Use of open data to analyze the publication of articles in scientific events

Abstract

Objective. This article has analyzed the publications of articles in scientific events using open data from the Lattes Platform. Design/Methodology/Approach. The LattesDataXplorer tool was used to extract curricular data from the Lattes Platform. The selection stage consisted of verifying which curricula had works published in scientific events. In the treatment stage, a characterization of the articles was carried out, thus allowing the analysis of articles published in scientific events. Results/Discussion. It was possible to carry out some characterizations such as temporal analysis, analysis by a large area of expertise, and which articles use persistent identifiers. The temporal analysis made it possible to verify how many articles were published per year. Through the analysis by a large area of action, the individuals with the highest and lowest rate of publication in annals of events were identified. Approximately 3% of articles report the persistent identifier (DOI). Conclusions. The peak of publications is in 2011, afterwards, there was a significant drop. Individuals from Health Sciences have a higher rate of publication in event proceedings, while individuals from the Exact and Earth Sciences have a lower volume of publications. Only 30,936 of the articles have a persistent identifier, but individuals from the Exact and Earth Sciences (30.68%) are the ones who use persistent identifiers the most. Originality/Value. From data extracted from the Lattes Platform, the results of original research that seeks to characterize Brazilian scientific production utilizing events are presented.

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Stored only when both papers are in the corpus — 7 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.