Proveniência de dados e metadados em repositórios de dados de pesquisa

• Ano de defesa: 2025
• Autor(a) principal: Silva, Felipe Ivo da
• Orientador(a): Arakaki, Felipe Augusto
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Informação - PPGCI
• Palavras-chave em Português: Metadados; Dados; Proveniência; Repositórios de dados de pesquisa
• Área do conhecimento CNPq: CIENCIAS SOCIAIS APLICADAS::CIENCIA DA INFORMACAO
• Link de acesso: https://hdl.handle.net/20.500.14289/21866

Research data repositories are environments for storing, preserving, and sharing scientific data, and ensure accessibility and reuse of data. Provenance, which documents the origin, history, and transformations of data, is essential to ensure the tradition, reliability, and traceability of information. However, the lack of standardization and interoperability between the main metadata standards in these repositories can compromise the effectiveness of provenance. In this context, the central question of this research was: do the metadata standards used to describe data in research repositories ensure traceability and prevent information from becoming obsolete over time? The general objective of the study was to evaluate the adherence of provenance metadata, based on the PROV Family, to the main metadata standards used in research data repositories according to Re3data, such as Dublin Core, DataCite, and DDI. The research sought to identify how these standards can assist in identifying deficiency and traceability of information, proposing recommendations for their application. The methodology adopted was theoretical and exploratory, using a bibliographic survey in recognized databases, analysis of specialized literature and the Crosswalk method to map and compare metadata standards in relation to PROV-O. The analysis focused on the interoperability between the standards and the PROV Family, eventually identifying possible adaptations to improve semantic interoperability. The main results indicated that the developed standards have different degrees of interoperability with the PROV Family. Dublin Core presented the highest relative correspondence, while DataCite and DDI presented lower levels of interoperability. Despite the integration suggestions, limitations were specified that exclude adaptations to meet the semantic interoperability principles promoted by the W3C. In conclusion, the study reinforces the importance of provenance for the reliability and traceability of data in research data repositories, highlighting the need for interdisciplinary collaboration between Information Science and Computer Science to improve data management in digital environments. The research suggests the implementation of provenance metadata to promote data veracity and longevity.