Snap-together visualization: a user interface for coordinating visualizations via relational schemata
By Chris North, Ben Shneiderman. International Working Conference on Advanced Visual Interfaces, 2000
355 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/1274c1f7a556f968cec299b8b8ba279e46e6f8eb
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Eugene Wu
- John T. Stasko
- Joseph M Hellerstein
- Dominik Moritz
- Andreas Paepcke
- Jeffrey Heer
- J. C. Roberts
- Sean Kandel
In Computer Vision and Pattern Recognition
- Jeffrey Heer
- Dominik Moritz
- Zhicheng Liu
- Kanit Wongsuphasawat
- Arvind Satyanarayan
- John T. Stasko
- Joseph M Hellerstein
- Andreas Paepcke
In Signal Processing
- Eugene Wu
- Jeffrey Heer
- Zhicheng Liu
- Kanit Wongsuphasawat
- Dominik Moritz
- John T. Stasko
- Joseph M Hellerstein
- Andreas Paepcke
Citations in the corpus
- Vega-Lite: A Grammar of Interactive Graphics (2018, background): “For example, in Snap-Together Visualization [17], multiple views are coordinated via “primary-” and “foreign-key actions,” which propagate selected data tuples from one view to the others.”
- Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective (2010, background): “The Snap-together system [40, 41] explores users’ ability to construct coordinated visualizations.”
- Guidelines for using multiple views in information visualization (2000, background): “Due to space constraints, we can not review all multiple view systems; however, many other interesting examples appear in [20].”
- Combining Design and Performance in a Data Visualization Management System (2017, methodology): “On one hand, existing visualization optimization techniques [31, 33, 34, 37, 47, 52] are specialized for specific scenarios that are neither applicable nor most suitable for every interactive visualization design.”
- Profiler: integrated statistical analysis and visualization for data quality assessment (2012, background): “Through linked highlighting (“brushing & linking”), coordinated multiple views enable assessment of relationships between data dimensions [22, 36].”
- State of the Art: Coordinated & Multiple Views in Exploratory Visualization (2007, methodology): “Tools like Tioga [67], LinkWinds [32], DEVise [38], CommonGIS [5], Snap-Together [42] GeoVISTA studio [69] and Improvise [77] all allow the user to define and browse highly-coordinated visualizations.”