Knowledge Graph Insights

Épisodes disponibles

5 sur 10

Dave McComb: Semantic Modeling for the Data-Centric Enterprise – Episode 29
Dave McComb During the course of his 25-year consulting career, Dave McComb has discovered both a foundational problem in enterprise architectures and the solution to it. The problem lies in application-focused software engineering that results in an inefficient explosion of redundant solutions that draw on overlapping data sources. The solution that Dave has introduced is a data-centric architecture approach that treats data like the precious business asset that it is. We talked about: his work as the CEO of Semantic Arts, a prominent semantic technology and knowledge graph consultancy based in the US the application-centric quagmire that most modern enterprises find themselves trapped in data centricity, the antidote to application centricity his early work in semantic modeling how the discovery of the "core model" in an enterprise facilitates modeling and building data-centric enterprise systems the importance of "baby step" approaches and working with actual customer data in enterprise data projects how building to "enduring business themes" rather than to the needs of individual applications creates a more solid foundation for enterprise architectures his current interest in developing a semantic model for the accounting field, drawing on his history in the field and on Semantic Arts' gist upper ontology the importance of the concept of a "commitment" in an accounting model how his approach to financial modeling permits near-real-time reporting his Data-Centric Architecture Forum, a practitioner-focused event held each June in Ft. Collins, Colorado Dave's bio Dave McComb is the CEO of Semantic Arts. In 2000 he co-founded Semantic Arts with the aim of bringing semantic technology to Enterprises. From 2000- 2010 Semantic Arts focused on ways to improve enterprise architecture through ontology modeling and design. Around 2010 Semantic Arts began helping clients more directly with implementation, which led to the use of Knowledge Graphs in Enterprises. Semantic Arts has conducted over 100 successful projects with a number of well know firms including Morgan Stanley, Electronic Arts, Amgen, Standard & Poors, Schneider-Electric, MD Anderson, the International Monetary Fund, Procter & Gamble, Goldman Sachs as well as a number of government agencies. Dave is the author of Semantics in Business Systems (2003), which made the case for using Semantics to improve the design of information systems, Software Wasteland (2018) which points out how application-centric thinking has led to the deplorable state of enterprise systems and The Data-Centric Revolution (2019) which outlines a alternative to the application-centric quagmire. Prior to founding Semantic Arts he was VP of Engineering for Velocity Healthcare, a dot com startup that pioneered the model driven approach to software development. He was granted three patents on the architecture developed at Velocity. Prior to that he was with a small consulting firm: First Principles Consulting. Prior to that he was part of the problem. Connect with Dave online LinkedIn email: mccomb at semanticarts dot com Semantic Arts Resources mentioned in this interview Dave's books: The Data-Centric Revolution: Restoring Sanity to Enterprise Information Systems Software Wasteland: How the Application-Centric Quagmire is Hobbling Our Enterprises Semantics in Business Systems: The Savvy Manager's Guide gist ontology Data-Centric Architecture Forum Video Here’s the video version of our conversation: https://youtu.be/X_hZG7cFOCE Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 29. Every modern enterprise wrestles with its data, trying to get the most out of it. The smartest businesses have figured out that it isn't just "the new oil" - data is the very bedrock of their enterprise architecture. For the past 25 years, Dave McComb has helped companies understand the...
--------
34:01
Ole Olesen-Bagneux: Understanding Enterprise Metadata with the Meta Grid – Episode 28
Ole Olesen-Bagneux In every enterprise, says Ole Olesen-Bagneux, the information you need to understand your organization's metadata is already there. It just needs to be discovered and documented. Ole's Meta Grid can be as simple as a shared, curated collection of documents, diagrams, and data but might also be expressed as a knowledge graph. Ole appreciates "North Star" architectures like microservices and the Data Mesh but presents the Meta Grid as a simpler way to manage enterprise metadata. We talked about: his work as Chief Evangelist at Actian his forthcoming book, "Fundamentals of Metadata Management" how he defines his Meta Grid: an integration architecture that connects metadata across metadata repositories his definition of metadata and its key characteristic, that it's always in two places at once how the Meta Grid compares with microservices architectures and organizing concepts like Data Mesh the nature of the Meta Grid as a small, simple, and slow architecture which is not technically difficult to achieve his assertion that you can't build a Meta Grid because it already exists in every organization the elements of the Meta Grid: documents, diagrams or pictures, and examples of data how knowledge graphs fit into the Meta Grid his appreciation for "North Star" architectures like Data Mesh but also how he sees the Meta Grid as a more pragmatic approach to enterprise metadata management the evolution of his new book from a knowledge graph book to his elaboration on the "slow" nature of the Meta Grid, in particular how its metadata focus contrasts with faster real-time systems like ERPs the shape of the team topology that makes Meta Grid work Ole's bio Ole Olesen-Bagneux is a globally recognized thought leader in metadata management and enterprise data architecture. As VP, Chief Evangelist at Actian, he drives industry awareness and adoption of modern approaches to data intelligence, drawing on his extensive expertise in data management, metadata, data catalogs, and decentralized architectures. An accomplished author, Ole has written The Enterprise Data Catalog (O’Reilly, 2023). He is currently working on Fundamentals of Metadata Management (O’Reilly, 2025), introducing a novel metadata architecture known as the Meta Grid. With a PhD in Library and Information Science from the University of Copenhagen, his unique perspective bridges traditional information science with modern data management. Before joining Actian, Ole served as Chief Evangelist at Zeenea, where he played a key role in shaping and communicating the company’s technology vision. His industry experience includes leadership roles in enterprise architecture and data strategy at major pharmaceutical companies like Novo Nordisk.Ole is passionate about scalable metadata architectures, knowledge graphs, and enabling organizations to make data truly discoverable and usable. Connect with Ole online LinkedIn Substack Medium Resources mentioned in this interview Fundamentals of Metadata Management, Ole's forthcoming book Data Management at Scale by Piethein Strengholt Fundamentals of Data Engineering by Joe Reis and Matt Housley Meta Grid as a Team Topology, Substack article Stewart Brand's Pace Layers Video Here’s the video version of our conversation: https://youtu.be/t01IZoegKRI Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 28. Every modern enterprise wrestles with the scale, the complexity, and the urgency of understanding their data and metadata. So, by necessity, comprehensive architectural approaches like microservices and the data mesh are complex, big, and fast. Ole Olesen-Bagneux proposes a simple, small, and slow way for enterprises to cultivate a shared understanding of their enterprise knowledge, a decentralized approach to metadata strategy that he calls the Meta Grid. Interview transcript Larry: Hi,
--------
34:25
Andrea Volpini: The Role of Memory in Digital Branding for AI – Episode 27
Andrea Volpini Your organization's brand is what people say about you after you've left the room. It's the memories you create that determine how people think about you later. Andrea Volpini says that the same dynamic applies in marketing to AI systems. Modern brand managers, he argues, need to understand how both human and machine memory work and then use that knowledge to create digital memories that align with how AI systems understand the world. We talked about: his work as CEO at WordLift, a company that builds knowledge graphs to help companies automate SEO and other marketing activities a recent experiment he did during a talk at an AI conference that illustrates the ability of applications like Grok and ChatGPT to build and share information in real time the role of memory in marketing to current AI architectures his discovery of how the agentic approach he was taking to automating marketing tasks was actually creating valuable context for AI systems the mechanisms of memory in AI systems and an analogy to human short- and long-term memory the similarities he sees in how the human neocortex forms memories and how the knowledge about memory is represented in AI systems his practice of representing entities as both triples and vectors in his knowledge graph how he leverages his understanding of the differences in AI models in his work the different types of memory frameworks to account for in both the consumption and creation of AI systems: semantic, episodic, and procedural his new way of thinking about marketing: as a memory-creation process the shift in focus that he thinks marketers need to make, "creating good memories for AI in order to protect their brand values" Andrea's bio Andrea Volpini is the CEO of WordLift and co-founder of Insideout10. With 25 years of experience in semantic web technologies, SEO, and artificial intelligence, he specializes in marketing strategies. He is a regular speaker at international conferences, including SXSW, TNW Conference, BrightonSEO, The Knowledge Graph Conference, G50, Connected Data and AI Festival. Andrea has contributed to industry publications, including the Web Almanac by HTTP Archive. In 2013, he co-founded RedLink GmbH, a commercial spin-off focused on semantic content enrichment, natural language processing, and information extraction. Connect with Andrea online LinkedIn X Bluesky WordLift Video Here’s the video version of our conversation: https://youtu.be/do-Y7w47CZc Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 27. Some experts describe the marketing concept of branding as, What people say about you after you’ve left the room. It's the memories they form of your company that define your brand. Andrea Volpini sees this same dynamic unfolding as companies turn their attention to AI. To build a memorable brand online, modern marketers need to understand how both human and machine memory work and then focus on creating memories that align with how AI systems understand the world. Interview transcript Larry: Hi, everyone. Welcome to episode number 27 of the Knowledge Graph Insights podcast. I am really delighted today to welcome to the show Andrea Volpini. Andrea is the CEO and the founder at WordLift, a company based in Rome. Tell the folks a little bit more about WordLift and what you're up to these days, Andrea. Andrea: Yep. So we build knowledge graphs and to help brands automate their SEO and marketing efforts using large language model and AI in general. Larry: Nice. Yeah, and you're pretty good at this. You've been doing this a while and you had a recent success story, I think that shows, that really highlights some of your current interests in your current work. Tell me about your talk in Milan and the little demonstration you did with that. Andrea: Yeah, yeah, so it was last week at AI Festival,
--------
32:08
Jacobus Geluk: Use-Case Trees for the Data-Product Marketplace – Episode 26
Jacobus Geluk The arrival of AI agents creates urgency around the need to guide and govern them. Drawing on his 15-year history in building reliable AI solutions for banks and other enterprises, Jacobus Geluk sees a standards-based data-product marketplace as the key to creating the thriving data economy that will enable AI agents to succeed at scale. Jacobus launched the effort to create the DPROD data-product description specification, creating the supply side of the data market. He's now forming a working group to document the demand side, a "use-case tree" specification to articulate the business needs that data products address. We talked about: his work as CEO at Agnos.ai, an enterprise knowledge graph and AI consultancy the working group he founded in 2023 which resulted in the DPROD specification to describe data products an overview of the data-product marketplace and the data economy the need to account for the demand side of the data marketplace the intent of his current work on to address the disconnect between tech activities and business use cases how the capabilities of LLMs and knowledge graphs complement each other the origins of his "use-case tree" model in a huge banking enterprise knowledge graph he built ten years ago how use case trees improve LLM-driven multi-agent architectures some examples of the persona-driven, tech-agnostic solutions in agent architectures that use-case trees support the importance of constraining LLM action with a control layer that governs agent activities, accounting for security, data sourcing, and issues like data lineage and provenance the new Use Case Tree Work Group he is forming the paradox in the semantic technology industry now of a lack of standards in a field with its roots in W3C standards Jacobus' bio Jacobus Geluk is a Dutch Semantic Technology Architect and CEO of agnos.ai, a UK-based consulting firm with a global team of experts specializing in GraphAI — the combination of Enterprise Knowledge Graphs (EKG) with Generative AI (GenAI). Jacobus has over 20 years of experience in data management and semantic technologies, previously serving as a Senior Data Architect at Bloomberg and Fellow Architect at BNY Mellon, where he led the first large-scale production EKG in the financial industry. As a founding member and current co-chair of the Enterprise Knowledge Graph Forum (EKGF), Jacobus initiated the Data Product Workgroup, which developed the Data Product Ontology (DPROD) — a proposed OMG standard for consistent data product management across platforms. Jacobus can claim to have coined the term "Enterprise Knowledge Graph (EKG)" more than 10 years ago, and his work has been instrumental in advancing semantic technologies in financial services and other information-intensive industries. Connect with Jacobus online LinkedIn Agnos.ai Resources mentioned in this podcast DPROD specification Enterprise Knowledge Graph Forum Object Management Group Use Case Tree Method for Business Capabilities DCAT Data Catalog Vocabulary Video Here’s the video version of our conversation: https://youtu.be/J0JXkvizxGo Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 26. In an AI landscape that will soon include huge groups of independent software agents acting on behalf of humans, we'll need solid mechanisms to guide the actions of those agents. Jacobus Geluk looks at this situation from the perspective of the data economy, specifically the data-products marketplace. He helped develop the DPROD specification that describes data products and is now focused on developing use-case trees that describe the business needs that they address. Interview transcript Larry: Okay. Hi everyone. Welcome to episode number 26 of the Knowledge Graph Insights podcast. I am really happy today to welcome to the show, Jacobus Geluk. Sorry, I try to speak Dutch, do my best.
--------
33:48
Rebecca Schneider: Knowledge Graphs and Enterprise Content Strategy – Episode 25
Rebecca Schneider Skills that Rebecca Schneider learned in library science school - taxonomy, ontology, and semantic modeling - have only become more valuable with the arrival of AI technologies like LLMs and the growing interest in knowledge graphs. Two things have stayed constant across her library and enterprise content strategy work: organizational rigor and the need to always focus on people and their needs. We talked about: her work as Co-Founder and Executive Director at AvenueCX, an enterprise content strategy consultancy her background as a "recovering librarian" and her focus on taxonomies, metadata, and structured content the importance of structured content in LLMs and other AI applications how she balances the capabilities of AI architectures and the needs of the humans that contribute to them the need to disambiguate the terms that describe the span of the semantic spectrum the crucial role of organization in her work and how you don't to have formally studied library science to do it the role of a service mentality in knowledge graph work how she measures the efficiency and other benefits of well-organized information how domain modeling and content modeling work together in her work her tech-agnostic approach to consulting the role of metadata strategy into her work how new AI tools permit easier content tagging and better governance the importance of "knowing your collection," not becoming a true subject matter expert but at least getting familiar with the content you are working with the need to clean up your content and data to build successful AI applications Rebecca's bio Rebecca is co-founder of AvenueCX, an enterprise content strategy consultancy. Her areas of expertise include content strategy, taxonomy development, and structured content. She has guided content strategy in a variety of industries: automotive, semiconductors, telecommunications, retail, and financial services. Connect with Rebecca online LinkedIn email: rschneider at avenuecx dot com Video Here’s the video version of our conversation: https://youtu.be/ex8Z7aXmR0o Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 25. If you've ever visited the reference desk at your local library, you've seen the service mentality that librarians bring to their work. Rebecca Schneider brings that same sensibility to her content and knowledge graph consulting. Like all digital practitioners, her projects now include a lot more AI, but her work remains grounded in the fundamentals she learned studying library science: organizational rigor and a focus on people and their needs. Interview transcript Larry: Hi, everyone. Welcome to episode number 25 of the Knowledge Graph Insights podcast. I am really excited today to welcome to the show Rebecca Schneider. Rebecca is the co-founder and the executive director at AvenueCX, a consultancy in the Boston area. Welcome, Rebecca. Tell the folks a little bit more about what you're up to these days. Rebecca: Hi, Larry. Thanks for having me on your show. Hello, everyone. My name is Rebecca Schneider. I am a recovering librarian. I was a trained librarian, worked in a library with actual books, but for most of my career, I have been focusing on enterprise content strategy. Furthermore, I typically focus on taxonomies, metadata, structured content, and all of that wonderful world that we live in. Larry: Yeah, and we both come out of that content background and have sort of converged on the knowledge graph background together kind of over the same time period. And it's really interesting, like those skills that you mentioned, the library science skills of taxonomy, metadata, structured, and then the application of that in structured content in the content world, how, as you've got in more and more into knowledge graph stuff, how has that background, I guess...
--------
32:09