Example — Hotels
Understanding the space and time characteristics of human interaction in complex social networks is a critical component of visual tools for intelligence analysis, consumer behavior analysis, and human geography. Visual identification and comparison of patterns of recurring events is an essential feature of such tools. The hotels visualization was designed for exploring hotel visitation patterns in and around central Pennsylvania circa 1900. It was in active development for over two years in an iterative process of data collection, hypothesis, design, discovery, and evaluation in close collaboration with historical geographers Deryck Holdsworth at Penn State and David Fyfe at York College of Pennsylvania.
The visualization consists of the following views:
  • A table view, showing the names, total visits, and pattern of visits over time for each guest.
  • A table view, showing the same information for each residence (place of origin).
  • A reruns view, showing total visits on each day using text and/or color. Squares distinguish weekends from circular weekdays. Months and seasons optionally appear as cell edges and a fill gradient, respectively. Cycle length and cell size can be rapidly adjusted using sliders. Mousing over a cell shows its date in the top left corner.
  • A vertical histogram along the right side of the reruns view, summarizing total visits for each period.
  • A horizontal histogram along the bottom of the reruns view, summarizing total visits for each day in the cycle.
  • A multi-layer map, showing crow-flies paths from residences to the hotel, relative to railroads and rivers.
  • An arc diagram, showing past (red) and future (blue) visits by guests visiting on selected dates.
  • A drill-down table view, showing individual register entries.
Analysts can pose rich sequences of who, what, where, and when questions by selecting arbitrary groups of hotels, guests, residences, and dates. These selections affect the filtering and visual appearance of all items across all views, thereby making it possible to ask questions by quickly drilling down into specific subsets of high-dimensional space-time data.
All views support additive selection of multiple data items. In the reruns view, selection of individual dates or particular cycles and periods happens by clicking individual cells or rubberbanding around blocks of cells. The map allows selection of residences by clicking, rubberbanding, or lassoing regions.
Extensive cross-filtering between views enables exploration of complex interdependent groupings of people, dates, and places. Bidirectional filtering allows users to show subsets of guests and/or home residences (as selected in the corresponding table views) in the reruns view, and conversely to show subsets of dates (as selected in the reruns view) in the guests and residences table views. Filtering between the residences table view and the nested bar plots in the guests table view allows users to show temporal visitation patterns for all guests, restricted to travel that involves selected residences. Similar filtering in the opposite direction shows temporal patterns of travel from all towns by selected guests only.
Using a process of successive selection and filtering, it is possible to ask specific questions and follow detailed chains of evidence. For example, an analyst might explore possible repeat meetings between guests prior to some critical event by asking the question, “For visitors on a particular date, on what previous dates did two or more of them visit repeatedly?” To pose this question, the analyst would select the critical event date in the reruns view, filter the guests table on date, select all guests in the guests table, filter the reruns view on selected guests, select all dates in the reruns view that involve multiple visitors, then look for guests having multiple visits with similar temporal patterns in the guests view.
Visualization (6.6 MB)
Video Tour (25.8 MB). Promotional video (of an older version) made to accompany the VAST 2006 paper.