Published on March 21, 2024, Hulsebos’s project focuses on narrowing the data literacy gap between small institutions and large corporations. With approximately 120 zettabytes of data collected globally, less than 1% is actually utilized. A large portion of this data is structured, such as tables, spreadsheets, and relational databases, which are crucial for decision-making processes in healthcare, government, and finance sectors.

With the DataLibra project, Hulsebos aims to democratize insight from (semi-)structured data through Table Representation Learning. The goal is to provide trustworthy, secure, and responsible data analytics, enabling everyone to make data-driven decisions easily, effectively, and efficiently. The project addresses challenges throughout the entire data analytics pipeline, including efficient data storage, query execution, automated responsible data quality improvement, multimodal data integration and querying, and retrieval systems. This five-year project will involve collaborations across various knowledge institutes and innovation labs due to its multidisciplinary nature.

Hulsebos, who was previously a postdoctoral fellow at UC Berkeley and earned her PhD from the University of Amsterdam, will start her tenure track position at the Database Architectures group of CWI in fall 2024. Her research focuses on the intersection of data management and machine learning, with recent contributions to methods, tools, and resources for Table Representation Learning.