Difference between revisions of "CS 4460"
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+ | {{DISPLAYTITLE:CS 4460 - Introduction to Information Visualization}} |
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+ | [[Category:Courses|^CS^CS]] |
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'''CS 4460''', formally known as '''Introduction to Information Visualization''' or Infovis for short, is a 3 credit hour [[Computer Science]] course about data visualization and interactivity. The course counts as both a Human-Centered Technology elective for the [[People]] thread and a Media Technologies elective for the [[Media]] thread. |
'''CS 4460''', formally known as '''Introduction to Information Visualization''' or Infovis for short, is a 3 credit hour [[Computer Science]] course about data visualization and interactivity. The course counts as both a Human-Centered Technology elective for the [[People]] thread and a Media Technologies elective for the [[Media]] thread. |
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== Topic List == |
== Topic List == |
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+ | The following is a high level overview of the topics covered during the course. |
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+ | * Representing multivariate data in two dimensions |
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− | {{Collapsed_Top| |
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⚫ | |||
− | === Lecture Topic List === |
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+ | * Ethics of visual design |
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− | }} |
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− | * Infovis overview |
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− | * Multivariate data and charts |
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− | ** Parallel coordinates |
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− | ** Attribute explorer |
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− | ** Scatterplot matrix |
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− | ** Star plots |
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− | ** Star coordinates |
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− | ** Small multiples |
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− | ** Mosaic plots |
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− | ** Attribute explorer |
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− | ** Dust & magnet |
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− | * Perception and Gestalt |
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− | ** Two-stage model of perceptual processing |
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− | * Visual chart design guidelines and principles (Tufte and Few) |
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− | ** Graphical integrity |
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− | ** Lie factor |
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− | ** Data-ink ratio |
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− | * Tasks and analysis |
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− | ** Schneiderman's task x datatype taxonomy |
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− | ** Schneiderman's mantra (overview first, zoom and filter, details on demand) |
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− | ** Sensemaking loop |
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− | ** Data frame model |
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− | ** ICE-T evaluation |
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* User interaction |
* User interaction |
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− | ** User Interaction taxonomies (Yi et al.) |
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− | ** Querying and dynamic query |
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− | ** Query controls |
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* Text visualization |
* Text visualization |
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− | ** Information retrieval |
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− | ** Visualizing search queries |
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− | ** Word clouds |
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− | ** Word trees |
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− | ** Phrase nets |
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− | ** Theme/topic analysis |
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* Graphs and networks |
* Graphs and networks |
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− | ** Schneiderman's Netviz Nirvana |
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− | ** Graph/Network task taxonomy |
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− | ** Graph layout approaches |
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− | ** Scale challenges |
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− | ** Graph querying |
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* Hierarchies and trees |
* Hierarchies and trees |
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− | ** Node-link diagrams |
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− | *** SpaceTree |
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− | *** Indented lists |
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− | *** Hyperbolic browser |
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− | *** Flextree |
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− | ** Space-filling representations |
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− | *** Icicle plot |
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− | *** Treemap |
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− | *** Context treemap |
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* Storytelling |
* Storytelling |
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− | ** Communicating insights |
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− | ** Hans Rosling |
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− | ** Data-driven storytelling |
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− | ** Exploration vs explanation |
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* Visual analytics |
* Visual analytics |
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− | ** Integration of data mining and machine learning algorithms |
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− | ** Time taxonomy |
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− | ** Querying time-series data |
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* Explainability |
* Explainability |
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+ | * Evaluating effectiveness |
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− | * Evaluation |
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− | ** Utility vs usability |
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− | ** Schneiderman & Plaisant's MILC technique (multi-dimensional, in-depth, long-term case study) |
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− | ** ICE-T evaluation |
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* Data humanism |
* Data humanism |
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* Geospatial visualization |
* Geospatial visualization |
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+ | * Visualization on small-scale and large-scale devices |
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− | ** Geometry |
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+ | |||
− | *** Modifiable areal unit problem (MAUP) |
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+ | {| role="presentation" class="mw-collapsible mw-collapsed" |
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− | ** Cartograms |
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+ | | |
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− | ** Scalar fields and isolines |
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− | * Post-WIMP visualization; visualization tools and toolkits |
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+ | |- |
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− | ** Vis on other devices |
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− | *** Small-scale (mobile/touch) |
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− | *** Large-scale (large/multiple displays) |
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− | {{Collapsed_Bottom}} |
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− | {{Collapsed| |
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* Lab 1: Intro to HTML, CSS, and SVG |
* Lab 1: Intro to HTML, CSS, and SVG |
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* Lab 7C: Scrollytelling |
* Lab 7C: Scrollytelling |
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* Lab 7D: Interactive Visual Comparison |
* Lab 7D: Interactive Visual Comparison |
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== Class Structure == |
== Class Structure == |
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= Resources = |
= Resources = |
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+ | https://va.gatech.edu/courses/cs4460/ |
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− | WIP |
Latest revision as of 18:46, 5 December 2022
CS 4460, formally known as Introduction to Information Visualization or Infovis for short, is a 3 credit hour Computer Science course about data visualization and interactivity. The course counts as both a Human-Centered Technology elective for the People thread and a Media Technologies elective for the Media thread.
The course surveys a breadth of visualization approaches and interaction methods, and outlines how the research space has evolved over time. Students learn principles of effective visual communication, implement visualizations with D3.js, and analyze and critique the merits and limitations of different visualization approaches.
Topic List[edit | edit source]
The following is a high level overview of the topics covered during the course.
- Representing multivariate data in two dimensions
- Perceptual processing and Gestalt principles
- Ethics of visual design
- Mental models and sensemaking
- User interaction
- Text visualization
- Graphs and networks
- Hierarchies and trees
- Storytelling
- Visual analytics
- Time series and temporal data
- Explainability
- Evaluating effectiveness
- Data humanism
- Geospatial visualization
- Visualization on small-scale and large-scale devices
Lab Topic List (Alex Endert, Fall 2021)[edit | edit source] |
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Class Structure[edit | edit source]
WIP
Prerequisite Knowledge[edit | edit source]
A formal requirement of CS 1332 with a C or higher is required to take this class. This class is only offered to students with junior or senior status.
Although no prior knowledge of HTML, CSS, and JavaScript is necessary, some familiarity with HTML, CSS, and JavaScript may help during labs.
Scheduling[edit | edit source]
WIP