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Related Experiment Videos

Fullerene data mining using bibliometrics and database tomography

Kostoff1, Braun, Schubert

  • 1Office of Naval Research, Arlington, Virginia 22217, USA. KOSTOFR@ONR.NAVY.MIL

Journal of Chemical Information and Computer Sciences
|February 8, 2000
PubMed
Summary

Database tomography (DT) uncovers key themes and relationships in scientific literature. This text mining approach, applied to fullerenes, revealed consistent patterns applicable to broader chemical research.

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Area of Science:

  • Materials Science
  • Bibliometrics
  • Data Mining

Background:

  • Scientific literature analysis is crucial for understanding research trends.
  • Existing methods may not fully capture the complex relationships within large datasets.
  • Fullerenes research presents a rich area for exploring advanced data analysis techniques.

Purpose of the Study:

  • To introduce and evaluate Database Tomography (DT) as a system for extracting multiword phrase frequencies and proximities from textual databases.
  • To derive technical intelligence from a fullerenes database using DT and bibliometric analysis.
  • To compare DT findings across diverse technical domains and identify commonalities in bibliometric distributions.

Main Methods:

  • Database Tomography (DT) algorithms for extracting multiword phrase frequencies and proximities.

Related Experiment Videos

  • Analysis of a fullerenes database sourced from Science Citation Index and Engineering Compendex.
  • Supplementation with bibliometric data including author, journal, and institution publication and citation metrics.
  • Comparative analysis with databases from near-earth space, chemistry, fluid dynamics, and naval hydrodynamics.

    • Main Results:

    • Phrase frequency analysis identified pervasive technical themes in the fullerenes database.
    • Phrase proximity analysis revealed relationships among these technical themes.
    • Normalized bibliometric distribution functions showed remarkable consistency across diverse technical domains, suggesting broader applicability.
    • DT successfully integrated expert interpretation with data mining for technical intelligence.

    Conclusions:

    • Database Tomography is an effective tool for analyzing large scientific textual databases.
    • Consistent bibliometric patterns exist across diverse scientific fields, including chemistry.
    • Integrating domain experts with data mining tools enhances the interpretative power of such analyses.