Rules of Visual Encoding
No unjus3fied 3D: Power of the plane
• high-ranked spa3al posi3on channels: planar spa3al posi3on – not depth!
No unjus3fied 3D: Danger of depth • we don’t really live in 3D: we see in 2.05D • acquire more info on image plane quickly from eye movements –acquire more info for depth slower, from head/body mo3on
Occlusion hides informa3on
• Occlusion • interac3on complexity
[Distor(onViewingTechniques for 3D Data.Carpendale et al.InfoVis1996.]
Perspec3ve distor3on loses informa3on
• perspec3ve distor3on – interferes with all size channel encodings – power of the plane is lost!
[Visualizing the Results of Mul(mediaWeb Search Engines. Mukherjea, Hirata, and Hara. InfoVis 96]
Tilted text isn’t legible
• text legibility • far worse when 3lted from image plane
[Visualizing the World- Wide Web with the Naviga(onal View Builder. Mukherjea and Foley. Computer Networks and ISDN Systems, 1995.]
No unjus3fied 3D example : Timeseries data
• extruded curves: detailed comparisons impossible
[Cluster and Calendar based Visualiza(on of Time Series Data. van Wijk and van Selow, Proc. InfoVis 99.]
No unjus3fied 3D example : Transform for new data abstrac3on
• derived data: cluster hierarchy • juxtapose mul3ple views: calendar, superimposed 2D curves
Jus3fied 3D: shape percep3on
• benefits outweigh costs when task is shape percep3on for 3D spa3al data
• interac3ve naviga3on supports synthesis across many viewpoints
[Image-Based Streamline Genera(on and Rendering. Li and Shen. IEEE Trans. Visualiza(on and Computer Graphics (TVCG) 13:3 (2007), 630–640.]
No unjus3fied 3D • 3D legi3mate for true 3D spa3al data • 3D needs very careful jus3fica3on for abstract data – enthusiasm in 1990s, but now skep3cism – be especially careful with 3D for point clouds or networks
[WEBPATH-a three dimensional Web history. Frecon and Smith. Proc. InfoVis 1999]
No unjus3fied 2D • consider whether network data requires 2D spa3al layout – especially if reading text is central to task!
– arranging as network means lower informa3on density and harder label lookup compared to text lists
• benefits outweigh costs when topological structure/context important for task – be especially careful for search results, document collec3ons, ontologies
Eyes beat memory • principle: external cogni3on vs. internal memory
– easy to compare by moving eyes between side-by-side views – harder to compare visible item to memory of what you saw
• implica3ons for anima3on – great for choreographed storytelling – great for transi3ons between two states – poor for many states with changes everywhere
• consider small mul3ples instead
Eyes beat memory example: Cerebral
• small mul3ples: one graph instance per experimental condi3on – same spa3al layout – color differently, by condi3on
[Cerebral:Visualizing Mul(ple Experimental Condi(ons on a Graph with Biological Context. Barsky, Munzner, Gardy, and Kincaid. IEEE Trans. Visualiza(on and Computer Graphics (Proc. InfoVis 2008 – Affordable Custom Essay Writing Service | Write My Essay from Pro Writers) 14:6 (2008 – Affordable Custom Essay Writing Service | Write My Essay from Pro Writers), 1253–1260.]
Why not anima3on? • disparate frames and
regions: comparison difficult – vs con3guous frames – vs small region – vs coherent mo3on of group
• change blindness – even major changes difficult to no3ce if mental buffer wiped
• safe special case – animated transi3ons
Resolu3on beats immersion • immersion typically not helpful for abstract data
– do not need sense of presence or stereoscopic 3D • resolu3on much more important
– pixels are the scarcest resource – desktop also be[er for workflow integra3on
• virtual reality for abstract data very difficult to jus3fy
[Development of an informa(on visualiza(on tool using virtual reality. Kirner and Mar(ns. Proc. Symp.Applied Compu(ng 2000]
Overview first, zoom and filter, details on demand
• influen3al mantra from Shneiderman [The Eyes HaveIt:ATask by DataTypeTaxonomy for Informa(onVisualiza(ons. Shneiderman. Proc. IEEE Visual Languages, pp. 336–343, 1996.]
• overview = summary – microcosm of full vis design problem
• Nuances – beyond just two levels: mul3-scale structure – difficult when scale huge: give up on overview and browse local neighborhoods?
[Search, Show Context, Expand on Demand: Suppor(ng Large Graph Explora(on with Degree-of-Interest. van Ham and Perer.IEEETrans.Visualiza(on and Computer Graphics (Proc.InfoVis 2009) 15:6 (2009), 953–960.]
Func3on first, form next
• start with focus on func3onality – straigh`orward to improve aesthe3cs later on, as refinement
– if no exper3se in-house, find good graphic designer to work with
• dangerous to start with aesthe3cs – usually impossible to add func3on retroac3vely
Artery Visualiza3ons for Heart Disease Diagnosis
HemoViz: Design study + evalua3on
• forma3ve study with experts – task taxonomy
• HemoViz design • deploy a[empt fails
– experts balk: demand 3D and rainbows
• quan3ta3ve user study – med students, real data – 91% with 2D/diverging vs 39% with 3D/ rainbows
– experts willing to use
[Fig 1. Borkin et al. Artery Visualiza(ons for Heart Disease Diagnosis. Proc InfoVis 2011.]]
Study Results: Error
Study Results: Time
Cri3que • many strengths
– careful and well jus3fied design, convincing human-subjects experiment • bringing visualiza3on best prac3ces to medical domain
• Limita3on – paper does not clearly communicate why colormap is diverging not sequen3al
• answer by email • doctors care about extremely high and extremely low ESS (scalar) values
– high values (top of scale, dark grey): extreme blood flow pa[erns may relate to heart malfunc3ons – but not imminently life threatening and don’t indicate plaque loca3ons
– low values (bo[om of scale, dark red): very diseased regions with lots of plaque, docs care a lot! – much debate from doctors on where is boundary between “normal” and “low” ESS values • most think below 3 Pa are indica3ve of disease but many argue other values in the 2-4 range. • all docs agree that values below 2 Pa are increasingly dangerous disease levels. • thus map has transi3on at 3 Pa for the diverging point and truly red below 2 Pa
• why con3nuous not segmented? – doctors gain tremendous insight by seeing the subtle pa[erning of the ESS values – par3cularly varying values in red region – pa[erns help them understand disease progression
and severity • especially useful for deciding what types of interven3ons to prescribe for the pa3ent
Further Reading
• Exploring and Reducing the Effects of Orienta(on on Text Readability in Volumetric Displays. Grossman et al. CHI 2007
