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dc.contributor.authorKrüger, Roberten_US
dc.contributor.authorThom, Dennisen_US
dc.contributor.authorWörner, Michaelen_US
dc.contributor.authorBosch, Haralden_US
dc.contributor.authorErtl, Thomasen_US
dc.contributor.editorB. Preim, P. Rheingans, and H. Theiselen_US
dc.date.accessioned2015-02-28T15:31:47Z
dc.date.available2015-02-28T15:31:47Z
dc.date.issued2013en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.12132en_US
dc.description.abstractThe 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.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectH.3.3 [Information Storage and Retrieval]en_US
dc.subjectInformation Search and Retrievalen_US
dc.subjectInformation filteringen_US
dc.subjectQuery formulationen_US
dc.subjectSelection processen_US
dc.subjectH.5.2 [Information Interfaces and Presentation]en_US
dc.subjectUser Interfacesen_US
dc.subjectGUIen_US
dc.titleTrajectoryLenses - A Set-based Filtering and Exploration Technique for Long-term Trajectory Dataen_US
dc.description.seriesinformationComputer Graphics Forumen_US


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