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| information visualization | |
|---|---|
| Name | Information visualization |
| Field | Human–computer interaction, graphic design, data science |
| Related | Edward Tufte, Ben Shneiderman, John Tukey, Jacques Bertin, William S. Cleveland |
information visualization Information visualization is the practice of representing data and abstract information using visual encodings to support perception, reasoning, and decision-making. It draws on methods and findings from Edward Tufte, Ben Shneiderman, John Tukey, Jacques Bertin, and William S. Cleveland and is implemented across software developed by Microsoft, Tableau Software, IBM, Google, and SAS Institute. Scholars and practitioners engage with communities such as ACM SIGCHI, IEEE VIS, EuroVis, InfoVis, and institutions like MIT Media Lab, Stanford University, and University of Maryland.
Information visualization integrates visual design, human perception, and computational methods to convert abstract data into graphical forms. It intersects with work by Alan Turing in computation, methods from Ronald Fisher in statistics, and interfaces influenced by Douglas Engelbart and Ivan Sutherland. Applications span projects from Human Genome Project visual analytics to dashboards used by United Nations agencies and products released by Apple Inc., Amazon (company), and Facebook (now Meta Platforms, Inc.).
Early roots appear in cartographic innovations by Gerardus Mercator and statistical graphics by William Playfair. Nineteenth-century contributions include work by Florence Nightingale and Charles Minard. The twentieth century advanced theoretical foundations through John Tukey's exploratory data analysis and Jacques Bertin's semiology of graphics; later momentum came from Edward Tufte's critique of graphical integrity and Ben Shneiderman's direct manipulation principles. The field professionalized with conferences like IEEE VIS and labs at Bell Labs, AT&T, and universities such as University of California, Berkeley and Carnegie Mellon University.
Core principles are derived from perception research by James J. Gibson, information theory by Claude Shannon, and cognitive science by George A. Miller. Design heuristics reference Edward Tufte's data-ink ratio, Ben Shneiderman's visual information-seeking mantra, and Jacques Bertin's visual variables. Statistical underpinnings rely on techniques advanced by Ronald Fisher, John Tukey, and Jerzy Neyman. Human–computer interaction principles come from work at Xerox PARC and researchers like Stuart Card, Jock Mackinlay, and George G. Robertson.
Visualization techniques include chart forms historically associated with William Playfair (bar charts, line graphs), multivariate displays tracing to John Tukey (scatterplot matrices, parallel coordinates), and network diagrams linked to studies at Stanford University and Imperial College London. Spatial techniques derive from cartographers such as Gerardus Mercator and John Snow (physician), while temporal techniques connect to timelines used in projects at Smithsonian Institution and British Museum. Advanced methods employ dimensionality reduction algorithms by Geoffrey Hinton and Joaquin Quinonero-Candela, clustering algorithms by J. B. MacQueen and John A. Hartigan, and graph layout algorithms with lineage to Peter Eades and Thomas H. J. Algorithms (note: lineage refers to graph drawing research). Interactive techniques reflect work by Ben Shneiderman and prototypes from MIT Media Lab.
Prominent tools include commercial products such as Tableau Software, Microsoft Power BI, SAS Institute offerings, and web platforms from Google and Amazon Web Services. Open-source ecosystems feature projects from The R Project for Statistical Computing (packages influenced by Hadley Wickham), Python (programming language) libraries developed in communities around NumFOCUS and contributors like Wes McKinney, and visualization frameworks originating from Protovis and D3.js authors such as Mike Bostock. Research prototypes and environments trace to VisIt, ParaView, and systems developed at Lawrence Berkeley National Laboratory and Los Alamos National Laboratory.
Applications span scientific research at NASA, CERN, and National Institutes of Health, business intelligence at McKinsey & Company and Deloitte, journalism projects by The New York Times and The Guardian, public policy analyses used by World Bank and International Monetary Fund, and healthcare visual analytics in hospitals like Mayo Clinic. Educational platforms from Khan Academy and museum exhibits at Smithsonian Institution leverage visualization to communicate complex information. Emergency response systems and situational awareness tools are used by Federal Emergency Management Agency and military organizations including NATO.
Evaluation methods draw on experimental traditions from Donald Broadbent and Ulric Neisser, controlled studies in ACM SIGCHI venues, and benchmark datasets from UCI Machine Learning Repository. Criticisms arise from scholars influenced by Edward Tufte and Jesse Shapiro regarding misleading or manipulative graphics; concerns about bias and fairness reference work by Cathy O'Neil and debates in forums hosted by Brookings Institution and Data & Society Research Institute. Ethical and legal considerations intersect with regulations like those enforced by European Commission and discussions informed by reports from National Academy of Sciences.