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dc.contributor.authorKonzack, Maximilian
dc.contributor.authorMcKetterick, Thomas
dc.contributor.authorOphelders, Tim
dc.contributor.authorBuchin, Maike
dc.contributor.authorGiuggioli, Luca
dc.contributor.authorLong, Jed
dc.contributor.authorNelson, Trisalyn
dc.contributor.authorWestenberg, Michel A.
dc.contributor.authorBuchin, Kevin
dc.identifier.citationKonzack , M , McKetterick , T , Ophelders , T , Buchin , M , Giuggioli , L , Long , J , Nelson , T , Westenberg , M A & Buchin , K 2017 , ' Visual analytics of delays and interaction in movement data ' International Journal of Geographical Information Science , vol. 31 , no. 2 , pp. 320-345 .
dc.identifier.otherPURE: 243473430
dc.identifier.otherPURE UUID: 6fbb3e31-527a-482c-87ad-f678bf690d15
dc.identifier.otherScopus: 84975282891
dc.descriptionMaximilian Konzack, Tim Ophelders, Michel A. Westenberg and Kevin Buchin are supported by the Netherlands Organisation for Scientific Research (NWO) under grant no. 612.001.207 (Maximilian Konzack, Michel A. Westenberg and Kevin Buchin) and grant no. 639.023.208 (Tim Ophelders).en
dc.description.abstractThe analysis of interaction between movement trajectories is of interest for various domains when movement of multiple objects is concerned. Interaction often includes a delayed response, making it difficult to detect interaction with current methods that compare movement at specific time intervals. We propose analyses and visualizations, on a local and global scale, of delayed movement responses, where an action is followed by a reaction over time, on trajectories recorded simultaneously. We developed a novel approach to compute the global delay in subquadratic time using a fast Fourier transform (FFT). Central to our local analysis of delays is the computation of a matching between the trajectories in a so-called delay space. It encodes the similarities between all pairs of points of the trajectories. In the visualization, the edges of the matching are bundled into patches, such that shape and color of a patch help to encode changes in an interaction pattern. To evaluate our approach experimentally, we have implemented it as a prototype visual analytics tool and have applied the tool on three bidimensional data sets. For this we used various measures to compute the delay space, including the directional distance, a new similarity measure, which captures more complex interactions by combining directional and spatial characteristics. We compare matchings of various methods computing similarity between trajectories. We also compare various procedures to compute the matching in the delay space, specifically the Fréchet distance, dynamic time warping (DTW), and edit distance (ED). Finally, we demonstrate how to validate the consistency of pairwise matchings by computing matchings between more than two trajectories.
dc.relation.ispartofInternational Journal of Geographical Information Scienceen
dc.rights© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.en
dc.subjectTrajectpry analysisen
dc.subjectVisual analyticsen
dc.subjectSimilarity measuresen
dc.subjectQA Mathematicsen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.titleVisual analytics of delays and interaction in movement dataen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.Geography & Sustainable Developmenten
dc.contributor.institutionUniversity of St Andrews.School of Geography and Geosciencesen
dc.contributor.institutionUniversity of St Andrews.Bell-Edwards Geographic Data Instituteen
dc.description.statusPeer revieweden

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