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Abstract

This paper proposes a novel methodology to visualize a classification scheme. It is demonstrated with the Association for Computing Machinery (ACM) Computing Classification System (CCS). The collection derived from the ACM digital library, containing 37,543 documents classified by CCS. The assigned classes, subject descriptors, and keywords were processed in a dataset to produce a graphical representation of the documents. The general conception is based on the similarity of co-classes (themes) proportional to the number of common publications. The final number of all possible classes and subclasses in the collection was 353 and therefore the similarity matrix of co-classes had the same dimension. A spherical surface was chosen as the target information space. Classes and documents' node locations on the sphere were obtained by means of Multidimensional Scaling coordinates. By representing the surface on a plane like a map projection, it is possible to analyze the visualization layout. The graphical patterns were organized in some colour clusters. For evaluation of given visualization maps, graphics filtering was applied. This proposed method can be very useful in interdisciplinary research fields. It allows for a great amount of heterogeneous information to be conveyed in a compact display, including topics, relationships among topics, frequency of occurrence, importance and changes of these properties over time.