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HCI, InfoVis

Response to [Spatiotemporal …] by

Spatiotemporal analysis of sensor logs is a challenging research field due to three facts: a) traditional two-dimensional maps do not support multiple events to occur at the same spatial location, b) three-dimensional solutions introduce ambiguity and are hard to navigate, c) map distortions to solve the overlap problem are unfamiliar to most users.

  • Coordinates on 2-d plane -> the actual positions of different sensor nodes.
  • Amount of time -> number of pixels in a ‘bounding’ circle’. Hence the more visits in certain time period, the larger the radius.
  • Different colors -> different sensor nodes in different regions. There are three kinds of sensor nodes: water place, ground floor and higher floor.
  • Varying color intensities -> temporal property of the subjects’ activity. Gradient is used to indicate the elapse of time.

The goal of the visualization is to find similarities and extract patterns of interest in spatiotemporal data by using humans’ perceptual abilities. For example, but recognizing the ‘darkness’ of the color of circles, viewers can tell when there are the most number of visits.

More issues:

  • Besides the Growth Ring Maps, the authors also considered two other approaches, namely, the temporal aspect of mice movement and the movement between sensors in a matrix representation of the sensor.
  • To cross-validate the results, the authors use MDS ( Multi-Dimensional Scaling).

Implications for project:


  • Using gradient should be an option to visualize the past and the future
  • The size of the representation matters (Maybe we can show how busy one is in the current week).


  • The nature of this paper is more task-centered whereas the calendar visualization is more of a casual visualization.
  • This paper focuses on the fact that how often where when was visited while ignoring the relations between different visits (we do not know what happen between these visits). The calendar visualization, on the other hand, focuses on 1) where I was, 2) where I am and 3) where I will be.
  • This paper use color-encoding to solve the third spatial dimension whereas such dimension is not an issue in the calendar visualization.
  • Fundamentally, the visualization in this paper is for closer observation while the calendar visualization is for public ambient display.

About Xiang 'Anthony' Chen

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