Detecting referential inconsistencies in electronic CV datasets

Abstract

One way to measure the scientific progress of a country is to evaluate the curriculum vitae (CV) of its researchers. In Brazil, this is not different. The Lattes Platform is an information system whose primary objective is to provide a single repository to store the CV of the Brazilian researchers. This system is increasingly acquiring expressiveness as the main source of information regarding the Brazilian community of researchers, students, managers, and other actors in the national system of science, technology, and innovation. However, the integrity of this important tool for gaging the national bibliographic production may be affected by the effect of ambiguities or referential inconsistencies in coauthoring citations. A first step towards solving this problem lies in identifying such inconsistencies. For that, we propose a heuristic-based approach that uses similarity search to match papers from coauthors of CV. We then use this technique to analyze over 2000 curricula of researchers from a given institution recovered from the Lattes Platform. The results indicate 18.98% of the analyzed publications present referential inconsistencies, which is a significant amount for a dataset that is supposed to be correct and trustable.

The prevalence and impact of university affiliation discrepancies between four bibliographic databases—Scopus, Web of Science, Dimensions, and Microsoft Academic

“…The figures were lower for all document types and much lower in the arts & humanities, 50% for journal citable items and just 20% for books and book chapters. Articles published in regional publications may also be less associated with DOIs, a sample of scholars from Brazil showed DOIs among less than half of their journal papers and less than a tenth of their conference papers (Rubim & Braganholo, 2017). Meanwhile, Mugnaini et al (2021) found the presence of international co-authors increased the proportion of DOIs.…”