Using a Semantic Analysis Tool to Generate Subject Access Points: A Study Using Panofsky's Theory and Two Research Samples

Publication Title

Knowledge Organization

Publication Date


Document Type



semantic analysis, subject access points, tags, terms


Library and Information Science


The problem addressed by this study is the assessment of alternative approaches of generating subject access points to materials that are usually not made available through regular library catalog routines. As an aid in understanding how computerized subject analysis might be approached, we suggest using the three-layer framework that has been accepted and applied in image analysis. The hypothesis is that the computer-assisted semantic analysis has great potential in generating subject access at the "description" and "identification" levels. Two research samples were used to analyze the access points supplied by the OpenCalais semantic analysis tool. The first sample includes 43 archival record groups from 16 institutions, including university archives, government records archives, and manuscript/special collections repositories in various LAMs. The analysis resulted in dozens and, at times, hundreds of potential entities and social tags that could be used to provide additional points of entry to these archival records. These entities and tags correspond almost exclusively to the first two layers of subject analysis (description and identification). The second sample contained 44 philosophy theses. In this part of the research, it was found that the semantic analysis based on the abstracts generated more successful tags than those based on the titles. The research based on the two samples indicate these subject access points fall at the "description" (referring to the generic elements depicted in or by the work) and "identification" (referring to the specific subject) levels, rather than the "interpretation" (referring to the meaning or themes represented by the subjects and including a conceptual analysis of what the work is about) level.