A human cognition framework for information visualization

• Published in: Computers & graphics Vol. 42; pp. 42 - 58
• Main Authors: Patterson, Robert E., Blaha, Leslie M., Grinstein, Georges G., Liggett, Kristen K., Kaveney, David E., Sheldon, Kathleen C., Havig, Paul R., Moore, Jason A.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.08.2014; Elsevier
• Subjects: Applied sciences; Artificial intelligence; Cognition; Cognitive augmentation; Communities; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Data processing. List processing. Character string processing; Data visualization; Exact sciences and technology; Human; Human cognition; Information visualization; Learning; Learning and adaptive systems; Memory organisation. Data processing; Pattern recognition. Digital image processing. Computational geometry; Reasoning; Software; Visual; Visual analytics; Visual attention; Visualization; Information visualization; Human cognition; Visual analytics; Visual attention; Cognitive augmentation; Induction; Top down method; Cognition; Chunking; Human factor; Mental model; Cognitive theory; Reasoning; Data visualization; Graphical interface; Analogy; Artificial intelligence

We present a human cognition framework for information visualization. This framework emphasizes how top-down cognitive processing enables the induction of insight, reasoning, and understanding, which are key goals of the visual analytics community. Specifically, we present a set of six leverage poin...