A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space‐Time Cubes

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dc.contributor.authorBach, B.en_US
dc.contributor.authorDragicevic, P.en_US
dc.contributor.authorArchambault, D.en_US
dc.contributor.authorHurter, C.en_US
dc.contributor.authorCarpendale, S.en_US
dc.contributor.editorChen, Min and Zhang, Hao (Richard)en_US
dc.date.accessioned2018-01-10T07:36:11Z
dc.date.available2018-01-10T07:36:11Z
dc.date.issued2017
dc.description.abstractWe present the , a descriptive model for visualizations of temporal data. Visualizations are described as operations on the cube, which transform the cube's 3D shape into readable 2D visualizations. Operations include extracting subparts of the cube, flattening it across space or time or transforming the cubes geometry and content. We introduce a taxonomy of elementary space‐time cube operations and explain how these operations can be combined and parameterized. The generalized space‐time cube has two properties: (1) it is purely conceptual without the need to be implemented, and (2) it applies to all datasets that can be represented in two dimensions plus time (e.g. geo‐spatial, videos, networks, multivariate data). The proper choice of space‐time cube operations depends on many factors, for example, density or sparsity of a cube. Hence, we propose a characterization of structures within space‐time cubes, which allows us to discuss strengths and limitations of operations. We finally review interactive systems that support multiple operations, allowing a user to customize his view on the data. With this framework, we hope to facilitate the description, criticism and comparison of temporal data visualizations, as well as encourage the exploration of new techniques and systems. This paper is an extension of Bach .'s (2014) work.We present the , a descriptive model for visualizations of temporal data. Visualizations are described as operations on the cube, which transform the cube's 3D shape into readable 2D visualizations. Operations include extracting subparts of the cube, flattening it across space or time or transforming the cubes geometry and content. We introduce a taxonomy of elementary space‐time cube operations and explain how these operations can be combined and parameterized. The generalized space‐time cube has two properties: (1) it is purely conceptual without the need to be implemented, and (2) it applies to all datasets that can be represented in two dimensions plus time (e.g. geo‐spatial, videos, networks, multivariate data). The proper choice of space‐time cube operations depends on many factors, for example, density or sparsity of a cube.en_US
dc.description.number6
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.12804
dc.identifier.issn1467-8659
dc.identifier.pages36-61
dc.identifier.urihttps://doi.org/10.1111/cgf.12804
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf12804
dc.publisher© 2017 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectspace‐time Cubes
dc.subjecttemporal data
dc.subjectinformation visualization
dc.subjectvideo visualization
dc.subjectnetwork visualization
dc.subjectH.5.m. Information Interfaces and Presentation (e.g. HCI): Miscellaneous
dc.titleA Descriptive Framework for Temporal Data Visualizations Based on Generalized Space‐Time Cubesen_US
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