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Keywords:

  • citation networks;
  • co-citation analysis;
  • dynamic systems

The majority of the effort in metrics research has addressed research evaluation. Far less research has addressed the unique problems of research planning. Models and maps of science that can address the detailed problems associated with research planning are needed. This article reports on the creation of an article-level model and map of science covering 16 years and nearly 20 million articles using cocitation-based techniques. The map is then used to define discipline-like structures consisting of natural groupings of articles and clusters of articles. This combination of detail and high-level structure can be used to address planning-related problems such as identification of emerging topics and the identification of which areas of science and technology are innovative and which are simply persisting. In addition to presenting the model and map, several process improvements that result in greater accuracy structures are detailed, including a bibliographic coupling approach for assigning current papers to cocitation clusters and a sequential hybrid approach to producing visual maps from models.