Existing classification schemes are visualized as hierarchical trees. Science data visualization requires a new method in information space modelling in order to reveal relations between class nodes. This paper describes a novel visualization concept of classification scheme using subject content metrics. We have mapped the document collection of Association for Computing Machinery (ACM) digital library to a sphere surface. To overcome the incorrectness of linear measures in indexes distances we calculated similarity matrix of themes and multidimensional scaling coordinates. The results show that space distances between class nodes accurately correspond with the thematic proximities. Documents mapped into a sphere surface were located according to the classification nodes and distributed uniformly. Proposed method to visualize classification scheme is proper to reach nonlinearity in subject content visualization. This property allows us to place close by more classification nodes. Symmetry of a sphere favours a new subclasses and sublevels of classification trees uniform visualization. This method may be useful in the visual analysis of Computer Science and Engineering domain development being grown instantly.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org