ReTracker: Actively and automatically matching retraction metadata in zotero

Yi Yun Cheng, Nikolaus Parulian, Tzu Kun Hsiao, Ly Dinh, Janina Sarol, Jodi Schneider

Research output: Contribution to journalArticle

Abstract

Retraction removes seriously flawed papers from the scientific literature. However, even papers retracted for scientific fraud continue to be cited and used as valid after their retraction. Retracted papers are inadequately identified on publisher pages and in scholarly databases, and scholars' personal libraries frequently contain retracted papers. To address this, we are developing a tool called ReTracker (https://github.com/nikolausn/ReTrackers) that automatically checks a user's Zotero library for retracted articles, and adds retraction status as a new metadata field directly in the library. In this paper, we present the current version of ReTracker, which automatically flags retracted articles from PubMed. We describe how we have iteratively improved ReTracker's matching performance through its initial two versions. Our tests show that the current version of ReTracker is able to flag retracted articles from PubMed with high precision and recall, and to distinguish retracted articles from articles about retraction. In its current state, ReTracker can actively and automatically bring retraction metadata into Zotero, and in future work we will test its usability with scholars.

Original languageEnglish (US)
Pages (from-to)372-376
Number of pages5
JournalProceedings of the Association for Information Science and Technology
Volume56
Issue number1
DOIs
StatePublished - Jan 1 2019

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Keywords

  • Publishing Ethics
  • Retraction
  • Scholarly Communication

ASJC Scopus subject areas

  • Computer Science(all)
  • Library and Information Sciences

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