May 5, 2022 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
May 5, 2022 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)
May 5, 2022 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 ▪ …
May 5, 2022 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
May 5, 2022 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
May 5, 2022 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.
May 5, 2022 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
May 5, 2022 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
May 5, 2022 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.
May 5, 2022 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.
May 5, 2022 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
May 5, 2022 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
May 5, 2022 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.
May 5, 2022 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)
May 5, 2022 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.
May 5, 2022 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.
May 5, 2022 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.