Total aviation crashes and fatalities between the years 1945 to 2011.
My model organizes number of fatalities per crash, according to airline and month. The height of each bar represents number of fatalities, while the width represents the number of crashes. Each airline is represented by a colour. Users can filter the graph to show data over specified year ranges, as well as filter by airline.
Data is displayed in overlapping boxes, which makes total airline crashes and fatalities more easily comparable. Fatality and crash numbers are placed according to bar length and position, eliminating the need for a grid. This makes the data more visually accessible. The monthly/yearly combination also helps determine notable crashes (e.g. 9/11) if the user wants to continue with further research.
Users can view the information as a whole, or filter and compare specific airlines and years. Combining both filter options provides a much more in depth look at the airlines, allowing the user to determine when an airline had the most or least number of crashes and fatalities.
A sort of history of each airline can be viewed when using the yearly filter. The dataset is slightly biased in the sense that some airlines began much later than others, however adding a yearly filter allows the user to determine differences in general activity. A yearly filter also solves the bias of displaying crashes and fatalities as totals, since some crashes resulted in no fatalities. Using this, users can observe how each total has added up over the years.