Managing semantic evolution in databases: from theory to implementation - Nepomuceno, Pedro Ivo Siqueira; Braghetto, Kelly Rosa (Anais do Concurso de Teses e Dissertações da SBC (CTD-SBC); 2026: Anais do XXXIX Concurso de Teses e DissertaçõesDO - 10.5753/ctd.2026.19637, 2026)
Semantic heterogeneity in long-term datasets emerges as categories, groupings, and units change over time, requiring users to manually adapt queries and results. The master’s thesis proposes a formal framework to address this issue through two strategies: query rewriting and data preprocessing. It introduces storage models and algorithms that manage semantic evolution via discrete, time-stamped operations (translation, merging, and splitting), enabling queries to be written as if the data were homogeneous. A prototype, MellowDB, was evaluated using Brazilian mortality data (1979–2021). Results show both approaches are production-ready, with data preprocessing generally outperforming query rewriting except in highly write-heavy scenarios.