TY - JOUR
T1 - TrajectoryLenses - A set-based filtering and exploration technique for long-term trajectory data
AU - Krüger, Robert
AU - Thom, Dennis
AU - Wörner, Michael
AU - Bosch, Harald
AU - Ertl, Thomas
PY - 2013/6
Y1 - 2013/6
N2 - The visual analysis of spatiotemporal movement is a challenging task. There may be millions of routes of different length and shape with different origin and destination, extending over a long time span. Furthermore there can be various correlated attributes depending on the data domain, e.g. engine measurements for mobility data or sensor data for animal tracking. Visualizing such data tends to produce cluttered and incomprehensible images that need to be accompanied by sophisticated filtering methods. We present TrajectoryLenses, an interaction technique that extends the exploration lens metaphor to support complex filter expressions and the analysis of long time periods. Analysts might be interested only in movements that occur in a given time range, traverse a certain region, or end at a given area of interest (AOI). Our lenses can be placed on an interactive map to identify such geospatial AOIs. They can be grouped with set operations to create powerful geospatial queries. For each group of lenses, users can access aggregated data for different attributes like the number of matching movements, covered time, or vehicle performance. We demonstrate the applicability of our technique on a large, real-world dataset of electric scooter tracks spanning a 2-year period.
AB - The visual analysis of spatiotemporal movement is a challenging task. There may be millions of routes of different length and shape with different origin and destination, extending over a long time span. Furthermore there can be various correlated attributes depending on the data domain, e.g. engine measurements for mobility data or sensor data for animal tracking. Visualizing such data tends to produce cluttered and incomprehensible images that need to be accompanied by sophisticated filtering methods. We present TrajectoryLenses, an interaction technique that extends the exploration lens metaphor to support complex filter expressions and the analysis of long time periods. Analysts might be interested only in movements that occur in a given time range, traverse a certain region, or end at a given area of interest (AOI). Our lenses can be placed on an interactive map to identify such geospatial AOIs. They can be grouped with set operations to create powerful geospatial queries. For each group of lenses, users can access aggregated data for different attributes like the number of matching movements, covered time, or vehicle performance. We demonstrate the applicability of our technique on a large, real-world dataset of electric scooter tracks spanning a 2-year period.
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U2 - 10.1111/cgf.12132
DO - 10.1111/cgf.12132
M3 - Article
AN - SCOPUS:84879756726
SN - 0167-7055
VL - 32
SP - 451
EP - 460
JO - Computer Graphics Forum
JF - Computer Graphics Forum
IS - 3 PART4
ER -