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This summary is machine-generated.

This study presents a protocol for comprehensive scientometric analysis using the Science Performance Evaluation (SciPE) web application. It enables detailed evaluation and contextualization of global research output and scientific efforts.

Keywords:
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Area of Science:

  • Bibliometrics and Scientometrics
  • Bioinformatics
  • Data Science

Background:

  • Scientometric analyses are crucial for evaluating research impact and productivity.
  • Existing methods may lack comprehensive data integration and visualization capabilities.
  • A structured protocol is needed for advanced scientometric studies.

Purpose of the Study:

  • To develop a structured study protocol for comprehensive scientometric analyses.
  • To utilize the Science Performance Evaluation (SciPE) web application for this purpose.
  • To enable precise evaluation and contextualization of scientific efforts.

Main Methods:

  • Metadata processing from online databases.
  • Visualization using undirected multipartite graphs and partitioned node sets.
  • Normalization and merging of institution-specific data for geocoordinate positioning and heatmapping.
  • Implementation of bioinformatic methods including heatmapping and chord diagrams.
  • Calculation of country-specific modified Hirsch Index and relevant ratios (e.g., population/publication).

Main Results:

  • Obtained verified, processed data on articles, institutions, journals, author gender, nations, and subject categories.
  • Enabled precise geocoordinate positioning for heatmapping and identification.
  • Demonstrated the utility of specific ratios and visualization techniques for research output analysis.
  • Facilitated the contextualization of research performance across nations and topics.

Conclusions:

  • The developed protocol enables precise, contemporaneous scientometric analyses.
  • Bioinformatic and meta-analytical techniques are key for evaluating scientific efforts.
  • Mandatory data presentation with depicted visualization techniques ensures transparent and consistent research output analyses.
  • Research performance can be effectively discussed through a synopsis of all findings.