Deja vu: a database of highly similar citations in the scientific literature
Long, Tara C.
George, Angela C.
Garner, Harold R.
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In the scientific research community, plagiarism and covert multiple publications of the same data are considered unacceptable because they undermine the public confidence in the scientific integrity. Yet, little has been done to help authors and editors to identify highly similar citations, which sometimes may represent cases of unethical duplication. For this reason, we have made available De´ ja` vu, a publicly available database of highly similar Medline citations identified by the text similarity search engine eTBLAST. Following manual verification, highly similar citation pairs are classified into various categories ranging from duplicates with different authors to sanctioned duplicates. De´ ja` vu records also contain user-provided commentary and supporting information to substantiate each document’s categorization. De´ ja` vu and eTBLAST are available to authors, editors, reviewers, ethicists and sociologists to study, intercept, annotate and deter questionable publication practices. These tools are part of a sustained effort to enhance the quality of Medline as ‘the’ biomedical corpus. The De´ ja` vu database is freely accessible at http://spore.swmed.edu/dejavu. The tool eTBLAST is also freely available at http://etblast.org.