ELLAS Architecture and Process: Collecting and Curating Data on Women’s Presence in STEM

Rita Cristina Galarraga Berardi; Pedro Henrique Stolarski Auceli; Cristiano Maciel; Rodgers Fritoli; Guillermo Davila; Indira R. Guzman; Luana Mendes

doi:10.5753/jis.2024.3853

Authors

Rita Cristina Galarraga Berardi Federal University of Technology - Paraná https://orcid.org/0000-0002-0281-8952
Pedro Henrique Stolarski Auceli Federal University of Technology - Paraná https://orcid.org/0009-0000-1903-7960
Cristiano Maciel Federal University of Mato Grosso | California State Polytechnic University https://orcid.org/0000-0002-2431-8457
Rodgers Fritoli Federal University of Technology - Paraná https://orcid.org/0009-0001-7696-7600
Guillermo Davila Universidad de Lima https://orcid.org/0000-0002-1479-2585
Indira R. Guzman California State Polytechnic University, Pomona https://orcid.org/0000-0003-3670-7270
Luana Mendes Foundation for Support and Development of the Federal University of Mato Grosso https://orcid.org/0009-0003-4322-5680

DOI:

https://doi.org/10.5753/jis.2024.3853

Keywords:

Knowledge Graphs, Latin America, Female Leadership, STEM, Open Data

Abstract

The underrepresentation of women in STEM fields needs to be highlighted through data to assist decision-makers and public policy creators in addressing the issue effectively. However, the lack of structured, organized data published openly in this domain is still a reality. To address this problem, a Latin American research network called ELLAS was created. The project's goal is to develop a platform with Semantic Web-based technologies to structure and concentrate data from Brazil, Peru, and Bolivia, initially. This paper presents the processes defined for the collection and curation of both unstructured and structured data, sourced from scientific articles, social networks, and existing open data. We explore the architecture design in a way that facilitates understanding of the details of the processes and the actors involved for each data source. We present the preliminary results from the application of these processes, and the strategies for future work, which include the data extraction and curation, and the ontology and knowledge graph development We also present some of the undergoing work, such as the survey development and application as well as showing what still hasn't been done, such as the platform development.

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