The Book of Trees is now available!      See other retailers
Home     About     VC Book     Stats     Blog     Books     Links     Contact  
Search the VC database:
    Knowledge Networks   < Prev | 19 of 112 | Next >
The materials shown on this page are copyright protected by
their authors and/or respective institutions.
Visualizing Knowledge Domains
Author(s):
Katy Borner, Chaomei Chen, Kevin Boyack
Institution:
School of Library and Information Science, Indiana University
Year:
2003
URL:
http://ella.slis.indiana.edu/%7Ekaty/gallery/
Project Description:
Advanced data mining and information visualization techniques can be applied to support science and technology management. Large amounts of, e.g., publication, patent, and grant data are analyzed, correlated, and visualized to map the semantic space of researchers, publications, funding, etc.. The resulting visualizations can be utilized to objectively identify major research areas, experts, institutions, grants, publications, journals, etc. in a research area of interest. In addition, they can assist identify interconnections, the import and export of research between fields, the dynamics (speed of growth, diversification) of scientific fields, scientific and social networks, and the impact of strategic and applied research funding programs among others.

Using a tutorial style, various algorithms were applied to map papers related to "Visualizing Knowledge Domain" research, the so called ARIST data set. Never before have so many knowledge domain mapping algorithms been applied to one data set.

Comments (0):
*Note* Before you submit your comment, bear in mind there's no guarantee it will be seen by this project's author. In case you want to contact the author directly, please follow the provided URL.
Leave a Comment:
* COMMENTS HAVE BEEN TEMPORARILY DISABLED *
(We're looking for the best solution to avoid unwanted SPAM)
Manuel Lima | VisualComplexity.com