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Hypersonic and supersonic flow roadmaps using bibliometrics and database tomography

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  • R. N. Kostoff
  • Henry J. Eberhart
  • Darrell Ray Toothman

Abstract

Database Tomography (DT) is a textual database analysis system consisting of two major components: 1) Algorithms for extracting multiword phrase frequencies and phrase proximities (physical closeness of the multiword technical phrases) from any type of large textual database, to augment 2) interpretative capabilities of the expert human analyst. DT was used to derive technical intelligence from a hypersonic/supersonic flow (HSF) database derived from the Science Citation Index and the Engineering Compendex. Phrase frequency analysis by the technical domain expert provided the pervasive technical themes of the HSF database, and the phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the HSF literature supplemented the DT results with author/journal/institution publication and citation data. Comparisons of HSF results with past analyses of similarly structured near‐earth space and Chemistry databases are made. One important finding is that many of the normalized bibliometric distribution functions are extremely consistent across these diverse technical domains.

Suggested Citation

  • R. N. Kostoff & Henry J. Eberhart & Darrell Ray Toothman, 1999. "Hypersonic and supersonic flow roadmaps using bibliometrics and database tomography," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(5), pages 427-447.
    • Handle: RePEc:bla:jamest:v:50:y:1999:i:5:p:427-447
    DOI: 10.1002/(SICI)1097-4571(1999)50:53.0.CO;2-P
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    Cited by:

    1. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    2. Kostoff, R.N. & Tshiteya, R. & Pfeil, K.M. & Humenik, J.A. & Karypis, G., 2005. "Power source roadmaps using bibliometrics and database tomography," Energy, Elsevier, vol. 30(5), pages 709-730.
    3. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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