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Interaction - Lecture 10 - Information Visualisation (4019538FNR)

Interaction - Lecture 10 - Information Visualisation (4019538FNR)

This lecture forms part of the course Information Visualisation given at the Vrije Universiteit Brussel.

Beat Signer
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May 04, 2023
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  1. 2 December 2005
    Information Visualisation
    Interaction
    Prof. Beat Signer
    Department of Computer Science
    Vrije Universiteit Brussel
    beatsigner.com

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  2. Beat Signer - Department of Computer Science - [email protected] 2
    May 4, 2023
    Interaction
    ▪ Interactivity is necessary for vis tools handling complexity
    ▪ limitations of people and displays make it impossible to show a
    large dataset at once
    ▪ change level of details
    ▪ show different aspects of a dataset
    ▪ different representations and summaries of data
    ▪ different presentations of data

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  3. Beat Signer - Department of Computer Science - [email protected] 3
    May 4, 2023
    Handling Visual Complexity
    ▪ There a 5 major approaches for dealing with
    visual complexity
    ▪ deriving new data to be shown in a view
    ▪ view manipulation (single view)
    ▪ reduction (items or attributes)
    ▪ faceting into multiple views
    ▪ embed: focus+context (single view)

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  4. Beat Signer - Department of Computer Science - [email protected] 4
    May 4, 2023
    Facet Into Multiple Views

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  5. Beat Signer - Department of Computer Science - [email protected] 5
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    Facet Into Multiple Views …

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  6. Beat Signer - Department of Computer Science - [email protected] 6
    May 4, 2023
    Facet Into Multiple Views …
    ▪ Faceting information into multiple views to deal with
    visual complexity
    ▪ Juxtapose views side by side
    ▪ coordination of views to create linked views (multiple views)
    - sharing of encoding
    - sharing of data
    - synchronisation of navigation
    ▪ arrangement of views
    ▪ when to show views
    ▪ Superimpose views as layers
    ▪ partitioning of elements between layers
    ▪ number of layers
    ▪ …

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  7. Beat Signer - Department of Computer Science - [email protected] 7
    May 4, 2023
    Sharing of Encoding
    ▪ Shared encoding views
    ▪ all channels handled the same for an identical visual encoding
    ▪ Multiform views (multiple views)
    ▪ some aspects of the visual encoding different between views
    ▪ each view might show a subset of attributes to avoid visual clutter
    ▪ Linked highlighting (brushing)
    ▪ items interactively selected in one view are highlighted with the
    same colour in all other views
    - see how region that is continous in one view is distributed in another

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  8. Beat Signer - Department of Computer Science - [email protected] 8
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    Exploratory Data Visualizer Example
    ▪ Linked highlighting (brushing) between views

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  9. Beat Signer - Department of Computer Science - [email protected] 9
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    Sharing of Data
    ▪ Shared data
    ▪ each view shows all the data
    ▪ Overview-detail (subset)
    ▪ one view shows entire dataset (overview) and another view
    shows detailed information about a selected subset of the data
    ▪ different possible combinations of views
    - subset data and shared encoding (e.g. bird's-eye map)
    - multiform views (e.g. details-on-demand view)
    ▪ Small multiples
    ▪ multiple views with same visual encoding but different partitions of
    the data
    - often aligned in matrix to support comparison between datasets
    - limited screen estate to show many views next to each other

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  10. Beat Signer - Department of Computer Science - [email protected] 10
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    Bird's-Eye Maps Example
    Bird's-Eye Maps
    What(Data) Geographic.
    How(Encode) Use given geographic information.
    How(Facet) Partition into two views with same encoding, overview-detail.
    How (Reduce) Navigate.

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  11. Beat Signer - Department of Computer Science - [email protected] 11
    May 4, 2023
    Improvise Example

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  12. Beat Signer - Department of Computer Science - [email protected] 12
    May 4, 2023
    Partition Into Views
    ▪ Divide data up between views based on attributes
    ▪ partitioning attribute typically a categorical variable with limited
    number of values (levels)
    ▪ List alignment or matrix alignment
    ▪ Recursive subdivision
    ▪ partitioning used in an exploratory way
    ▪ user can reconfigure the display to see different choices of
    partitioning variables

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  13. Beat Signer - Department of Computer Science - [email protected] 13
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    Partitioning Bar Charts Example
    Single bar chart with grouped bars Aligned small-multiple bar chart views

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  14. Beat Signer - Department of Computer Science - [email protected] 14
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    Hierarchical Visual Expression (HiVE)

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  15. Beat Signer - Department of Computer Science - [email protected] 15
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    Hierarchical Visual Expression (HiVE) …

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  16. Beat Signer - Department of Computer Science - [email protected] 16
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    Hierarchical Visual Expression (HiVE) …

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  17. Beat Signer - Department of Computer Science - [email protected] 17
    May 4, 2023
    Hierarchical Visual Expression (HiVE) …

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  18. Beat Signer - Department of Computer Science - [email protected] 18
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    Superimpose Views as Layers
    ▪ Design choices when superimposing multiple layers
    ▪ number of layers
    - often just two layers (e.g. background and foreground layer)
    ▪ distinction of layers
    - use different and non-overlapping range of the visual channels
    ▪ static vs. dynamic layers
    ▪ partitioning of items into layers

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  19. Beat Signer - Department of Computer Science - [email protected] 19
    May 4, 2023
    Cartographic Layering Example
    Cartographic Layering
    What(Data) Geographic.
    How(Encode) Area marks for regions (water, parks, other land), line marks for roads,
    categorical colourmap.
    How(Facet) Superimpose: static layers distinguished with colour saturation, colour
    luminance, and size channels.

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  20. Beat Signer - Department of Computer Science - [email protected] 20
    May 4, 2023
    Superimposed Line Charts Example
    Superimposed Line Charts
    What(Data) Multidimensional table: one ordered key attribute (time), one
    categorical key attribute (machine), one quantitative value attribute
    (CPU utilisation).
    How(Encode) Line charts, coloured by machine attribute.
    How(Facet) Superimpose: static layers, distinguished with colour.
    Scale Ordered key attribute: hundreds. Categorical key attribute: one dozen.

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  21. Beat Signer - Department of Computer Science - [email protected] 21
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    Hierarchical Edge Bundles Example

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  22. Beat Signer - Department of Computer Science - [email protected] 22
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    Hierarchical Edge Bundles Example …
    Hierarchical Edge Bundles
    What(Data) Compound graph: network, hierarchy whose leaves are nodes in
    network.
    How(Encode) Back layer shows hierarchy with containment marks coloured grey,
    middle layer shows network links coloured red-green, front layer shows
    nodes coloured grey.
    How(Facet) Superimpose static layers, distinguished with colour.

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  23. Beat Signer - Department of Computer Science - [email protected] 23
    May 4, 2023
    Embed: Focus+Context

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  24. Beat Signer - Department of Computer Science - [email protected] 24
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    Embed: Focus+Context
    ▪ Single view embedding detailed information (focus) and
    overview information (context)
    ▪ avoid potential for disorientation that might result from navigation
    techniques such as geometric zooming
    ▪ Focus changes dynamically based on user interaction

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  25. Beat Signer - Department of Computer Science - [email protected] 25
    May 4, 2023
    Elide and Superimpose Data
    ▪ Some items are completely omitted from the view while
    others are summarised (context)
    ▪ dynamic aggregation for context
    ▪ only focus items shown in detail
    ▪ Superimposed layers can also be used for focus and
    context
    ▪ e.g. toolglass and magic lens example

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  26. Beat Signer - Department of Computer Science - [email protected] 26
    May 4, 2023
    DOITrees Revisited Example
    DOITrees Revisited
    What(Data) Tree.
    How(Encode) Node-link layout.
    How(Reduce) Embed: elide, multiple foci.
    Scale Nodes: hundreds of thousands.

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  27. Beat Signer - Department of Computer Science - [email protected] 27
    May 4, 2023
    Toolglass and Magic Lenses Example
    Toolglass and Magic Lenses
    What(Data) Spatial, quantitative curvature attribute across surface.
    How(Encode) Use given, colour by curvature.
    How(Reduce) Embed: superimpose.

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  28. Beat Signer - Department of Computer Science - [email protected] 28
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    Distortion
    ▪ Geometric distortion of contextual regions to make more
    space for details in focus region
    ▪ Design choices
    ▪ number of focus regions
    ▪ shape of focus region (e.g. radial or rectangular)
    ▪ global or local focus region
    ▪ interaction metaphor (e.g. movable lenses)
    ▪ Costs and benefits
    ▪ good for topological network structures
    ▪ length judgements severely impaired
    ▪ users might not be aware of distortion (potential misunderstanding)

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  29. Beat Signer - Department of Computer Science - [email protected] 29
    May 4, 2023
    Fisheye Lens Example
    Fisheye Lens
    What(Data) Any data.
    How(Encode) Any layout.
    How(Reduce) Embed: distort with fisheye; single focus, local radial region,
    moveable lens interaction metaphor.

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  30. Beat Signer - Department of Computer Science - [email protected] 30
    May 4, 2023
    Hyperbolic Geometry Example
    Hyperbolic Geometry
    What(Data) Tree or network.
    How(Encode) Hyperbolic layout.
    How(Reduce) Embed: distort by projecting from hyperbolic to Euclidean space;
    single global radial focus; hyperbolic translation interaction metaphor.

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  31. Beat Signer - Department of Computer Science - [email protected] 31
    May 4, 2023
    Nonlinear Magnification Fields Example
    Nonlinear Magnification Fields
    What(Data) Any data.
    How(Encode) Any layout.
    How(Reduce) Embed: distort with magnification fields; multiple foci, local arbitrary
    regions, lens or stretch or data-driven interaction metaphors.

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  32. Beat Signer - Department of Computer Science - [email protected] 32
    May 4, 2023
    Graph Exploration Example
    Fisheye lens Magnifying lens
    Neighbourhood highlighting with layering
    Neighbourhood highlighting
    with both layering and Bring
    and Go interaction

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  33. Beat Signer - Department of Computer Science - [email protected] 33
    May 4, 2023
    Exercise 9
    ▪ Interaction and Design Guidelines
    with Bokeh and Plotly

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  34. Beat Signer - Department of Computer Science - [email protected] 34
    May 4, 2023
    Further Reading
    ▪ This lecture is mainly based on the
    book Visualization Analysis & Design
    ▪ chapter 12
    - Facet Into Multiple Views
    ▪ chapter 14
    - Embed: Focus+Context

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  35. Beat Signer - Department of Computer Science - [email protected] 35
    May 4, 2023
    References
    ▪ Visualization Analysis & Design, Tamara
    Munzner, Taylor & Francis Inc, (Har/Psc edition),
    May, November 2014,
    ISBN-13: 978-1466508910

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  36. 2 December 2005
    Next Lecture
    Dashboards

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