Interaction Visualization Usability & UX Laboratory
Information Visualization Paolo Buono
[email protected]
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
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Dati
FedEx: 6 milioni di transazioni al giorno VISA: 98 milioni di transazioni al giorno (2005) AT&T: 5,4 PB di traffico al giorno email: 610-1110 miliardi di email scambiate (2000) 800 milioni di foto caricate su internet al giorno (350 solo su facebook) 50 miliardi di messaggi scambiati su Whatsapp al giorno (2013) Data overload
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Alcuni modi di dire
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“I see what you’re saying”
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“Seeing is believing”
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“A picture is worth a thousand words”
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Definition
Visualization is: Use of computer-supported interactive visual representation of data to amplify cognition
Paolo Buono – Information Visualization – 24 febbraio 2016
Shneiderman, 2004
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Interaction Visualization Usability & UX Laboratory
Definition
Information Visualization is: Use of computer-supported interactive visual representation of abstract data to amplify cognition
Paolo Buono – Information Visualization – 24 febbraio 2016
Shneiderman, 2004
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Interaction Visualization Usability & UX Laboratory
Information Visualization
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Use of computer-supported interactive visual representation of abstract data to amplify cognition How?
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Why?
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Compact graphical presentation to manipulate large numbers of items, possibly extracted from far large datasets (big data) make discoveries take decisions explain
What?
patterns groups of items individual items
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
More definitions
“a process of transforming data and information that are not inherently spatial into a visual form, allowing the user to observe and understand the information…” ⦿
Gershon & Eick, 1995
“the communication of abstract data through the use of interactive visual interfaces” ⦿
Keim et al., 2006
“a process of forming a mental model of data, thereby gaining insight into and understanding of that data” ⦿
Spence, 2007
“produces (interactive) visual representations of abstract data to reinforce human cognition; thus enabling the viewer to gain knowledge about the internal structure of the data and causal relationships in it” ⦿
Paolo Buono – Information Visualization – 24 febbraio 2016
InfoVis Wiki (http://www.infovis-wiki.net) 7
Interaction Visualization Usability & UX Laboratory
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What is Information Visualization
Visualization is more than method of computing. It is a process of transforming information into a visual form enabling the user to observe the information We need to take into account human perceptual and cognitive capabilities, human variations, and task characteristics Visualization is more than pretty pictures. Successful visualizations can reduce the time it takes to get information, make sense out of it, and enhance creative thinking Information is usually non-spatial data or abstract
Finding a good spatial representation of the information at hand is one of the most difficult tasks
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Description of InfoVis
Information Visualization (InfoVis) is a research area that focuses on the use of visualization techniques to help people understand and analyze data.
While related fields such as Scientific Visualization involve the presentation of data that has some physical or geometric correspondence, Information Visualization centers on abstract information without such correspondences, i.e., it is not possibile to map this information into the physical world in most cases. Examples of such abstract data are symbolic, tabular, networked, hierarchical, or textual information sources. The ever increasing amount of data generated or made available every day confirms the urgent need for suitable InfoVis tools. As prerequisite for building a successful visualization, InfoVis combines several aspects of different research areas, such as Computer Graphics, Graph Drawing, Data Mining, Information Design, Cognitive Psychology, and Human-Computer Interaction (HCI), among many others. http://www.dagstuhl.de/de/programm/kalender/semhp/?semnr=10241
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
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Information Visualization vs Scientific Visualization
Scientific visualization is: “The graphical representation of complex physical phenomena in order to assist scientific investigation and to make inferences that aren’t apparent in numerical form. Typical examples include processing of satellite photographs and 3D representations of molecules and fluids to examine their dynamics”
Usability first, 2003
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Scientific Visualization (SV) is focused on visually representing phisical objects and phenomena
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Information Visualization (IV) focuses on more abstract data
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IV tackles applications that deal with data (e.g., Web site accesses) which are outside the scope of SV
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
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Visualizations in everyday life
Table in a newspaper Train/subway map with arrival/departure times Map of a region Weather chart Stock market graph Your product vs leading brand comparison plot 3D reconstruction of a body part generated from a CT scan Instruction manual Highway signs
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
special mention: maps
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
special mention: maps
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
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Domains
Finance Engineering Medicine Physics Statistics Data analysis Simulation Marketing / advertisement …
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Importance of Visualization
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Billions of potential users
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Huge amounts of existing information
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Information overload Difficult to make sense
New visual computing, display technologies, and visualization methods make it possible to represent information effectively
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Importance of good Visualization
Same data (a) Equally (uniformly) large scale in both x and y
(b) Large scale in y
(c) Large scale in y
(d) Scale determined by range of x- and y-values.
Different scale
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
IV influence: continue or abort trial?
Paolo Buono – Information Visualization – 24 febbraio 2016
Linda S. Elting, Charles G. Martin, Scott B. Cantor, and Edward B. Rubenstein, Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures, British Medical Journal, vol. 318, pp. 1527-1531, 1999. 17
Interaction Visualization Usability & UX Laboratory
IV influence: continue or abort trial?
Paolo Buono – Information Visualization – 24 febbraio 2016
Linda S. Elting, Charles G. Martin, Scott B. Cantor, and Edward B. Rubenstein, Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures, British Medical Journal, vol. 318, pp. 1527-1531, 1999. 18
Interaction Visualization Usability & UX Laboratory
Jamie’s alternative proposal
Paolo Buono – Information Visualization – 24 febbraio 2016
http://eagereyes.org/blog/2011/visualization-choice-influences-decisions 19
Interaction Visualization Usability & UX Laboratory
Peltier’s alternative proposal
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Interaction Visualization Usability & UX Laboratory
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Tufte about graphical excellence
Excellence consists of complex ideas communicated with clairity, precision, efficiency. Graphical display should:
Show the data Induce the viewer to think about the substance rather than about methodology, graphic design, the technology of graphic production, … Avoid distorting what the data have to say Present many numbers in a small space Make large data sets coherent Encourage the eye to compare different pieces of data Reveal the data at several levels of detail Serve a reasonably clear purpose: description, exploration, tabulation, decoration Be closely integrated with the statistical and verbal descriptions of a data set E. R. Tufte, the Visual Display of Quantitative Information, Graphics Press, Cheshire, Connecticut, 1983
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Storia visualizzazione dati (in forma tabulare) Tufte
Bertin Egitto
Cartesio
Cleveland
1st IV Conference
Playfair
(Descartes)
Panel of Graphics, Image, Processing and Workstations
Iowa State University Tukey
Paolo Buono – Information Visualization – 24 febbraio 2016
Macintosh 22
Interaction Visualization Usability & UX Laboratory
Early Visualizations
One of the Lascaux cave paintings on the notrhern slopes of the French Pyrenees on the banks of the Vézère river (13.000-15.000 a.C.) Paolo Buono – Information Visualization – 24 febbraio 2016
http://www.lascaux.culture.fr
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Interaction Visualization Usability & UX Laboratory
Early Visualizations A section of John Snow’s map of the deaths from cholera in London in 1663 Each bar within the houses represents one deceased individual
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Early Visualizations Overview map of the deaths from Cholera in London in 1663 Note the concentration around the Broad Street Water Pump Note as well the outliers
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Early Visualizations
Small details worth investigating
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Early Visualizations: Minard’s map
Width: size of the army at that location Color: direction of movement Temperature: along the retreat at the bottom Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Early Visualizations
William Playfair
Paolo Buono – Information Visualization – 24 febbraio 2016
National debt over time
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Interaction Visualization Usability & UX Laboratory
Early Visualizations Florence Nightingale’s coxcomb chart showing monthly deaths from battle and other causes Blue: deaths from disease Red: deaths from wounds Black: all other deaths http://understandinguncertainty.org/node/213
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization Today - Bari
… yes, the Bari’s metro Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization Today – London
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization Today - London
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization Today
Dow Jones Industrial Average (DJIA) from 1900 to 2000. The Dow Jones Industrial Average is a U.S. stock index based on the weighted average of the stock prices of 30 large and actively traded U.S. companies. The divisor changes over time as stock splits, so as not to alter that average in those cases. Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization Today
Two examples of 12-lead ECGs: A normal adult:
http://www.ecglibrary.com/ecghome.html
Paolo Buono – Information Visualization – 24 febbraio 2016
An 83-year-old adult with heart problems:
http://www.ecglibrary.com/ecghome.html
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Interaction Visualization Usability & UX Laboratory
Visualization Today
Umass Lowell UVP Software (http://www.uvp.com/visionworks.html)
Action data with regression line Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization Today
UMass Lowell UVP software (http://www.uvp.com/visionworks.html)
A pathway represented by a network with nodes representing genes and color the level of expression Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
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Visualization vs Computer Graphics
Originally considered a subfield of CG Visualization are always connected to data, do not emphasize visual realism CG focuses on graphical objects and organization of graphical primitives. A secondary application of CG is in art and entertrainement
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
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Scientific Data Visualization vs Information Visualization
Still in early 2000 SciVis and InfoVis were differenciated Both provide representations of data Dataset are often different
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Information Visualization: Using Vision to Think
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Visualization pipeline
Raw Data
Data
Data/flow Transformations
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Data Tables
Visual Structures Visual Mappings
Visual form
View Transformations
Human Interaction
Data modeling Data selection Data to visual mappings Scene parameter settings (view transformations)
Paolo Buono – Information Visualization – 24 febbraio 2016
Views
Task
Card et al. 1999
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Interaction Visualization Usability & UX Laboratory
The role of the User
Can be involved in most stages of visualization pipeline
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Exploration
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Confirmation
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Presentation (primary)
Paolo Buono – Information Visualization – 24 febbraio 2016
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Interaction Visualization Usability & UX Laboratory
Exploratory visualization
microarray gene expression experiment analysis
J. Zhou, G. Grinstein, and K. Marx. “A New Gene Selection Method for Visual Analysis.” Scientific Report No. 015, University of Massachusetts Lowell, 2007
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Find what you need Understand what you Find
