Schema Aware Conversational Data Collection - Alves, Lucas Emmanuel de Sousa; C. Campelo, Claudio E. (Anais do Simpósio Brasileiro de Banco de Dados (SBBD); 2026: Anais do XLI Simpósio Brasileiro de Bancos de DadosDO - 10.5753/sbbd.2026.249461, 2026)
This paper proposes a conversational approach to structured data collection using an automated agent that addresses limitations of traditional form-based methods. Guided by a predefined schema of attributes, types, and constraints, the agent conducts dialogues to clarify ambiguities, complete missing information, and validate data in real time while minimizing the number of interactions. To support this, we developed a Python library enabling rapid creation of applications that proactively request user input. Using this library, we built a chatbot evaluated through user-based experiments in a culinary habits case study. Results show the approach effectively validates constraints, supports semantic inference, and guides users to provide complete and consistent data.