2 December 2005 Information Visualisation Interaction Prof. Beat Signer Department of Computer Science Vrije Universiteit Brussel beatsigner.com

Beat Signer - Department of Computer Science - [email protected] 2 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 3 May 2, 2024 Handling Visual Complexity ▪ There are 5 major approaches for dealing with visual complexity ▪ deriving new data to be shown in a view ▪ view manipulation (single view) ▪ reduction (filtering/aggregation of items or attributes) ▪ faceting into multiple views ▪ embed: focus+context (single view)

Beat Signer - Department of Computer Science - [email protected] 4 May 2, 2024 Facet Into Multiple Views

Beat Signer - Department of Computer Science - [email protected] 5 May 2, 2024 Facet Into Multiple Views …

Beat Signer - Department of Computer Science - [email protected] 6 May 2, 2024 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 ▪ …

Beat Signer - Department of Computer Science - [email protected] 7 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 8 May 2, 2024 Exploratory Data Visualizer Example ▪ Linked highlighting (brushing) between views

Beat Signer - Department of Computer Science - [email protected] 9 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 10 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 11 May 2, 2024 Improvise Example

Beat Signer - Department of Computer Science - [email protected] 12 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 13 May 2, 2024 Partitioning Bar Charts Example Single bar chart with grouped bars Aligned small-multiple bar chart views

Beat Signer - Department of Computer Science - [email protected] 14 May 2, 2024 Hierarchical Visual Expression (HiVE)

Beat Signer - Department of Computer Science - [email protected] 15 May 2, 2024 Hierarchical Visual Expression (HiVE) …

Beat Signer - Department of Computer Science - [email protected] 16 May 2, 2024 Hierarchical Visual Expression (HiVE) …

Beat Signer - Department of Computer Science - [email protected] 17 May 2, 2024 Hierarchical Visual Expression (HiVE) …

Beat Signer - Department of Computer Science - [email protected] 18 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 19 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 20 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 21 May 2, 2024 Hierarchical Edge Bundles Example

Beat Signer - Department of Computer Science - [email protected] 22 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 23 May 2, 2024 Embed: Focus+Context

Beat Signer - Department of Computer Science - [email protected] 24 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 25 May 2, 2024 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

Beat Signer - Department of Computer Science - [email protected] 26 May 2, 2024 DOITrees Revisited Example DOITrees Revisited What (Data) Tree. How (Encode) Node-link layout. How (Reduce) Embed: elide, multiple foci. Scale Nodes: hundreds of thousands.

Beat Signer - Department of Computer Science - [email protected] 27 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 28 May 2, 2024 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)

Beat Signer - Department of Computer Science - [email protected] 29 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 30 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 31 May 2, 2024 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.

Beat Signer - Department of Computer Science - [email protected] 32 May 2, 2024 Graph Exploration Example Fisheye lens Magnifying lens Neighbourhood highlighting with layering Neighbourhood highlighting with both layering and Bring and Go interaction

Beat Signer - Department of Computer Science - [email protected] 33 May 2, 2024 Exercise 9 ▪ Interaction and Design Guidelines with Bokeh and Plotly

Beat Signer - Department of Computer Science - [email protected] 34 May 2, 2024 Further Reading ▪ This lecture is mainly based on the book Visualization Analysis & Design ▪ chapter 12 - Facet Into Multiple Views ▪ chapter 14 - Embed: Focus+Context

Beat Signer - Department of Computer Science - [email protected] 35 May 2, 2024 References ▪ Visualization Analysis & Design, Tamara Munzner, Taylor & Francis Inc, (Har/Psc edition), May, November 2014, ISBN-13: 978-1466508910

2 December 2005 Next Lecture Dashboards