Toward a Deeper Understanding of the Role of Interaction in Information Visualization

By Ji Soo Yi, Youn Ah Kang, John T. Stasko, Julie A. Jacko. IEEE Transactions on Visualization and Computer Graphics, 2007

1,237 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/e30ecedc7f5fa639915e95f153d9561a3da0962f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computer Vision and Pattern Recognition

In Sociology and Political Science

Citations in the corpus

Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization (2011, background): “review a large number of visualization systems to better understand the role of interaction in visualization [60].”
A survey on information visualization: recent advances and challenges (2014, neutral): “[166] provided a comprehensive survey to”
Combining Design and Performance in a Data Visualization Management System (2017, background): “…that the primary classes of interaction techniques— interactive selection, changing visual encodings, adding or removing marks, coordinated views, and undo/redo—that are common across several interaction taxonomies [57, 63] can be readily expressed in DeVIL based on the constructs presented above.”
A Nested Model for Visualization Design and Validation (2009, background): “The theory of interaction design for visualization is less well developed, but is starting to appear [23, 52].”
An Information-theoretic Framework for Visualization (2010, background): “Let us consider a non-linear mapping function, which maps R1 : [0,63] to [0,31], R2 : [64,127] to [32,47], R3 : [128,191] to [48,55], and R4 : [192,255] to [56,63].”
Reactive Vega: A Streaming Dataflow Architecture for Declarative Interactive Visualization (2016, methodology): “Example declarative interactive visualizations [32] that cover an existing taxonomy of interaction techniques [41]: (a) Reconfigure with an Index Chart; (b) Explore by panning & zooming; (c) Select & Connect with brushing & linking; (d) Abstract/Elaborate with overview+detail;”
Mastering the Information Age - Solving Problems with Visual Analytics (2010, background): “We should think about the users’ intentions when designing interactive systems More recently Yi et al.[126] identified the following categories of interaction:”
Vega-Lite: A Grammar of Interactive Graphics (2018, background): “Moreover, selections, transformations, and their application to visual encodings decompose interaction into a parametric design space.”
Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation (2008, positive): “Furthermore, the highly interactive nature of the method is designed to promote direct and evocative control and overview of the data, supporting both reconfigure and connect interaction [42].”
Science Mapping: A Systematic Review of the Literature (2017, background): “…networks (Shannon et al., 2003), the ground breaking work of visual analytics (Thomas & Cook, 2005), Many Eyes – the popular Web-based visualization platform (Viégas et al., 2007), and a framework of seven types of interaction techniques in information visualization (Yi et al., 2007) (Figure 23).”
Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey (2013, neutral): “Navigation is an important task in visualization and can be done manually [40], [46], automatically [47], or computationally assisted [48], [49].”
Visual Analytics: Definition, Process, and Challenges (2008, neutral): “Development of novel interaction algorithms incorporating machine recognition of the actual user intent and appropriate adaptation of main display parameters such as the level of detail, data selection and aggregation, etc. by which the data is presented[44].”
Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective (2010, background): “In a similar vein to previous work on interaction [14, 66], we emphasize human intentionality as a basis for understanding interaction in InfoVis.”