Visualizing Literature Review Theme Evolution on Timeline Maps: Comparison Across Disciplines

Abstract

Data-driven visualization techniques can be utilized to enhance the literature review process across different disciplines. In our work, 910 articles were retrieved using keyword search from bibliographic databases of two different disciplines (computer science: DBLP and medicine: MEDLINE) between 2001 and 2016. These articles' titles were processed using dynamic latent Dirichlet allocation to generate a set of themes/topics, which were subsequently classified and assigned to regions in a spatiotemporal geographical map. Resulting data visualizations from both repositories were manually reviewed by independent annotators. The results from the DBLP and MEDLINE were comparable and, taken together, suggest potential benefits of increased future interaction amongst multidisciplinary fields. Our findings indicate that spiral timeline maps have the potential to help researchers acquire or compare knowledge efficiently without prior domain knowledge.

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