This line of research seeks to establish the theoretical and practical foundations on which future data-centric platforms and systems will be built. It focuses on anticipating emerging requirements—such as efficiency, explainability, expressiveness, fairness, privacy, among others—and developing tools capable of addressing them.

From a theoretical perspective, new formalisms, languages, and computational results based on formal methods are proposed. At the experimental level, prototype systems are designed and implemented to study the behavior of these tools in real or synthetic data contexts.

This flagship project acts as a bridge between conceptual development and empirical validation, driving advances in key areas such as explainable artificial intelligence, differential privacy, and the integration of these methods into knowledge graph-oriented systems.

Pablo Barceló, from the Institute of Computational Mathematical Engineering at the Catholic University of Chile, together with Aidan Hogan, director of the Department of Computer Science at the University of Chile, are the leaders of this line of work.

The team is made up of Susana Eyheramendy (Faculty of Engineering and Sciences, Adolfo Ibáñez University), Éric Tanter (Department of Computer Science, University of Chile), Jorge Baier (Department of Computer Science, Catholic University of Chile), Federico Olmedo (Department of Computer Science, University of Chile), Cristian Riveros (Department of Computer Science, Catholic University of Chile), Leopoldo Bertossi ( San Sebastián University), and Matías Toro (Department of Computer Science, University of Chile).

Leaders of the research line

Research team