Content related to Taxonomy Alignment for SDG Tagging
Enterprises, KM, & AI: From Fragmented Knowledge to Intelligent Systems
In the session “Enterprises, KM, & AI: From Fragmented Knowledge to Intelligent Systems,” Jess DeMay (Enterprise Knowledge) and Rachel Teague (Emory Consulting LLC.) co-presented at KMWorld 2025, exploring how organizations can evolve from disconnected information environments into intelligent and adaptive … Continue reading
Taxonomist Role in the New World of Generative AI
We have been at the forefront of implementing generative technologies to augment traditional taxonomy workflows offering new capabilities for content modeling, classification, and semantic enrichment. This raises an important question for practitioners: What are the implications of Generative AI for … Continue reading
The Cost of Missing Critical Connections in Data: Suspicious Behavior Detection using Link Analysis
Graph-powered link analysis, combined with natural language processing (NLP), offers a powerful approach to identifying complex patterns and trends within extensive and complex datasets, especially unstructured data like emails, documents, and social media. By modeling data as interconnected entities and … Continue reading
A Healthier Knowledge Platform: Taxonomy Principles to Support Knowledge Management at a Not-for-Profit
Would your organization benefit from “healthier” knowledge management practices? Learn more about how the YMCA of the USA improved the health of key internal tools. During their presentation, “Taxonomy Principles to Support Knowledge Management at a Not-for-Profit” at KMWorld’s Taxonomy … Continue reading
Knowledge Cast – Ole Olesen-Bagneux, Vice President & Chief Evangelist at Actian
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Ole Olesen-Bagneux, Vice President & Chief Evangelist at Actian. He is a twice-published author with a BA, MA, and PhD in Library and Information Science from the University … Continue reading
How to Design Taxonomies that Reflect Organizational Differences, For Humans and AI
One of the key steps to prepare your content and data for AI is developing taxonomies that identify, organize, and define the terms used in the organization in order to better structure and contextualize knowledge assets for use in AI … Continue reading
How Taxonomies and Ontologies Enable Explainable AI
Taxonomy and ontology models are essential to unlocking the value of knowledge assets. They provide the structure needed to connect fragmented information across an organization, enabling explainable AI. As part of a broader Knowledge Intelligence (KI) strategy, these models help … Continue reading
How to Leverage LLMs for Auto-tagging & Content Enrichment
When working with organizations on key data and knowledge management initiatives, we’ve often noticed that a roadblock is the lack of quality (relevant, meaningful, or up-to-date) existing content an organization has. Stakeholders may be excited to get started with advanced … Continue reading
Defining Governance and Operating Models for AI Readiness of Knowledge Assets
Artificial intelligence (AI) solutions continue to capture both the attention and the budgets of many organizations. As we have previously explained, a critical factor to the success of your organization’s AI initiatives is the readiness of your content, data, and … Continue reading
Semantic Layer Strategy: The Core Components You Need for Successfully Implementing a Semantic Layer
Today’s organizations are flooded with opportunities to apply AI and advanced data experiences, but many struggle with where to focus first. Leaders are asking questions like: “Which AI use cases will bring the most value? How can we connect siloed … Continue reading