Abstract
Scientific visualization applications can be divided into two categories: expository and exploratory. This chapter focuses on exploratory applications. Exploratory applications typically represent complicated scientific data as fully as possible so that a scientific user can interactively explore it. As per the scientific method, a scientist gathers data to test a hypothesis, but the binary answer to that test is usually just a beginning. The challenge comes in understanding the correlations and dependencies among all the values. The chapter begins with a narrative of some of the work in the area of representing multivalued data, illustrating more specifically some of the ways in which art can be brought to bear on scientific visualization. The chapter then gives a broader survey of scientific visualization work that has been influenced by art, followed by a discussion of some of the open issues in this area, which ties back to studying art, design, and art education. © 2005
| Original language | English (US) |
|---|---|
| Title of host publication | Visualization Handbook |
| Publisher | Elsevier Inc. |
| Pages | 873-891 |
| Number of pages | 19 |
| ISBN (Electronic) | 9780123875822 |
| ISBN (Print) | 9780123875822 |
| DOIs | |
| State | Published - Jan 1 2004 |
Bibliographical note
Funding Information:This work was supported by NSF (CCR-96-19649, CCR-9996209, CCR-0086065) and NSF (ASC-89-20219) as part of the NSF STC for Computer Graphics and Scientific Visualization; and the Human Brain Project with contributions from the National Institute on Drug Abuse, the National Institute of Mental Health, and the National Institute on Biomedical Imaging and Bioengineering.