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Related Experiment Videos

Mapping knowledge domains: characterizing PNAS.

Kevin W Boyack1

  • 1Computation, Computers, Information and Mathematics Center, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185, USA. kboyack@sandia.gov

Proceedings of the National Academy of Sciences of the United States of America
|February 14, 2004
PubMed
Summary

Data mining reveals that research funded jointly by US and international sources, and larger grants, yield higher citation impact. This analysis maps scientific knowledge domains and identifies high-impact research trends.

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Area of Science:

  • Bibliometrics
  • Scientometrics
  • Data Mining

Background:

  • Knowledge domain mapping utilizes data mining and analysis techniques.
  • Literature mapping can be based on authors, documents, journals, words, or indicators.
  • Mapping is often used for research assessment and understanding discipline dynamics.

Purpose of the Study:

  • To review data mining and analysis techniques for knowledge domain mapping.
  • To demonstrate mapping techniques using 20 years of PNAS publications.
  • To identify factors influencing research impact and trends.

Main Methods:

  • Review of data mining and analysis techniques.
  • Merging data from various sources (funding, citations) for PNAS domain.
  • Citation analysis to map high-performing papers and topics.

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Main Results:

  • Jointly funded research (USPHS/NIH + non-US) shows higher performance than other funding sources.
  • Larger grants correlate with higher citation counts, indicating increased performance.
  • Identification of high-impact papers, subject trends, and topic interactions within PNAS.

Conclusions:

  • Funding source and grant size significantly impact research performance.
  • Citation analysis effectively maps knowledge domains and identifies impactful research.
  • Trends in high-impact subjects and topic interactions within PNAS are discernible.