Taxonomy Fundamentals
Length: 1 Hour 45 Minutes
Speaker(s):
Heather Hedden, Taxonomy Consultant, Hedden Information Management
Description: This introductory taxonomy tutorial covers key concepts to get you up-to-speed for the rest of the conference or helps prepare you to take on a role in a taxonomy project. Topics include what taxonomies are, the various uses and benefits of taxonomies, comparisons of taxonomies with other knowledge organization systems, standards for taxonomies, taxonomy creation research and sources for concepts, the wording of concept lapels, best practices for creating hierarchical relationships, the structural design of hierarchies and facets, and brief introductions to other issues related to taxonomy management.
Taxonomy Applications
Length: 1 Hour 45 Minutes
Speaker(s):
Brian Provenzale, Senior Manager of Information Architecture, Electronic Arts
Michele Ann Jenkins, Senior Consultant, Dovecot Studio
Ashish Garg, Principal Product Manager, Walmart
Amelia Quintero, Manager, Information Governance & Compliance, Cheniere Energy, Inc.
Claudette Lloyd, Principal Consultant, Access Sciences
Seth Earley, CEO, Earley Information Science
Heather Eisenbraun, Chief Knowledge Architect, Earley Information Science
Title: Growing Pains: A Taxonomy Road-Mapping Case Study for AI Readiness
Time: 10:15 AM - 10:40 AM
Description: Large organizations increasingly rely on AI applications such as conversational bots, auto-classification, routing rules, and analytics workflows, yet many existing vocabularies were never designed to support those demands. Hear about a taxonomy readiness assessment conducted for Electronic Arts, whose web-focused taxonomy needed to support multiple AI and operational use cases with conflicting semantic requirements. Conversational systems required terminology aligned to user intent and natural language variation, while auto-classification, routing, and reporting depended on consistency, granularity, and stability. Provenzale and Jenkins explore how each use case was analyzed for its distinct taxonomy, governance, and technical requirements; where those requirements conflicted with the existing vocabulary and with each other; and how the findings informed a prioritized road map for evolving the organization’s semantic infrastructure to support enterprise AI initiatives.
Title: The Taxonomy Underneath: Why Intake Determines Global Content Quality
Time: 10:40 AM - 11:10 AM
Description: Global content programs increasingly adopt AI, but many lack the taxonomy and shared vocabulary needed to support reliable automation. Without a structured framework for classifying requests, organizations risk accelerating ambiguity and producing results they cannot effectively measure or trust. One of the highest-leverage investments in AI-driven multilingual content operations is an intake taxonomy that defines elements such as market, intent, audience, brand voice, regulatory context, and success criteria. Drawing on enterprise-scale content operations experience, Garg outlines a practical framework for defining intake taxonomies, establishing scoring and routing rules, and connecting outcomes to measurable categories. This approach positions taxonomy as the foundation that enables AI to support scalable, consistent, and accountable content operations.
Title: From Legacy Burden to Strategic Asset: A Taxonomy Transformation Story
Time: 11:10 AM - 11:35 AM
Description: In the energy industry, reliable technical information supports safety, operational excellence, and environmental stewardship. This case study examines how a leading energy company used an enterprise taxonomy and knowledge model to transform metadata for more than 2.1 million technical documents during migration, from legacy repositories to a new enterprise document management system. The taxonomy and knowledge model provided the semantic context needed to analyze inconsistent or incomplete metadata and automatically apply standardized values such as discipline, document type, area, and system. The multiyear effort addressed active projects, completed projects, and legacy operational content with minimal metadata. Lloyd demonstrates how enterprise taxonomy and knowledge modeling strengthen information quality, improve discoverability, and increase organizational trust in critical information assets.
Title: From Maps to Models: Using Structured Content to Seed Enterprise Ontologies for GenAI
Time: 11:35 AM - 12:00 PM
Description: As organizations race to deploy RAG, they often discover that unstructured content cannot become AI-ready overnight. Earley and Eisenbraun argue that many organizations already possess an underutilized asset: structured content that already acts as a map of enterprise knowledge. Using DITA as a concrete example, they demonstrate how to treat content hierarchies as seed triples for a knowledge graph, enrich content chunks with map-based metadata to preserve context during retrieval, and leverage existing libraries to build authoritative AI. Regardless of your current tech stack, discover a way to look at your own assets and ask a vital question: What here is already a triple?