Multi-Dimensional Data Visualization 2

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Transcript Multi-Dimensional Data Visualization 2

Dynamic Queries
cs5984: Information Visualization
Chris North
HomeFinder
Spotfire
Limitations
• Scale:
• Scatterplot screen space: 10,000 – 1,000,000
• Data structures & algorithms: < 50,000
– Poor screen drawing on Filter-out
• A Solution: Query Previews!
• “AND” queries only
• Arbitrary boolean queries?
• A solution: Filter Flow
DQ Algorithm
• Idea: incremental algorithm
• only deal with data items that changed state
• When slider moves:
• Calculate slider delta
• Search in data structure for data items in the delta region
• If slider moved inward (filter out):
– Erase data items from visualization
• Else slider moved outward (filter in):
– Draw data items on visualization
Problem!
Overlapped items,
erases items
underneath too
DQ Data Structures (1)
• Sorted array of the data for each slider
Year:
Delta
• Need counter for each data item = # sliders that filter it
• Attribute Explorer visualizes these counters too!
• O(delta)
DQ Data Structures (2)
• Multi-dimensional data structure
• E.g.: K-d tree, quad-tree, …
• Recursively split space, store in tree structure
• Enables fast range search, O()
DQ Data Structures (2)
• Multi-dimensional data structure
• E.g.: K-d tree, quad-tree, …
• Recursively split space, store in tree structure
• Enables fast range search, O(logn)
Delta
Erasure Problem
• Each pixel has counter = number of items
• Can visualize this for density!
• Z-buffer?
• Redraw local area only
Filter-Flow
Betty
Catherine
Edna
Freda
Grace
Hilda
Judy
Marcus
Tom
Influence/Attribute Explorer
• Tweedie, Spence, “Externalizing Abstract
Mathematical Models” (Influence/Attribute
Explorer)
• Z.Wang, Ali
Query Previews
• Doan, “Query Previews”
• Anuj, Vikrant
Thurs
• Book chapter 9
• Thurs: Multi-D Functions
• Feiner, “Worlds within Worlds”
» sandip, ben
• vanWijk “HyperSlice”
» kumar, kunal
Next Week
• Tues: 1-D
• Plaisant, “Lifelines”
» mahesh, jon
• Eick, “SeeSoft”
» jeevak, alex
• Thurs: 1-D
• Mackinlay, “Perspective Wall”
» ahmed, ganesh
• Hibino, “MMVIS”
» atul, dananjan
Project Proposal
• Project list…
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Due thurs
Team members
Project idea
Schedule
Presentations
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Use pictures, pictures, pictures, pictures, …
Use text only to hammer home key points
What’s the take-home message?
~2 main points
Motivate!
• In class:
• Goal 1: understand visualization (mapping, simple examples)
• Goal 2: strengths, weaknesses, scale, HCI metrics, “insight”
• Time is short: 10 min = ~5 slides, practice out loud
Implementation detail crap
• The first step of processing requires the construction of
several tree and graph structures to store the database.
• System then builds visualization of data by mapping data
attributes of graph items to graphical attributes of nodes
and links in the visualization windows on screen.
• More boring stuff nobody is ever going to read here or if
they do they wont understand it anyway so why bother.
• If they do read it then they most certainly will not be
listening to what you are saying so why bother give a talk?
Why not just sit down and let everybody read your slides
or just hand out the paper and then say ‘thank you’.
• This person needs to take Dr. North’s info vis class.
Discusser
• Ask questions:
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what do you think about this visualization?
scale
Good, bad?
Comparisons to other vis
Improvements
• Have some possible answers
• Spark controversy!