Dean Allemang

Dean Allemang literally wrote the book on the semantic web. "Semantic Web for the Working Ontologist" is now in its third edition.

In the book, Dean and his co-authors, James Hendler and Fabien Gandon, show how to apply web standards to build a meaningful web of global, connected knowledge.

More recently, Dean has conducted research with his colleagues at data.world that shows how using knowledge graphs can triple the accuracy of LLM-based question-answering systems.

We talked about:

his role as a principal solutions architect at data.world

the meaning of the "semantic web" and its intent of sharing meaning across the web

the long history of knowledge representation and how the connectedness of the semantic web adds to it

the crucial difference between documents about things and the strings that describe them

the contrast between the persistent nature of enterprise data and the ephemerality of the applications that use the data

the power of the simple structure of RDF, its mathematical affordances, and the ease of distribution it permits

the impact of newer AI tech on knowledge graph building and querying

the research that he and Juan Sequeda have conducted that shows how using knowledge graphs can triple the accuracy of LLM-based question-answering systems

his thoughts on the yet-to-be-resolved one-way or two-way ontology question

the crucial role of trust in AI and how replacing LLMs with knowledge graphs as the point of contact in AI systems could build more trust

Dean's bio

Dean Allemang has been active in the field of Artificial Intelligence (AI) since the 1980s. With a notable emphasis on Semantic Web, he is the author of the book "Semantic Web for the Working Ontologist." His passion for understanding and implementing knowledge graphs led to a significant publication about using LLMs to answer queries over structured data, which introduced a new benchmark for evaluation.

In his current role as a Principal Solutions Architect at data.world, he contributes extensively to the development of the AI Context Engine product, which is inspired by his recent research (with Juan Sequeda and Bryon Jacob), and underscores his commitment to practical application of theoretical principles.

For a span of about a decode, Dean operated as an independent consultant, utilizing knowledge graph solutions to address challenges in industries such as Media, Finance, and Life Sciences. This diverse experience has cultivated a broad perspective on applying AI and Semantic Web principles.

Influenced by Sir Tim Berners-Lee's concept of linked data and data sharing, Dean Allemang's work reflects a consistent focus on these principles. His contributions have advanced the field of AI and his current interest lies in how knowledge graphs can make generative AI more effective.

Connect with Dean online

LinkedIn

Medium

Resources mentioned in this interview

Semantic Web for the Working Ontologist

A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases, Juan Sequeda, Dean Allemang, Bryon Jacob

The Semantic Web, Tim Berners-Lee, James Hendler, and Ora Lassila

Video

Here’s the video version of our conversation:

https://youtu.be/29kmAc6tobU

Podcast intro transcript

This is the Knowledge Graph Insights podcast, episode number 6. Long before the introduction of the semantic web - the innovation that added meaning and metadata to documents on the web - AI pioneers like Dean Allemang had been thinking about how knowledge could be formalized to help people do their work. The web itself, along with the W3C standards that power its semantic capabilities, gave Dean and his peers the ability to scale and connect existing practices and technologies to build a more meaningful web.

Interview transcript

Larry:

Things. Hi everyone. Welcome to episode number six of the Knowledge Grap...