摘要 :
Analyzing important changes to massive transportation datasets like national bottleneck statistics, passenger data for domestic flights, airline maintenance budgets, or even publication data from the Transportation Research Record...
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Analyzing important changes to massive transportation datasets like national bottleneck statistics, passenger data for domestic flights, airline maintenance budgets, or even publication data from the Transportation Research Record can be extremely complex. These types of datasets are often grouped by attributes in a tree structure hierarchy. The parent-child relationships of these hierarchical datasets allow for unique analytical opportunities, including the ability to track changes in the dataset at different levels of granularity, over time or between versions. For example, analysts can use hierarchies to uncover changes in the patterns of passengers flying in the United States over the last ten years, breaking down the data by states, cities, airports, and number of passengers. Exploring changes in travel patterns over time can help carriers make better decisions regarding their operations and long-range planning. This paper describes TreeVersity2, a web-based data comparison tool that provides users with information visualization techniques to find what has changed in a dataset over time. TreeVersity2 enables users to explore data that can be inherently hierarchical or not (by categorizing them by their attributes). An interactive textual reporting tool complements the visual exploration when the amount of data is very large. The results of two case studies conducted with transportation domain experts along with the results of an exit questionnaire are also described. TreeVersity2 preloaded with several demo datasets can be found at along with several example videos.
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