The Happy Land Fire Tragedy Casualties Visualization Tool - Cockeyed.com

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Disaster Casualties Visualization Tool: The Happy Land Fire: 1990

87 Dead Men and Women

The Happy Land fire was an arson fire that killed 87 people trapped in an unlicensed social club, 1990.

This was a person. She had a green thumb.

This was a person. He was divorced. He was allergic to peanuts.

This was a person. She was a virgin. She was learning to use CAD software.

This was a person. He could play banjo.

This was a person. He was the unofficial relationship guru among friends.

This was a person. He loved Elvis.

This was a person. He had a gun.

This was a person. He spends a lot of time watching tennis.

This was a person. He could fix anything.

This was a person. She played chess.

This was a person. She loved to fish. She helped people.

This was a person. She was a Mac evangelist.

This was a person. She talked during movies.

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. She could play cricket. She had extensions.

This was a person. She could fall asleep anywhere.

This was a person. He wore earphones all the time.

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

This was a person. She was a drunk. She was rebuilding an engine.

This was a person. She snored.

This was a person. He was left-handed.

This was a person. He was 4 days sober.

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

This was a person. He was a pharmacist. He was working his way through all of the shows on Netflix.

This was a person. He smoked pot at music festivals.

This was a person. He was gluten intolerant.

This was a person. She snored.

This was a person. He was playing nine games of Words with Friends on his phone. He was a crossword whiz.

This was a person. He went to the horseraces. He played guitar on the streets for money.

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

This was a person. He had long fingernails. He did not own a fridge.

This was a person. She was sporty.

This was a person. He was a Mac evangelist.

This was a person. He loved Elvis.

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

This was a person. He took careful notes after every meal.

This was a person. He could fall asleep anywhere.

This was a person. He was a pharmacist. He was working his way through all of the shows on Netflix.

This was a person. He wore a lot of hats.

This was a person. She helped strangers.

This was a person. She played piano.

This was a person. She was gluten intolerant.

This was a person. She was afraid of the water.

This was a person. She was cockeyed.

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

This was a person. She was a drunk.

This was a person. She was polite to salesmen.

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

This was a person. She dropped her work laptop last week, destroyed it and couldn't sleep for days.

This was a person. He loved oreos.

This was a person. He ate the food at convenience stores.

This was a person. He made pie. He kept to himself mostly

This was a person. He played chess.

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

This was a person. He was a skilled woodcarver. He had bonsai trees.

This was a person. He was a hoarder.

This was a person. He was left-handed.

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

This was a person. She was divorced.

This was a person. He was a glassblower.

This was a person. She was a poet.

This was a person. She plays fantasy football.

This was a person. She had a hangover yesterday. She was a street vendor.

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

This was a person. She was afraid of flying.

This was a person. He got thrown off of a golf course.

This was a person. He was afraid of flying.

This was a person. She had a bunch of cameras.

This was a person. He was a good dancer.

This was a person. He smoked pot at music festivals.

This was a person. She prefered bread without crusts.

This was a person. He has two living parents.

This was a person. She was very careful about conserving gasoline.

This was a person. She was an awful driver.

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

This was a person. He was cockeyed.

This was a person. She was an awful driver.

This was a person. She was polite to telemarketers.

This was a person. She got out of jail two years ago and never reunited with her family.

This was a person. He was a DJ.

This was a person. She was living with her sister. She was a pharmacist.

This was a person. She was the unofficial relationship guru among friends. She has four overdue books.

This was a person. He loved fine dining.

This was a person. He overtipped.

This was a person. She always wore a hat.

This was a person. She always had gum. She once robbed a bank.

This was a person. He helped people.

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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The Weight of Clothing

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