DRE-CVM: Exploring Financial Data Enriched with Provenance and FAIR Principles of Brazilian Public Companies

• Gilberto Gil F. Gomes Passos Federal University of Rio de Janeiro
• Saulo A. Almeida Federal University of Rio de Janeiro
• Valquire da S. de Jesus Federal University of Rio de Janeiro http://orcid.org/0009-0003-5800-838X
• Jorge Zavaleta Federal University of Rio de Janeiro https://orcid.org/0000-0002-4747-8613
• Sérgio Manuel Serra da Cruz Federal University of Rio de Janeiro

DOI: https://doi.org/10.5753/sbbd.2023.232527

Abstract

Since 2005, the Organization for Economic Cooperation and Development (OECD) has encouraged the implementation of Financial Education (FE) initiatives for young people in various countries. The lack of FE can lead to financial difficulties for individuals, families, and businesses. With the aim of democratizing access to FE and promoting reflections on Economics and Finance for high school students throughout the country, the Brazilian Investment Olympiad (OBInvest) was created. This work presents the computational strategy DRE-CVM, which provides curated data series for OBInvest. Its architecture includes reproducible pipelines in container environments that generate high quality datasets, FAIRified and annotated with provenance metadata on financial information from the Securities and Exchange Commission.

Keywords: Data Science, Data Provenance, Pipelines

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