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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.
Plos One
|May 19, 2015
Summary
Analyzing scientific databases reveals inconsistencies. This study uses complex networks to compare six major databases, finding significant differences that impact bibliometric studies.
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.
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