Data harmonization is an essential task that entails integrating datasets from diverse sources. Despite years of research in this area, it remains a time-consuming and challenging task due to schema mismatches, varying terminologies, and differences in data collection methodologies. This paper presents the case for agentic data harmonization as a means to both empower experts to harmonize their data and to streamline the process. We introduce Harmonia, a system that combines LLM-based reasoning, an interactive user interface, and a library of data harmonization primitives to automate the synthesis of data harmonization pipelines. We demonstrate Harmonia in a clinical data harmonization scenario, where it helps to interactively create reusable pipelines that map datasets to a standard format. Finally, we discuss challenges and open problems, and suggest research directions for advancing our vision.
@article{arxiv.2502.07132,
title = {Interactive Data Harmonization with LLM Agents: Opportunities and Challenges},
author = {Aécio Santos and Eduardo H. M. Pena and Roque Lopez and Juliana Freire},
journal= {arXiv preprint arXiv:2502.07132},
year = {2025}
}