Journal article
An information-theoretic view of visual analytics
IEEE Computer Graphics and Applications, v 28(1), pp 18-23
28 Feb 2008
Abstract
Prior to the 9/11 terrorist attacks, several foreign nationals enrolled in US civilian flying schools to learn how to fly large commercial aircraft. They wanted to learn how to navigate civilian airlines, but they were not interested in landings or takeoffs. They all paid cash for the lessons. So, the 9/11 investigations raised questions about whether intelligence agencies could have connected the dots and prevented the attacks. But how do you connect these seemingly isolated dots and reveal the hidden story? One clue might lie in the differentiation between puzzles and mysteries that Malcolm Gladwell made in a recent New Yorker article on stories about Enron's collapse. To solve a puzzle, Gladwell writes, you need a specific piece of information; but to solve a mystery, you must ask the right question. Connecting dots is more a mystery than a puzzle. You might have all the necessary information in front of you and yet fail to see the connection or recognize an emergent pattern. Asking the right question is critical to staying on track. Visual analytics is an emerging discipline that helps connect dots. It facilitates analytical reasoning and decision making through integrated and highly interactive visualization of complex and dynamic data and situations. 3 Solving mysteries is only part of the game. Visual analytics must augment analyst and decision-maker capabilities to assimilate complex situations and reach informed decisions. Information theory offers a framework for keeping focused on the right questions.
Metrics
Details
- Title
- An information-theoretic view of visual analytics
- Creators
- Chaomei Chen - Drexel University
- Publication Details
- IEEE Computer Graphics and Applications, v 28(1), pp 18-23
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000251686900004
- Scopus ID
- 2-s2.0-38348999479
- Other Identifier
- 991014632730004721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Software Engineering