Work

Manipulable Semantic Components: A Computational Representation of Data Visualization Scenes

Year: 2024

Type: article

Abstract: Various data visualization applications such as reverse engineering and interactive authoring require a vocabulary that describes the structure of visualization scenes and the procedure to manipulate them. A few scene abstractions have been proposed, but they are restricted to specific applications for a limited set of visualization types. A unified and expressive model of data visualization scenes for different applications has been missing. To fill this gap, we present Manipulable Semantic Components (MSC), a computational representation of data visualization scenes, to support applications in scene understanding and augmentation. MSC consists of two parts: a unified object model describing the structure of a visualization scene in terms of semantic components, and a set of operations to generate and modify the scene components. We demonstrate the benefits of MSC in three applications: visualization authoring, visualization deconstruction and reuse, and animation specification.

Source: IEEE Transactions on Visualization and Computer Graphics

DOI: 10.1109/tvcg.2024.3456296

Authors: Zhicheng Liu, Chen Chen, John Hooker

Institution: University of Maryland, College Park

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Award: CAREER: Manipulable Semantic Components in Data Visualization Design