Visualization-by-Sketching: An Artist's Interface for Creating Multivariate Time-Varying Data Visualizations

David Schroeder, Daniel F Keefe

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

We present Visualization-by-Sketching, a direct-manipulation user interface for designing new data visualizations. The goals are twofold: First, make the process of creating real, animated, data-driven visualizations of complex information more accessible to artists, graphic designers, and other visual experts with traditional, non-technical training. Second, support and enhance the role of human creativity in visualization design, enabling visual experimentation and workflows similar to what is possible with traditional artistic media. The approach is to conceive of visualization design as a combination of processes that are already closely linked with visual creativity: sketching, digital painting, image editing, and reacting to exemplars. Rather than studying and tweaking low-level algorithms and their parameters, designers create new visualizations by painting directly on top of a digital data canvas, sketching data glyphs, and arranging and blending together multiple layers of animated 2D graphics. This requires new algorithms and techniques to interpret painterly user input relative to data "under" the canvas, balance artistic freedom with the need to produce accurate data visualizations, and interactively explore large (e.g., terabyte-sized) multivariate datasets. Results demonstrate a variety of multivariate data visualization techniques can be rapidly recreated using the interface. More importantly, results and feedback from artists support the potential for interfaces in this style to attract new, creative users to the challenging task of designing more effective data visualizations and to help these users stay "in the creative zone" as they work.

Original languageEnglish (US)
Article number7185456
Pages (from-to)877-885
Number of pages9
JournalIEEE Transactions on Visualization and Computer Graphics
Volume22
Issue number1
DOIs
StatePublished - Jan 31 2016

Bibliographical note

Publisher Copyright:
© 1995-2012 IEEE.

Keywords

  • Brushes
  • Data visualization
  • Image color analysis
  • Painting
  • Paints
  • Visualization

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