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Quantifying the consistency of scientific databases.

Lovro Šubelj1, Marko Bajec1, Biljana Mileva Boshkoska2

  • 1Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

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|May 19, 2015
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Summary

Analyzing scientific databases reveals inconsistencies. This study uses complex networks to compare six major databases, finding significant differences that impact bibliometric studies.

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Area of Science:

  • Bibliometrics
  • Scientometrics
  • Information Science

Background:

  • Science is a social process with significant societal impact.
  • The study of science itself is a recent development, enabled by large-scale data.
  • Scientific publication data is available in databases like Web of Science and PubMed.

Purpose of the Study:

  • To systematically analyze the consistency of major scientific databases.
  • To evaluate the reliability of bibliometric data for studying science.
  • To identify discrepancies among scientific databases.

Main Methods:

  • Utilized complex network analysis.
  • Conducted a systematic comparison of six major scientific databases.
  • Assessed the mutual consistency of database information.

Main Results:

  • No single database emerged as definitively "best".
  • Appreciable differences were found in the mutual consistency between databases.
  • Database inconsistencies pose challenges for bibliometric studies.

Conclusions:

  • Database consistency is a critical factor for accurate bibliometric analysis.
  • Findings provide insights for future bibliometric research and database development.
  • Understanding database differences is essential for studying the science of science.