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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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Interpreting Bibliometric Data.

Martin Szomszor1, Jonathan Adams1, Ryan Fry2

  • 1Institute for Scientific Information, Clarivate, London, United Kingdom.

Frontiers in Research Metrics and Analytics
|April 19, 2021
PubMed
Summary
This summary is machine-generated.

Bibliometric data analysis should prioritize user needs over technical details for better understanding. Simple, transparent quantitative evaluation is key for research managers to avoid flawed investment decisions.

Keywords:
bibliometricsdata interpretationresearch assessmentresearch policyresponsible metrics

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Area of Science:

  • Bibliometrics and Scientometrics
  • Research Evaluation
  • Science Policy

Background:

  • Academic analyses of bibliometric data often overlook user needs, focusing narrowly on technical aspects.
  • Bibliometric indicators are typically used alongside other evidence, not in isolation.
  • Current research evaluation practices may overemphasize precision at the expense of user comprehension.

Purpose of the Study:

  • To highlight the importance of user requirements in bibliometric data analysis.
  • To advocate for simpler, more transparent quantitative evaluation methods.
  • To demonstrate how data presentation and composition affect the interpretation of research performance.

Main Methods:

  • Discussion of academic literature on bibliometric data use.
  • Analysis of how iterative deconstruction and visualization alter performance interpretation.
  • Exploration of real-life data samples to illustrate interpretive influences.

Main Results:

  • Focusing solely on technical accuracy in bibliometrics can obscure user needs and practical application.
  • Simplified and transparent quantitative evaluation methods are more crucial than technical purity.
  • The way bibliometric data is presented and its specific composition significantly impact how research performance is understood.

Conclusions:

  • Research evaluation frameworks must integrate user perspectives for effective bibliometric data utilization.
  • Prioritizing clarity and accessibility in bibliometrics supports better-informed decision-making for research managers.
  • Understanding the influence of data presentation and composition is vital for accurate research performance assessment.