Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Context Extraterrestrials, visitors, little green men, UFOs, swap gas. What do they want? Where do they come from? Do they like cheeseburgers? This dataset will likely not help you answer these questions. It does contain over 80,000 records of UFO sightings dating back as far as 1949. With the latitude and longitude data it is possible to assess the global distribution of UFO sightings (patterns could aid in planetary defence if invasion proves to be imminent). The dates and times, along with the duration of the UFO's stay and description of the craft also lend themselves to predictions. Can we find patterns in their arrival times and durations? Do aliens work on weekends? Help defend the planet and learn about your fellow earthlings (and when they are most likely to see ET).
Content Date_time - standardized date and time of sighting date_documented - when was the UFO sighting reported Year - Year of sighting Month - Month of sighting Hour - Hour of sighting Season - Season of the sighting Country_Code - Country code for the country of the sighting Country - Country name Region - More granular address than country (Includes state, province, region, etc) Locale - More granular address than Region (Includes city, town, village, etc) latitude - latitude longitude - longitude UFO_shape - a one word description of the "spacecraft" length_of_encounter_seconds - standardized to seconds, length of the observation of the UFO Encounter_Duration - raw description of the length of the encounter (shows uncertainty to previous column) description - text description of the UFO encounter. Warning column is messy, with some curation it could lend itself to some natural language processing and sentiment analysis.
Note there are still some missing data in the columns. I've left it as is because depending on what the user is interested in the missing values in any one column may or may not matter.
Acknowledgements Original Data source: https://github.com/planetsig/ufo-reports Previous dataset: https://www.kaggle.com/datasets/camnugent/ufo-sightings-around-the-world Geo-locate script: https://github.com/jonwright13/geo-locate
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Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Context Extraterrestrials, visitors, little green men, UFOs, swap gas. What do they want? Where do they come from? Do they like cheeseburgers? This dataset will likely not help you answer these questions. It does contain over 80,000 records of UFO sightings dating back as far as 1949. With the latitude and longitude data it is possible to assess the global distribution of UFO sightings (patterns could aid in planetary defence if invasion proves to be imminent). The dates and times, along with the duration of the UFO's stay and description of the craft also lend themselves to predictions. Can we find patterns in their arrival times and durations? Do aliens work on weekends? Help defend the planet and learn about your fellow earthlings (and when they are most likely to see ET).
Content Date_time - standardized date and time of sighting date_documented - when was the UFO sighting reported Year - Year of sighting Month - Month of sighting Hour - Hour of sighting Season - Season of the sighting Country_Code - Country code for the country of the sighting Country - Country name Region - More granular address than country (Includes state, province, region, etc) Locale - More granular address than Region (Includes city, town, village, etc) latitude - latitude longitude - longitude UFO_shape - a one word description of the "spacecraft" length_of_encounter_seconds - standardized to seconds, length of the observation of the UFO Encounter_Duration - raw description of the length of the encounter (shows uncertainty to previous column) description - text description of the UFO encounter. Warning column is messy, with some curation it could lend itself to some natural language processing and sentiment analysis.
Note there are still some missing data in the columns. I've left it as is because depending on what the user is interested in the missing values in any one column may or may not matter.
Acknowledgements Original Data source: https://github.com/planetsig/ufo-reports Previous dataset: https://www.kaggle.com/datasets/camnugent/ufo-sightings-around-the-world Geo-locate script: https://github.com/jonwright13/geo-locate