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1. Working Paper2026Open Access

   Operationalizing FAIR in National Research Information Systems: The BrCris Example and Its Role in Open Repositories(opens in a new tab)

   

   Segundo, Washington; Dias, Thiago Magela; Souza, Marcel Garcia; do Canto, Fábio Lorensi; Sena, Priscila Machado

   The adoption of the FAIR principles (Findable, Accessible, Interoperable, Reusable) has become a cornerstone of Open Science, guiding practices aimed at improving the quality, transparency, and reuse of scientific data. In the context of CRIS (Current Research Information Systems), these principles play a strategic role in supporting the integration, standardization, and governance of scientific information on a national scale. This article analyzes the application of the FAIR principles within the Brazilian Scientific Research Information Ecosystem (BrCris), developed by the Brazilian Institute of Information in Science and Technology (Ibict), with the aim of discussing how its technical and organizational practices contribute to building a more reliable, interoperable, and reusable scientific data infrastructure. The methodology adopted is based on a literature review of the FAIR principles and a document analysis of technical reports, scientific articles, and institutional materials related to BrCris. The results indicate that BrCris shows significant progress in adopting the FAIR principles, especially in the use of persistent identifiers, semantic data integration, interoperability with international infrastructures, and the availability of data in open and reusable formats. It is concluded that BrCris constitutes a strategic infrastructure for the implementation of the FAIR principles in Brazil.

   DOI: 10.5281/zenodo.20789089OR2026FAIR PrinciplesOpen ScienceBrCris PlatformInteroperability
2. Article2026Open Access

   Interoperability between local and global databases in scientometrics: lattes, CAPES, and OpenAlex(opens in a new tab)

   

   Mazoni, Alysson; Borges, Luís; Macedo, Estevão Fernandes; Tuesta, Esteban Fernández; Mena‐Chalco, Jesús Pascual

   Funded by CAPES, FAPESP, UNICAMP

   Disambiguating research entities remains a long-standing methodological problem in scientometric analyses, as inconsistencies and ambiguous metadata limit the interoperability of major bibliographic databases. While global systems such as OpenAlex provide extensive coverage, they often lack the granularity and accuracy provided by national-level research databases. This study proposes a large-scale methodology to enhance author and institutional disambiguation by integrating local (Lattes and CAPES) and global (OpenAlex) databases. The method combines shared Digital Object Identifiers with an adapted Levenshtein distance algorithm to handle variations in author and institutional names across multilingual research databases, achieving over 97% accuracy for authors and 64% for institutions. The proposed framework provides a scalable and replicable approach for entity disambiguation in tabular research databases. Beyond the Brazilian context, this integration strategy offers a globally applicable approach for harmonizing national research information systems with open scientometric infrastructures.

   DOI: 10.1007/s11192-026-05765-0InteroperabilityIdentifierMetadataScalabilityGranularity
3. Working Paper2025Open Access

   Exploring Interoperability Between Local and Global Databases in Scientometrics: Lattes, Capes, and OpenAlex(opens in a new tab)

   

   Mazoni, Alysson Fernandes; Borges, Luís Fabiano Farias; Macedo, Estevao Fernandes; Tuesta, Esteban Fernandez

   Numerous initiatives are currently underway to disambiguate databases worldwide. In this paper, we propose a methodology for disambiguating research entities using big data techniques, adopting an approach that goes from local to global databases. Our objective is to enhance the quality of data in the OpenAlex database by leveraging information from Brazilian databases, particularly data from the Lattes Platform and the Brazilian Federal Agency for Support and Evaluation of Graduate Education. We compare similar names of authors and institutions, employing Digital Object Identifiers to link entities, along with an adaptation of the Levenshtein distance algorithm. The proposed method is straightforward to implement in tabular databases and facilitates disambiguation, thereby contributing to open science practices and providing an effective solution for research information systems. The findings indicate the potential for integrating local and global databases to address issues related to ambiguous names and incomplete metadata.

   DOI: 10.1590/SciELOPreprints.12668Bibliographic coverageLattes CVScientometrics