Change Management Through The Ontology Pipeline with Jessica Talisman

ESTES PARK GROUP: We will be hosting Jessica Talisman, Senior Information Architect at Adobe this May for Semantic Arts, Inc.'s Estes Park Group, a non-salesy monthly virtual community gathering where guest speakers are invited to share lessons learned from their work developing data-centric architectures. This session will be co-moderated by Steve Case and Joaquin Melara. ABOUT THE SESSION: "Change Management through The Ontology Pipeline" Organized, structured, and semi-structured semantic knowledge systems are finally being recognized as a core foundation for performant LLM and AI systems. Yet technologists— who are not accustomed to thinking through a holistic socio-technical perspective— often dismiss semantic knowledge systems as overly simplistic and flat, consisting of little more than text labels or annotations. Business stakeholders may view the investment in developing semantic knowledge graphs as labor-intensive, complex, and a luxury rather than a competitive advantage. This leads organizations to deploy watered-down, off-the-shelf taxonomies or ontologies that only partially meet domain or business needs. However, a semantic knowledge-graph system is essential for all subsequent AI development— data products, machine-learning algorithms, generative AI/LLM implementations, and more. You can’t build a skyscraper on sand—and you can’t build enterprise AI on top of bad data. KEY TOPICS: The growing recognition of semantic knowledge systems as foundational for high-performance LLM and AI. Technologists’ misconceptions—viewing semantic systems as simplistic, label-only artifacts. Business stakeholders’ skepticism—seeing knowledge-graph investments as costly, complex, and nonessential. The necessity of robust semantic knowledge graphs as the data foundation for all AI initiatives. LINK TO ARTICLE: https://moderndata101.substack.com/p/... ABOUT JESSICA TALISMAN: Jessica Talisman has dedicated her career to exploring the dynamics of information and knowledge, and how information flows across systems. Her experiences range from historical contexts to educational frameworks and extends to the realms of artificial intelligence and its application within enterprise knowledge systems. She is an active contributor in codifying knowledge management techniques, founded in the discipline of library science. As a librarian, she evangelizes the importance of high-quality data as a prerequisite to rendering truthful and reliable AI systems. Currently, she is a Senior Information Architect at Adobe, building semantic knowledge graphs for content and context setting. She believes in the importance of bridging the gaps between library science and data management, to enable robust knowledge management systems that can support innovation in AI.