AnyLattes: An Application for Continuous Assessment of Lattes Curriculum Information - Cirilo, Alex Carlos Saraiva; Santos, Isadora Mendes dos; Mota, Marcelle Pereira (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI); 2025: Anais do XXI Simpósio Brasileiro de Sistemas de InformaçãoDO - 10.5753/sbsi.2025.246529, 2025)
Context: With the advancement of technology, process automation becomes increasingly necessary, especially for data analysis and organization of information for decision making. Problem: The Process of obtaining scores from conferences and journals within publications in Lattes Curriculum demands a lot of time and manual work, in addition to the need for analysis to be done jointly at universities due to the way in which capes evaluates postgraduate programs. Solution: AnyLattes – An application for automation, data extraction and organization of information from the Lattes Curriculum to assist in the evaluation of postgraduate programs, in addition to serving as a basis for filling out the Sucupira platform. SI Theory: This work is influenced by Organizational Information Processing Theory, where organizations need quality information to deal with environmental uncertainty and improve their decision making. Method: The research has a prescriptive nature along with the evaluation carried out through proof of concept, in addition to the qualitative approach for analyzing the results. Summary of results: In the experiments carried out, AnyLattes showed optimization in the data extraction routine and organization and grouping of information for analysis of postgraduate programs in comparison to commonly used means. Contributions and Impact in the IS area: The contribution is to enable an application focused on optimizing, organizing and grouping information extracted from Lattes Curriculum for postgraduate programs, have a view of the entire program and proceed with consistent data in their decision making.