Database tomography for technical intelligence: Comparative roadmaps of the research impact assessment literature and the journal of the American Chemical Society

Abstract

This paper shows how Database Tomography 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 applicafion 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 lmpact Assessment (RIA) and the technical field of Chemistry. A database of relevant RIA articles was analyzed to produce characteristics and key features of the R1A field. The recent prolific RIA authors, the journals prolific in RIA papers, the prolific institutions in R1A, 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 analyses 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 R1A and Chemistry results were compared. Finally, the conceptual use of Database Tomography to help identify promising research directions was discussed.

Science and Technology Text Mining: Electric Power Sources

“…All are from universities. This prolific author country distribution differs radically from any in previous studies [27][28][29][30][31][32], with the high concentration from India. These prolific author countries in previous text mining studies tended to be dominated by Northern America countries (United States and Canada), the most developed Western European nations (UK, Germany, France, Italy), and the major oriental Asian countries (Japan, China, South korea).…”

“…It differs from the previous published papers in this category [27][28][29][30][31][32] in four respects. First, the topical domain (power sources) is completely different.…”

“…This is twice the number of journals from any of the previous studies [27][28][29][30][31][32], and again reflects the multi-disciplined nature of EPS. There was an average of 14.64 papers per journal.…”

“…England, India, Germany, Canada, and France constitute the next group, and the remaining countries constitute the third group. This is the prolific country distribution pattern typical of past text mining studies [27][28][29][30][31][32].…”

“…There was an average of 14.64 papers per journal. This number is somewhat inflated compared to the journal averages from other text mining studies [27][28][29][30][31][32]. In the journal-derived component of the present study, all the papers in eleven journals were used.…”