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Assessing database accuracy for article retractions: A preliminary study comparing Retraction Watch Database, PubMed,
1University Institute for Primary Care (IuMFE), University of Geneva, Geneva, Switzerland.
Accountability in Research
|February 20, 2025
Summary
Metadata accuracy varies across retraction databases. The Retraction Watch Database (RWD) had more errors than PubMed and Web of Science (WoS), highlighting the need for cross-database verification of retracted article data.
Area of Science:
- Bibliometrics
- Scholarly Communication
- Research Integrity
Background:
- Retracted articles pose challenges to scientific literature integrity.
- Accurate metadata is crucial for identifying and tracking retractions.
- Discrepancies in bibliographic databases can hinder research on retractions.
Purpose of the Study:
- To compare the accuracy of metadata for retracted articles across three major databases: Retraction Watch Database (RWD), PubMed, and Web of Science (WoS).
- To identify the types and frequency of metadata errors in each database.
Main Methods:
- Randomly selected 20 general internal medicine journals with an impact factor > 2.
- Retrieved retracted articles from RWD, PubMed, and WoS.
- Analyzed eight metadata variables: journal, title, article type, authors, affiliation country, publication year, retraction year, and retraction reason.
Main Results:
- Analyzed 35 retractions and 280 metadata entries.
- Retraction Watch Database (RWD) exhibited the highest error rate (20 errors across 16 articles), including issues with publication year, article type, author names, and affiliation country.
- Web of Science (WoS) had one author error, and PubMed had no metadata errors in this sample.
Conclusions:
- The Retraction Watch Database (RWD) shows a higher incidence of metadata errors compared to PubMed and Web of Science (WoS).
- Researchers should verify retracted article metadata across multiple databases to ensure accuracy.
- Further large-scale studies are recommended to confirm these findings and enhance the reliability of retraction databases.
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