Sharpeville Massacre Tragedy Casualties Visualization Tool - Cockeyed.com

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Disaster Casualties Visualization Tool: Sharpeville Massacre: 1960

69 Dead Men and Women

The Sharpeville massacre at the police station in the South African township of Sharpeville. After a day of demonstrations the South African police opened fire on the crowd of black protesters killing 69 people.

This was a person. She was sleeping with her ex.

This was a person. She was sleeping with her ex.

This was a person. She had a gun. She was homophobic.

This was a person. He got a terrible haircut a few days ago and shaved his head to escape from it.

This was a person. He was a skilled woodcarver. He had a bunch of cameras.

This was a person. She was a glassblower.

This was a person. He was sort of selfish in bed.

This was a person. She helped strangers.

This was a person. She was kind of addicted to ebay.

This was a person. He was sporty.

This was a person. She was kind of addicted to ebay.

This was a person. She was a tailor.

This was a person. She was a skilled woodcarver.

This was a person. She loved James Bond movies.

This was a person. She has a suit at the cleaners.

This was a person. He never carried cash.

This was a person. She wore bow ties.

This was a person. She always brought reusable bags into the store.

This was a person. He was a mason.

This was a person. She couldn't grow a mustache.

This was a person. He kept to himself mostly

This was a person. She was an expert barbecuer.

This was a person. She was a scout leader.

This was a person. She didn't get along with animals.

This was a person. She knew how to get free satelittle television.

This was a person. She plays fantasy football.

This was a person. She just had the bandages removed from plastic surgery.

This was a person. He never drank coffee.

This was a person. She was sleeping with her ex.

This was a person. She always made the mashed potatoes at family get-togethers.

This was a person. He wrote for the newspaper.

This was a person. She can't watch the end of T2 without crying

This was a person. She had a bunch of cameras. She could play harmonica.

This was a person. She occasionally shop lifted.

This was a person. She was the richest of her friends.

This was a person. She played World of Warcraft

This was a person. She was an awful driver.

This was a person. She made scrapbooks.

This was a person. He helped people.

This was a person. He was awaiting judgement for a DUI last month. He scalped tickets

This was a person. He always had gum. He was a scout leader.

This was a person. He was a tailor.

This was a person. She loved James Bond movies.

This was a person. He took a lot of photos.

This was a person. He made pie.

This was a person. She was homophobic.

This was a person. She did not own a fridge.

This was a person. She was kind of an awesome lover.

This was a person. He always brought reusable bags into the store.

This was a person. She had an awesome home theatre.

This was a person. She had a personal injury lawsuit working its way through the courts. She was a historian.

This was a person. She wore a lot of jewelry.

This was a person. He had a sexy phone voice.

This was a person. She could play harmonica.

This was a person. She plays fantasy football.

This was a person. She threw a lot of parties. She could play cricket.

This was a person. He could play harmonica.

This was a person. He was a wedding photographer.

This was a person. He was a trivia master.

This was a person. He could play trumpet.

This was a person. He was training to run a marathon.

This was a person. He was a tailor. He wore a lot of jewelry.

This was a person. He wore bow ties. He fixed bikes.

This was a person. He wore a lot of jewelry. He loved to fish.

This was a person. She was very careful about conserving gasoline. She never finished the book club book.

This was a person. He had extensions.

This was a person. He was thrifty.

This was a person. He was awaiting judgement for a DUI last month.

This was a person. She was polite to telemarketers.

View a different tragedy with the Disaster Visualization Tool

Jonestown | The Titanic | Kent State Shootings | My Lai | Lockerbie bombing | Kent State Shootings | Tiananmen Square Massacre | The Banana massacre | The Boyd Massacre | Mountain Meadows massacre | Kfar Etzion Massacre | Sharpeville Massacre | The Miami Showband Massacre | The Novocherkassk massacre | Tokyo Subway Sarin attack | Sinking of the Titanic | The Happy Land Fire | Brooklyn Bridge stampede | 1990 Pilgrim Stampede | Luxor hot air balloon crash |

Mouse-over body descriptions are randomly generated, intended to inject humanity into the raw number of dead. It cannot accurately represent the actual people who died in the tragedy.

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