Eidolon: An Architecture for the Reproducible Publication of Scientific Data Collections

• Lucas Calmon Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ)
• Marcus Junior Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ)
• Lucas Santos Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ)
• Fernando Alexandrino Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ) / Institito Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
• Rafaelli Coutinho Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ)
• Gustavo Guedes Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ) https://orcid.org/0000-0001-8593-1506
• Diego Carvalho Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ)
• Eduardo Ogasawara Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ)

DOI: https://doi.org/10.5753/bresci.2026.249332

Resumo

Scientific data collections used in data analytics workflows must reconcile four aspects: (i) data curation, (ii) reusable documentation, (iii) direct integration with a computational environment, and (iv) lightweight distribution. Although repositories and portals support storage and discovery, they do not always provide a runtime usage contract. This work proposes Eidolon, a publication architecture based on curation, structural standardization, compact local miniatures, and on-demand remote expansion. The architecture is instantiated in the integration between tspredbench and tspredit. This case study indicates that Eidolon preserves local discovery, documentation, and reproducibility without embedding the full dataset in the package.

Palavras-chave: Scientific Data Publishing, Reproducible Research, Data Curation, Software Architecture, Scientific Data Collections

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