Information Visualization• Increase the likelihood of spotting unexpected ... numbers can be...
Transcript of Information Visualization• Increase the likelihood of spotting unexpected ... numbers can be...
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Information Visualization
Dianna XuDepartment of Computer Science
Bryn Mawr College
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Big Data
• The amount of available data is quickly outpacing our ability to understand and use it in meaning full ways.
• The eventual solution to big data is likely really good black boxes.
• Black boxes only give answers if you know right questions to ask.
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Visualization and Explorative Data Analysis
• Visualization allows one to view things in global context.
• Increase the likelihood of spotting unexpected trends and perspectives.
• Allows new questions to be asked.• The life cycle of explorative data analysis with visualization is likely an iterative process
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Visualization Types
• Scientific visualization– numerical, high precision and has relative simple spatial relationships
– accurate representation of numerical proportions and realistic rendering of physical properties
• Data visualization– social/economical data– highly categorical and have strong association with physical locations/coordinates on the map
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Information Visualization
• Arbitrary or complex relationships with no clearly prescribed spatial representation choices
• Abstract representation techniques• Communication is an important goal• infoviz versus “data journalism”
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The Visualization Process
• Acquire• Parse• Filter• Mine• Represent• Refine • Interact
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Mapping Numbers
• How to represent numbers with visual primitives so that the relative values of numbers can be quickly deduced from visual cues
• Example with simple data set– 255 integers valued 0‐99– collected on twitter as random numbers
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Mapping Numbers
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Mapping Numbers
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Information Dimensions
• A fundamental challenge of visualization design is to add more information dimensions without introducing clutter
• Display is 2D• Going 3D is not a solution
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Time Series
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Stacked Graph
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Heat Map
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Birthdays
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Proportional Symbols
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Twitter Frequencies
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World Cloud
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Packing
• Randomized placement allowing overlap• Randomized greedy algorithm
– fit the largest tiles first at randomly chosen location
– if there is overlap, try again
• Exhaustive search• Exhaustive search guided by space filling curve
– Spiral, Peano, Hilbert, etc
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Spiral
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Intersection via Pixel Buffer
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Map‐based
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Coordinate Conversions
• Translate physical coordinates to drawing coordinates
• Geographical coordinates• Modern world map empolying a Universal Transverse Mercator (UTM) projection
• What if your data comes with names of countries or states?
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A Choropleth Map
• Thematic maps require that you color an entire area (state) with a particular color
• Need polygonal outlines of a state• A US political map of SVG format contains coordinates as an XML file
• Combine with Google Maps API to create interactive map overlay
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States as Polygons
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Google Map Overlay
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Foursquares Check‐ins
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Parallel Coordinates
• High dimensional numerical data• PNC Christmas Price Index
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Parallel Coordinates
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Brushing
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Citeology
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Parallel Sets
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TreeMap
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More Levels
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Radial
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Tree
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Radial Tree
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Hyperbolic Tree
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Focus+Context
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Network/Graph‐based
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Chord Diagrams
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Circular Layouts
• Enjoyed great popularity lately• We are drawn to circles
– symmetry– aesthetics– perceived novelty
• Not always justified by increased readability• Human visual perception supports only rough comparison of areas and angles
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Naming Names
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Data Analysis
• Unstructured data• A lot of it
• Dimension reduction• Cluster analysis• Statistical methods• Network models and optimization• Graph theory