Information visualization

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Graphic representation of a minute fraction of the WWW, demonstrating hyperlinks

Information visualization or information visualisation is the study of (interactive) visual representations of abstract data to reinforce human cognition. The abstract data include both numerical and non-numerical data, such as text and geographic information. However, information visualization differs from scientific visualization: "it’s infovis [information visualization] when the spatial representation is chosen, and it’s scivis [scientific visualization] when the spatial representation is given".[1]

Overview[edit]

Partial map of the Internet early 2005, each line represents two IP addresses, and some delay between those two nodes.

The field of information visualization has emerged "from research in human-computer interaction, computer science, graphics, visual design, psychology, and business methods. It is increasingly applied as a critical component in scientific research, digital libraries, data mining, financial data analysis, market studies, manufacturing production control, and drug discovery".[2]

Information visualization presumes that "visual representations and interaction techniques take advantage of the human eye’s broad bandwidth pathway into the mind to allow users to see, explore, and understand large amounts of information at once. Information visualization focused on the creation of approaches for conveying abstract information in intuitive ways."[3]

Data analysis is an indispensable part of all applied research and problem solving in industry. The most fundamental data analysis approaches are visualization (histograms, scatter plots, surface plots, tree maps, parallel coordinate plots, etc.), statistics (hypothesis test, regression, PCA, etc.), data mining (association mining, etc.), and machine learning methods (clustering, classification, decision trees, etc.). Among these approaches, information visualization, or visual data analysis, is the most reliant on the cognitive skills of human analysts, and allows the discovery of unstructured actionable insights that are limited only by human imagination and creativity. The analyst does not have to learn any sophisticated methods to be able to interpret the visualizations of the data. Information visualization is also a hypothesis generation scheme, which can be, and is typically followed by more analytical or formal analysis, such as statistical hypothesis testing.

History[edit]

The modern study of visualization started with computer graphics, which "has from its beginning been used to study scientific problems. However, in its early days the lack of graphics power often limited its usefulness. The recent emphasis on visualization started in 1987 with the special issue of Computer Graphics on Visualization in Scientific Computing. Since then there have been several conferences and workshops, co-sponsored by the IEEE Computer Society and ACM SIGGRAPH".[4] They have been devoted to the general topics of data visualisation, information visualization and scientific visualisation, and more specific areas such as volume visualization.

Product Space Localization, intended to show the Economic Complexity of a given economy
Tree Map of Benin Exports (2009) by product category. The Product Exports Treemaps are one of the most recent applications of these kind of visualizations, developed by the Harvard-MIT Observatory of Economic Complexity

In 1786, William Playfair, published the first presentation graphics.

Specific methods and techniques[edit]

Applications[edit]

Information visualization insights are being applied in areas such as:[2]

Experts[edit]

Stuart K. Card
Stuart K. Card is an American researcher. He is a Senior Research Fellow at Xerox PARC and one of the pioneers of applying human factors in human–computer interaction. The 1983 book The Psychology of Human-Computer Interaction, which he co-wrote with Thomas P. Moran and Allen Newell, became a very influential book in the field, partly for introducing the Goals, Operators, Methods, and Selection rules (GOMS) framework. His current research is in the field of developing a supporting science of human–information interaction and visual-semantic prototypes to aid sensemaking.[5]
George W. Furnas
George Furnas is a professor and Associate Dean for Academic Strategy at the School of Information of the University of Michigan. Furnas has also worked with Bell Labs where he earned the moniker "Fisheye Furnas" while working with fisheye visualizations. He is a pioneer of Latent semantic analysis, Professor Furnas is also considered a pioneer in the concept of Mosaic of Responsive Adaptive Systems (MoRAS).
James D. Hollan
James D. Hollan directs the Distributed Cognition and Human-Computer Interaction Laboratory at University of California, San Diego. His research explores the cognitive consequences of computationally based media. The goal is to understand the cognitive and computational characteristics of dynamic interactive representations as the basis for effective system design. His current work focuses on cognitive ethnography, computer-mediated communication, distributed cognition, human-computer interaction, information visualization, multiscale software, and tools for analysis of video data.
Aaron Koblin
Aaron Koblin is an American digital media artist best known for his innovative uses of data visualization and crowdsourcing. He is currently Creative Director of the Data Arts Team at Google in San Francisco, California.[6] Koblin's artworks are part of the permanent collections of the Victoria and Albert Museum (V&A) in London, the Museum of Modern Art (MoMA) in New York, and the Centre Georges Pompidou in Paris. He has presented at TED, and The World Economic Forum, and his work has been shown at international festivals including Ars Electronica, SIGGRAPH, and the Japan Media Arts Festival. In 2006, his Flight Patterns project received the National Science Foundation's first place award for science visualization.[7] In 2009, he was named to Creativity Magazine's Creativity 50,[8] in 2010 he was one of Esquire Magazine's Best and Brightest and Fast Company's Most Creative People in Business,[9] and in 2011 was one of Forbes Magazine's 30 under 30. Koblin is a graduate of UCLA's Design | Media Arts MFA program, and sits on the board of the non-profit Gray Area Foundation For The Arts GAFFTA in San Francisco.
Manuel Lima
Manuel Lima is the founder of VisualComplexity.com and a Senior UX Design Lead at Microsoft. He is a Fellow of the Royal Society of Arts and was nominated by Creativity magazine as "one of the 50 most creative and influential minds of 2009". Lima is a leading voice on information visualization and a frequent speaker in conferences and schools around the world, including TED, Lift, OFFF, Reboot, VizThink, IxDA Interaction, Royal College of Art, NYU Tisch School of the Arts, ENSAD Paris, University of Amsterdam, MediaLab Prado Madrid.[10]
Edward Tufte
Edward Tufte is an American statistician and professor emeritus of political science, statistics, and computer science at Yale University.[11] He is noted for his writings on information design and as a pioneer in the field of data visualization.[12][13][14]
Fernanda Viegas and Martin Wattenberg
Fernanda Viegas and Martin Wattenberg are known for pioneering work in artistic and social data visualization. They lead Google's data visualization research group. They founded the field of Social data analysis and were the creators of "Many Eyes," the first cloud-based visualization service, and History Flow, a tool for visualizing Wikipedia edits. Their artwork has been shown in museums worldwide, and helped establish visualization as an artistic practice.[15][16][17]
More related scientists

Organization[edit]

Organizations

See also[edit]

References[edit]

  1. ^ http://www.cs.ubc.ca/labs/imager/tr/2008/pitfalls/
  2. ^ a b Benjamin B. Bederson and Ben Shneiderman (2003). The Craft of Information Visualization: Readings and Reflections, Morgan Kaufmann ISBN 1-55860-915-6.
  3. ^ James J. Thomas and Kristin A. Cook (Ed.) (2005). Illuminating the Path: The R&D Agenda for Visual Analytics. National Visualization and Analytics Center. p.30
  4. ^ G. Scott Owen (1999). History of Visualization. Accessed Jan 19, 2010.
  5. ^ Stuart Card at PARC, 2004. Retrieved 1 July 2008.
  6. ^ Hoffman, Jascha (2012). "Aaron Koblin Q&A: The data visualizer". Nature 486 (7401): 33. doi:10.1038/486033a.  edit
  7. ^ "2006 Science and Engineering Visualization Challenge Winners". September 2006. Retrieved 2009-04-08. 
  8. ^ "The 2009 Creativity 50: Aaron Koblin". Creativity Magazine; Crain Communications Group. February 2009. Retrieved 2009-04-08. 
  9. ^ "The 100 Most Creative People in Business: Aaron Koblin". Fast Company. Dec 2010. 
  10. ^ Lima, Manuel (2011). Visual Complexity: Mapping Patterns of Information. ISBN 1568989369. 
  11. ^ Edward Tufte, Yale University: Political Science webpage.
  12. ^ Yaffa, Joshua. "The Information Sage". Washington Monthly. 
  13. ^ Tufte, Edward R. (1990). Envisioning Information. ISBN 0961392118. 
  14. ^ Tufte, Edward R. (2001) [1st Pub. 1983]. The Visual Display of Quantitative Information (2nd ed.). ISBN 0961392142. 
  15. ^ Blais, Joline; Ippolito, Jon (2006). At the Edge of Art. Thames and Hudson. 
  16. ^ Bulajic, Viktorija Vesna (2007). Database aesthetics: art in the age of information overflow. University of Minnesota Press. 
  17. ^ Reas, Casey; Ben (2007). Processing: a programming handbook for visual designers and artists. MIT Press. 

Further reading[edit]

External links[edit]