FlockViz: A Visualization Technique to Facilitate Multi-dimensional Analytics of Spatio-temporal Cluster Data

dc.contributor.authorHossain, Mohammad Zahid
dc.contributor.examiningcommitteeWang, Yang (Computer Science) Hossain, Ekram (Electrical and Computer Engineering)en_US
dc.contributor.supervisorIrani, Pourang (Computer Science)en_US
dc.date.accessioned2014-05-26T13:08:44Z
dc.date.available2014-05-26T13:08:44Z
dc.date.issued2014-05-26
dc.degree.disciplineComputer Scienceen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractVisual analytics of large amounts of spatio-temporal data is challenging due to the overlap and clutter from movements of multiple objects. A common approach for analyzing such data is to consider how groups of items cluster and move together in space and time. However, most methods for showing Spatio-temporal Cluster (STC) properties, concentrate on a few dimensions of the cluster (e.g. the cluster movement direction or cluster density) and many other properties are not represented. Furthermore, while representing multiple attributes of clusters in a single view existing methods fail to preserve the original shape of the cluster or distort the actual spatial covering of the dataset. In this thesis, I propose a simple yet effective visualization, FlockViz, for showing multiple STC data dimensions in a single view by preserving the original cluster shape. To evaluate this method I develop a framework for categorizing the wide range of tasks involved in analyzing STCs. I conclude this work through a controlled user study comparing the performance of FlockViz with alternative visualization techniques that aid with cluster-based analytic tasks. Finally the exploration capability of FlockViz is demonstrated in some real life data sets such as fish movement, caribou movement, eagle migration, and hurricane movement. The results of the user studies and use cases confirm the advantage and novelty of the novel FlockViz design for visual analytic tasks.en_US
dc.description.noteOctober 2014en_US
dc.identifier.urihttp://hdl.handle.net/1993/23591
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectData Visualizationen_US
dc.subjectTheoretical design and implementation of representing dataen_US
dc.subjectSpatio-temporal dataen_US
dc.subjectMovement data visualization such as vehicle movement, animal migration etcen_US
dc.subjectCluster visualizationen_US
dc.subjectHow to visualize clusters in Spatio-temporal dataen_US
dc.subjectMulti-Data analysisen_US
dc.subjectMulti-dimensional data visualization to ease analytic tasksen_US
dc.titleFlockViz: A Visualization Technique to Facilitate Multi-dimensional Analytics of Spatio-temporal Cluster Dataen_US
dc.typemaster thesisen_US
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