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Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco

Moritz, Dominik ; Chenglong Wang ; Nelson, Greg L ; Lin, Halden ; Smith, Adam M ; Howe, Bill ; Heer, Jeffrey

IEEE Transactions on Visualization and Computer Graphics, January 2019, Vol.25(1), pp.438-448 [Rivista Peer Reviewed]

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  • Titolo:
    Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco
  • Autore: Moritz, Dominik ; Chenglong Wang ; Nelson, Greg L ; Lin, Halden ; Smith, Adam M ; Howe, Bill ; Heer, Jeffrey
  • Note di contenuto: There exists a gap between visualization design guidelines and their application in visualization tools. While empirical studies can provide design guidance, we lack a formal framework for representing design knowledge, integrating results across studies, and applying this knowledge in automated design tools that promote effective encodings and facilitate visual exploration. We propose modeling visualization design knowledge as a collection of constraints, in conjunction with a method to learn weights for soft constraints from experimental data. Using constraints, we can take theoretical design knowledge and express it in a concrete, extensible, and testable form: the resulting models can recommend visualization designs and can easily be augmented with additional constraints or updated weights. We implement our approach in Draco, a constraint-based system based on Answer Set Programming (ASP). We demonstrate how to construct increasingly sophisticated automated visualization design systems, including systems based on weights learned directly from the results of graphical perception experiments.
  • Fa parte di: IEEE Transactions on Visualization and Computer Graphics, January 2019, Vol.25(1), pp.438-448
  • Soggetti: Data Visualization ; Encoding ; Task Analysis ; Tools ; Visualization ; Programming ; Computational Modeling ; Automated Visualization Design ; Perceptual Effectiveness ; Constraints ; Knowledge Bases ; Answer Set Programming ; Engineering
  • Lingua: Inglese
  • Tipo: Articolo
  • Identificativo: ISSN: 1077-2626 ; E-ISSN: 1941-0506 ; DOI: 10.1109/TVCG.2018.2865240

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