Autossuficiência na plataforma ELLAS: controle de qualidade na integração de grafos de conhecimento

Abstract

The project “Latin American Open Data for Gender Equality Policies Focusing on Leadership in STEM”, known by the acronym ELLAS – the name of the international research network formed to carry it out – was created in 2022 with the aim of building a platform of connected open data seeking to reduce the gender gap in the areas of Science, Technology, Engineering and Mathematics (STEM), especially in leadership positions in universities, public institutions and industries. The initiative involves collecting data on female participation in these areas using bibliographic sources, social media, specific forms, and other sources. With financial support expected to end in 2025, ensuring the continuous addition of new data without the need for manual curation is essential. Thus, this work aims to develop an automated system for quality control of new data, allowing users to contribute without requiring specialized knowledge. The methodology includes mapping data quality constraints based on the dimensions of Consistency, Validity, and Identity and implementing an integration system into the existing knowledge graph, ensuring data governance and promoting continuous collaboration. The results include greater efficiency in data validation and project sustainability, ensuring the expansion of the knowledge base without direct dependence on the initial team. It is concluded that automating this process will significantly contribute to the self-sufficiency of the ELLAS platform.