application was built using Canvas, SVG in addition to d3.js.
Wikipedia has entries for 8,049 battles that induce got taken house across the globe throughout the sorrowful history of the human race. Nodegoat's map, the Wikidata Geography of Violence, visualizes this warfare information throughout fourth dimension in addition to across the globe.
The map includes a appointment command which allows you lot to filter the results shown on the map for whatever menses of time. The battle markers on the map are likewise color coded yesteryear date. If you lot select a battle's marking on the map you lot tin laissez passer on the axe click through to come across its entry on Wikidata in addition to read its Wikipedia entry.
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