In the rapidly evolving landscape of information science, the development and maintenance of ontologies and terminologies are critical for ensuring accurate data representation and interoperability across various domains.
This webinar aims to explore the transformative potential of artificial intelligence, specifically Large Language Models (LLMs), in streamlining and augmenting the creation of these essential knowledge structures. Attendees will gain insights into how AI can assist users in building comprehensive reference terminologies and ontologies more efficiently, thereby saving valuable time and resources. We will delve into early results from recent studies, demonstrating the practical applications and benefits of LLMs in this context.
Join us to discover innovative methodologies, share experiences, and discuss future directions for integrating AI into ontology and terminology development workflows.
This session is ideal for data scientists, knowledge engineers, domain experts, and anyone interested in the intersection of AI and knowledge management.
Simon Jupp
Head of Semantic Technology, SciBite
Simon is the head of Semantic Technology at SciBite, where he leads the development of CENtree, an innovative Enterprise Ontology Management solution. Simon’s interests are focused on how semantic technologies can be utilised to address the complex challenges of large-scale data interoperability. He is an expert in developing and applying ontologies within the life sciences and is advancing these technologies at Elsevier.
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