I Want to Believe : A Visualization of UFO Siting Reports

In this work we present an interactive visualization tool for examining UFO reports. The high level goal is to support 1) a geographic summarization of UFO sightings and 2) a linguistic summarization of these reports. By using manipulation tools, such as filter and zoom, we show how our visualization can aid curious individuals in gaining an insightful summary of the thousands of UFO reports available. Corresponding scenarios are provided for each task and an in depth review of potential future work is outlined. INTRODUCTION Have you ever looked into the night sky and seen something unusual? Perhaps it was a star or an airplane, but what if it was actually something from another planet? While some people may see something suspicious in the sky and keep going on with their lives, others feel the need to report this strange event to the appropriate authorities. The National UFO Reporting Center (NUFORC) was founded in 1974 and since then its primary function has been to receive, record, corroborate, and document reports from individuals who have witnessed unusual, possibly UFO-related events. [1] NUFORC has had a 24-hour hotline available since 1974 and in the past 20 years has expanded to receiving reports via fax, email, and the organization’s webform. These reports are stored in a publicly available database and are indexed by date of sighting, shape, state, and date posted. The reports range from serious reports to obvious hoaxes and while mostly reported from within the United States, there are reports of sightings throughout the world. Initially when looking through the data, we thought it would be interesting to plot the reports geographically based on population density with the intention of searching for trends over time in terms of location, shape, and duration. With some investigation we found that current visualizations tend to address the question of who the people making reports are and where they are from. Trends in shape over time was also a popular visualization, as well as what time of day and what month have the most sightings. Upon gathering this prior work, we decided that while mapping the reports is still of interest, we also wanted to do some sort of textual analysis of the summaries of the reports in aggregate. We came to this conclusion after spending some time with the raw data and seeing that the text summaries often paint a more vivid picture of the encounter than the quantitative and categorical data possibly could. What we propose in this work is a dual-view interaction tool which provides a geographic view that plots the reports on an interactive map and a textual summary of the aggregated reports. We use filters to reduce the number of items on the map based on shape, date range, time of day, and duration. The map view can be zoomed in to limit the visible data points. When there are multiple markers in a small area in the map, they are clustered together and encoded by hue to indicate the density of the markers within an area. Once a view on the map has been established, textual analysis can be performed on the visible reports using SentenTree, a visualization tool originally intended for text-based social media posts (tweets, etc.). The appearance of each SentenTree report is similar to a word cloud with the additional benefit of preserving an aggregated visual representation of sentence structure. DATA AND TASK ABSTRACTIONS