Storygraph: extracting patterns from spatio-temporal data

  • Authors:
  • Ayush Shrestha;Ben Miller;Ying Zhu;Yi Zhao

  • Affiliations:
  • Georgia State University, Atlanta, Georgia;Georgia State University, Atlanta, Georgia;Georgia State University, Atlanta, Georgia;Georgia State University, Atlanta, Georgia

  • Venue:
  • Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics
  • Year:
  • 2013

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Abstract

Analysis of spatio-temporal data often involves correlating different events in time and location to uncover relationships between them. It is also desirable to identify different patterns in the data. Visualizing time and space in the same chart is not trivial. Common methods includes plotting the latitude, longitude and time as three dimensions of a 3D chart. Drawbacks of these 3D charts include not being able to scale well due to cluttering, occlusion and difficulty to track time in case of clustered events. In this paper we present a novel 2D visualization technique called Storygraph which provides an integrated view of time and location to address these issues. We also present storylines based on Storygraph which show movement of the actors over time. Lastly, we present case studies to show the applications of Storygraph.