2 D cs 5984 Information Visualization Chris North
- Slides: 26
2 -D cs 5984: Information Visualization Chris North
Powers of 10
Quiz • What is the “keyhole problem”? • • 4 strategies to solve the keyhole problem for 1 D? • • f+c Detail only Zoom O+d
Information Types • • Multi-dimensional: databases, … 1 D: timelines, … 2 D: maps, … 3 D: volumes, … Hierarchies/Trees: directories, … Networks/Graphs: web, … Document collections: digital libraries, …
2 -D • • • Image browsing Maps Photos 2 d funcs A powerpiont slide
2 -D: large spaces • http: //terraserver. homeadvisor. msn. com/image. asp? S=10&T=1&X=2689&Y=20639&Z=17&W=2
Tasks? • • • Search for target Patterns Distance Aesthetics Routefinding
Detail Only • Typical image browser MS Photo. Editor • Typical map browser mapquest. com
Zooming: Pad++ • Infinitely zoomable surface • Layout information in 2 d+scale • Interaction: pan+zoom • Need more info? Just zoom in! • Jazz (Bederson et al. )
Pad++ examples • Authored spaces (user specified layouts) • E. g: filesystem replacement? , presentations, stories • Hi. Note, Kidpad • http: //www. cs. umd. edu/hcil/jazz/play/ • http: //vtopus. cs. vt. edu/~north/infoviz/hinoteapplet. html • Counterpoint: powerpoint with zooming • http: //www. cs. umd. edu/hcil/counterpoint/
Pad++ examples • Automated layouts • E. g: File system, web history
Pad++ examples • In visualization
Space-Scale
Pad++ on edge Info surface • Like ray-tracing zoom window
Semantic Zooming • Zooming in, red object turns to blue label
Good/Bad • Good: • • “step back” to get overview “step forward” for more details Infinite space for more details Visual scale conceptual scale • Bad: • get lost because of no overview • Need work on input device
Overview+Detail Overview: Detail: Square in overview coupled to scroll bars of detail • Zoom factor = 6
Multiple levels = large scale overview intermediate view detail view • Zoom factor = 10*10*10=1000
Multiple Foci
Multiple Overviews • Can have different data types in each view Color slice Ca. T scan
O+D vs Detail-Only • Beard & Walker: 2 D • Chimera: trees • North: 1 D (lists) • Scrollbars are bad!
Intermediate views? • Plaisant, “When an Intermediate view matters” • abhi, sandeep Overview ? Detail view
Translucency • Lieberman, “Macroscope: Powers of Ten Thousand” • anusha, mrinmayee
2 -D + Attributes • Dynamaps: dynamic queries on maps
Assignment • Thurs: 2 -D, focus+context • Robertson, “Document Lens” » priya, parool • Leung, “Bifocal displays” » alex, qiang • Homework #2 due thurs
Next Week • tues: Visual Overview Strategies • Stasko, “Information Mural” » ben, ahmed • Rayson, “Aggregate Towers” » anil, supriya • thurs: Multiple View Strategies • Chi, “Visualization Spreadsheet” » mudita, abhi • North, “Snap-Together Visualization” » varun, kumarl
- Da form 5823
- Ece 5984
- Dr chris north
- Chris north properties
- Information visualization ppt
- Introduction to information visualization
- Information visualization
- True north vs magnetic north
- Integrated care system north east
- Chapter 14 lesson 1
- The north pole ____ a latitude of 90 degrees north
- Prim's algorithm visualization
- Ocean data visualization
- Vli demo tool
- Red-black tree visualization
- Horspool algorithm visualization
- Spatial visualization training
- Visualization robot simulation
- Photoshop scientific notation
- Taxonomy chart
- Google visualization api query language
- 2d array visualization
- Weka visualization
- Shneiderman's mantra
- Data visualization rules of thumb
- Value chain visualization
- Huffman code visualization