Abstract
This paper shows how Database Tomgraphy can be used to derive technical intelligence from the published literature. Database Tomography is a patented system for analyzing large amounts of textual computerized material. It includes algorithms for extracting multi-word phrase frequencies and performing phrase proximity analyses. Phrase frequency analysis provides the pervasive themes of a database, and the phrase proximity analysis provides the relationships among the pervasive themes, and between the pervasive themes and sub-themes. One potential application of Database Tomography is to obtain the thrusts and interrelationships of a technical field from papers published in the literature within that field. This paper provides applications of Database Tomography to analyses of both the non-technical field of Research Impact Assessment (RIA) and the technical field of Chemistry. A database of relevant RIA articles was analyzed to produce characteristics and key features of the RIA field. The recent prolific RIA authors, the journals prolific in RIA papers, the prolific institutions in RIA, the prolific keywords specified by the authors, and the authors whose works are cited most prolifically as well as the particular papers/journals/institutions cited most prolifically, are identified. The pervasive themes of RIA are identified through multi-word phrase of the database. A phrase proximity analysis of the database shows the relationships among the pervasive themes, and the relationships between the pervasive themes and subthemes. A similar process was applied to Chemistry, with the exception that the database was limited to one year's issues of the Journal of the American Chemical Society. Wherever possible, the RIA and Chemistry results were compared. Finally, the conceptual use of Database Tomography to help identify promising research directions was discussed.
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Kostoff, R.N., Eberhart, H.J., Toothman, D.R. et al. Database tomography for technical intelligence: Comparative roadmaps of the research impact assessment literature and the journal of the American Chemical Society. Scientometrics 40, 103–138 (1997). https://doi.org/10.1007/BF02459264
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DOI: https://doi.org/10.1007/BF02459264