DIP-BR: An Open and Network-Based Dataset of Brazilian Patents

• Pablo Vasconcelos da Cruz Federal Center for Technological Education of Minas Gerais (CEFET-MG) http://orcid.org/0009-0004-0494-4196
• Iuri V. A. Lima Federal Center for Technological Education of Minas Gerais (CEFET-MG) https://orcid.org/0009-0000-3104-9040
• Danilo B. Seufitelli Federal University of Minas Gerais (UFMG) https://orcid.org/0000-0002-0155-7631
• Daniel H. Dalip Federal Center for Technological Education of Minas Gerais (CEFET-MG)
• Fabricio P. V. de Campos Federal University of Juiz de Fora (UFJF) https://orcid.org/0009-0004-9522-7351

DOI: https://doi.org/10.5753/dsw.2025.248102

Abstract

The gap between research institutions and industry leads to a significant challenge for technology transfer. Patent analysis is a strategic tool for unveiling collaborations between companies and research institutions. In this context, we introduce DIP-BR, an open research dataset of Brazilian intellectual property. This dataset is enriched by applying a deduplication algorithm to standardize names and using machine learning techniques to classify each patent holder as a research institution, company, or individual. The primary contribution of this work is the resulting enriched dataset, which is structured through network modeling and clustering. DIP-BR serves as a tool for analyzing trends and visualizing the dynamics of innovation in Brazil.

Keywords: Patent, Technology Transfer, Intellectual Property

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