BDI-Kit Demo: A Toolkit for Programmable and Conversational Data Harmonization

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Authors: Roque Lopez, Yurong Liu, Christos Koutras, Juliana Freire
Cited by: 1
References: 8

Abstract

Data harmonization remains a major bottleneck for integrative analysis due to heterogeneity in schemas, value representations, and domain-specific conventions. BDI-Kit provides an extensible toolkit for schema and value matching. It exposes two complementary interfaces tailored to different user needs: a Python API enabling developers to construct harmonization pipelines programmatically, and an AI-assisted chat interface allowing domain experts to harmonize data through natural language dialogue. This demonstration showcases how users interact with BDI-Kit to iteratively explore, validate, and refine schema and value matches through a combination of automated matching, AI-assisted reasoning, and user-driven refinement. We present two scenarios: (i) using the Python API to programmatically compose primitives, examine intermediate outputs, and reuse transformations; and (ii) conversing with the AI assistant in natural language to access BDI-Kit's capabilities and iteratively refine outputs based on the assistant's suggestions.

Fields of Study & Subjects

Natural Language Processing Techniques Topic Modeling Speech Recognition and Synthesis

Publication details

Journal / source
Companion of the International Conference on Management of Data
Publisher
ACM
Pages
94–97
Publication date
26 May 2026