AI Ready Data: Why Does AI Look for Data First?
Session Overview
The success of an AI project is no longer determined by the model — it's determined by the data. With the rise of generative AI and AI agents, ontologies and knowledge graphs are drawing renewed attention.
But what AI actually uses isn't the ontology itself — it's AI Ready Data: data prepared so that AI can understand and act on it. This talk shows how data quality, standardization, ontology, and knowledge graphs connect into a single data-readiness pipeline.
Through a live demo, the speakers will present the data preparation strategy and implementation approach needed for the age of AI agents.
Speakers
A researcher of meaning and relationships. Professor Haklae Kim is a professor in the Department of Library and Information Science at Chung-Ang University and the author of Knowledge Graphs for Ontology Scientists.
He has built a research career around semantics-based data using ontologies and knowledge graphs, and his current work focuses on AI Ready Data for AI agents, data quality, standardization, and public data.
A PhD researcher. Jeongyun Lee is currently pursuing her PhD in the Department of Library and Information Science at Chung-Ang University's Graduate School.
She is a researcher at HIKE Lab, where she studies ontology and knowledge structuring through a data-centric approach.