ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis challenging, due to data size and complexity. We present an integrated solution for interactive visual analysis and exploration of events along trajectories data. Our approach supports analysis of event sequences at three different levels of abstraction, namely spatial, temporal, and events themselves. Customized views as well as standard views are combined to form a coordinated multiple views system. In addition to trajectories and events, we include on-the-fly derived data in the analysis. We evaluate our integrated solution using the IEEE VAST 2015 Challenge data set. A successful detection and characterization of malicious activity indicate the usefulness and efficiency of the presented approach.

[1]  Georges G. Grinstein,et al.  VAST Challenge 2015: Mayhem at dinofun world , 2015, 2015 IEEE Conference on Visual Analytics Science and Technology (VAST).

[2]  Wei Luo,et al.  VAST challenge 2015: Grand challenge - Team VADER/VIS Award for Outstanding Comprehensive Submission , 2015, 2015 IEEE Conference on Visual Analytics Science and Technology (VAST).

[3]  Ben Shneiderman,et al.  LifeFlow: visualizing an overview of event sequences , 2011, CHI.

[4]  Xiaoru Yuan,et al.  TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection , 2011, 2011 IEEE Pacific Visualization Symposium.

[5]  Ben Shneiderman,et al.  Cohort Comparison of Event Sequences with Balanced Integration of Visual Analytics and Statistics , 2015, IUI.

[6]  David Gotz,et al.  DecisionFlow: Visual Analytics for High-Dimensional Temporal Event Sequence Data , 2014, IEEE Transactions on Visualization and Computer Graphics.

[7]  Cláudio T. Silva,et al.  Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips , 2013, IEEE Transactions on Visualization and Computer Graphics.

[8]  Hai Lin,et al.  A collaborative visual analysis system for communication pattern discovery , 2015, 2015 IEEE Conference on Visual Analytics Science and Technology (VAST).

[9]  Denis Gracanin,et al.  Color LinesView:AnApproach toVisualization of Families of Function Graphs , 2007, 2007 11th International Conference Information Visualization (IV '07).

[10]  Ben Shneiderman,et al.  Temporal Event Sequence Simplification , 2013, IEEE Transactions on Visualization and Computer Graphics.

[11]  Dino Pedreschi,et al.  Unveiling the complexity of human mobility by querying and mining massive trajectory data , 2011, The VLDB Journal.

[12]  Denis Gracanin,et al.  Interactive Visual Analysis of Families of Function Graphs , 2006, IEEE Transactions on Visualization and Computer Graphics.

[13]  Mengchen Liu,et al.  A survey on information visualization: recent advances and challenges , 2014, The Visual Computer.

[14]  Daniel A. Keim,et al.  Using visual analytics to provide situation awareness for movement and communication data , 2015, 2015 IEEE Conference on Visual Analytics Science and Technology (VAST).

[15]  Christopher Andrews,et al.  Middguard at dinofun world , 2015, 2015 IEEE Conference on Visual Analytics Science and Technology (VAST).

[16]  Naren Ramakrishnan,et al.  Experiences with mining temporal event sequences from electronic medical records: initial successes and some challenges , 2011, KDD.

[17]  Daniel A. Keim,et al.  Visual Analytics of Movement , 2013, Springer Berlin Heidelberg.

[18]  Heikki Mannila,et al.  Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.

[19]  Michael Gleicher,et al.  Sequence Surveyor: Leveraging Overview for Scalable Genomic Alignment Visualization , 2011, IEEE Transactions on Visualization and Computer Graphics.

[20]  M. Wachowicz,et al.  Exploring visitor movement patterns in natural recreational areas. , 2012 .