Information visualization: perception for design
Information visualization: perception for design
A Fast Adaptive Layout Algorithm for Undirected Graphs
GD '94 Proceedings of the DIMACS International Workshop on Graph Drawing
BEST PAPER: A Knowledge Task-Based Framework for Design and Evaluation of Information Visualizations
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Low-Level Components of Analytic Activity in Information Visualization
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
The Word Tree, an Interactive Visual Concordance
IEEE Transactions on Visualization and Computer Graphics
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
MizBee: A Multiscale Synteny Browser
IEEE Transactions on Visualization and Computer Graphics
A Nested Model for Visualization Design and Validation
IEEE Transactions on Visualization and Computer Graphics
Participatory Visualization with Wordle
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Crowdsourcing graphical perception: using mechanical turk to assess visualization design
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Articulated Planar Reformation for Change Visualization in Small Animal Imaging
IEEE Transactions on Visualization and Computer Graphics
“behaviorism”: a framework for dynamic data visualization
IEEE Transactions on Visualization and Computer Graphics
Cardiogram: visual analytics for automotive engineers
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visualization Rhetoric: Framing Effects in Narrative Visualization
IEEE Transactions on Visualization and Computer Graphics
Design and Evaluation of MagnetViz—A Graph Visualization Tool
IEEE Transactions on Visualization and Computer Graphics
Interpretation and trust: designing model-driven visualizations for text analysis
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Computing Voronoi Treemaps: Faster, Simpler, and Resolution-independent
Computer Graphics Forum
Visual scanning as a reference framework for interactive representation design
Information Visualization - Special issue on Evaluation for Information Visualization
Information visualization evaluation in large companies: challenges, experiences and recommendations
Information Visualization - Special issue on Evaluation for Information Visualization
Empirical Studies in Information Visualization: Seven Scenarios
IEEE Transactions on Visualization and Computer Graphics
Hypermoval: interactive visual validation of regression models for real-time simulation
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Why ask why?: considering motivation in visualization evaluation
Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors - Novel Evaluation Methods for Visualization
Evolutionary visual exploration: evaluation with expert users
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
Hi-index | 0.00 |
We propose an extension to the four-level nested model of design and validation of visualization system that defines the term "guidelines" in terms of blocks at each level. Blocks are the outcomes of the design process at a specific level, and guidelines discuss relationships between these blocks. Within-level guidelines provide comparisons for blocks within the same level, while between-level guidelines provide mappings between adjacent levels of design. These guidelines help a designer choose which abstractions, techniques, and algorithms are reasonable to combine when building a visualization system. This definition of guideline allows analysis of how the validation efforts in different kinds of papers typically lead to different kinds of guidelines. Analysis through the lens of blocks and guidelines also led us to identify four major needs: a definition of the meaning of block at the problem level; mid-level task taxonomies to fill in the blocks at the abstraction level; refinement of the model itself at the abstraction level; and a more complete set of mappings up from the algorithm level to the technique level. These gaps in visualization knowledge present rich opportunities for future work.