Interviews with experts on semantic technology, ontology design and engineering, linked data, and the semantic web.
Knowledge Graph Insights
Claim This Podcastby Larry Swanson
4.6(27 reviews)
51 episodes
Updated Daily
Accepts GuestsHas SponsorsLocation 🇺🇸
63
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality83
Social0
YouTube74
Engagement32
Podcast Overview
Interviews with experts on semantic technology, ontology design and engineering, linked data, and the semantic web.
Language
🇺🇲
Publishing Since
7/15/2024
Unlock The Full Podcast Authority Score Report
See how your podcast performs across key metrics
63
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality83
Social0
YouTube74
Engagement32
8
Excellent Areas
4
Good Performance
7
Growth Opportunities
excellent
Episode Length
34 minutes
Performing excellently!
good
Publishing Consistency
Every 11 days
Recommendations available
Unlock the full report to see detailed tips
poor
Episode Thumbnails
Recommendations available
Unlock the full report to see detailed tips
+16 More Metrics
Unlock comprehensive insights including:
- • YouTube presence analysis
- • Social media reach metrics
- • RSS compliance scoring
- • Podcast 2.0 features
- • Technical standards
What's Included in Your Full Report
Detailed Analytics
- Complete breakdown of all 19 authority metrics
- Personalized recommendations for each metric
- Industry benchmarks and comparisons
- Technical RSS feed analysis and compliance scoring
Growth Strategies
- Step-by-step action plans for improvement
- Quick wins to boost your score immediately
- Pro tips from successful podcasters
Get your free podcast insights report
See how your show performs across every key metric
Instant delivery
No spam
Attract Better Guests
High authority scores make your podcast more attractive to industry leaders and influencers who want to appear on credible shows.
Secure Sponsorships
Sponsors look for podcasts with proven authority and engagement. Your score demonstrates your podcast's value to potential partners.
Grow Your Audience
Understanding your strengths and weaknesses helps you make data-driven decisions to expand your listener base effectively.
1 verified contact email on file for Knowledge Graph Insights
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
June 9, 2026
Lulit Tesfaye: Semantic Architectures for the AI Era – Episode 52
Lulit Tesfaye, Partner & VP at Enterprise Knowledge, explains how semantic architectures provide crucial context for AI, enabling organizations to leverage their knowledge assets effectively.
May 25, 2026
Giancarlo Guizzardi: Ontology, Semantics, and Explainable AI – Episode 51
Professor Giancarlo Guizzardi discusses ontology, semantics, and explainable AI, revealing how conceptual modeling underpins AI systems and leads to practical pattern languages.
May 11, 2026
Ora Lassila and Adrian Gschwend: RDF 1.2 Working Group Update – Episode 50
Ora Lassila and Adrian Gschwend Even as RDF has become ubiquitous in enterprises and across the web, its awkward handling of reification — the ability to refer to other statements in a graph — has limited its wider adoption. RDF 1.2 addresses this with the reifier: a new element that lets you attach provenance, confidence, and source directly to a relationship — including claims you're tracking but not asserting as true. We talked about: Ora and Adrian's extensive experience and backgrounds in the RDF community how the need to better handle reification led to the development of RDF 1.2 the W3C's use of the term "recommendation," which many/most people would think of as a "standard" the recent advancement of the RDF Concepts and Abstract Syntax and RDF Semantics specifications to "candidate recommendation" status the new RDF triple term - and how it permits references to RDF statements that have not been asserted some of the details that made reification difficult in prior versions of RDF: verbosity, inability to scale, etc. how the ability to reason on data distinguishes RDF graphs from labeled property graphs the high quality of the RDF 1.2 W3C working group and their confidence that their work has accounted for all of the important considerations that might arise the challenges of dealing with the needs for both backward and forward compatibility how committee specifications like RDF 1.2 compare with less collaborative vendor specifications how RDF saves BMW millions of lines of code when reasoning over car features how standards-setting has evolved over time, from codifying existing practices 30 years ago to more proactive approaches today Adrian's appreciation for the working group volunteer contributors and how they exemplify the values of open standards, open source, and open data Ora's observation about the truly open and transparent nature of the working group and the many benefits open standards, including the ability to avoid vendor lock-in Ora's bio Dr. Ora Lassila has been working on the Semantic Web since 1996, first exploring possibilities for knowledge representation on the Web—work that launched the W3C RDF activity—and later pursuing his ideas about using autonomous agents on the Web—something that became the original Semantic Web vision as articulated in the 2001 Scientific American article he co-authored. All this was preceded by several years of research work on knowledge representation, ontologies, agents, planning, and other classical AI technologies. He is currently an Associate Director of Data Engineering and Governance at Accenture, working on topics like ontologies and knowledge graphs. He is also the co-chair of the current W3C RDF & SPARQL Working Group that is defining the next version of the RDF standard. His prior positions include Principal Technologist (in the Neptune graph database team) at AWS, Managing Director (Head of Ontology Engineering) at State Street, Research Fellow (Head of Agent Research) at Nokia Research, and Project Manager at Carnegie Mellon University, among several others. Dr. Lassila’s knowledge representation software flew onboard the NASA Deep Space 1 probe to the Asteroid Belt in the 1990s. He is also a Grand Prize Winner of the Obfuscated C Code Contest. He received his Ph.D (D.Sc) and M.Sc degrees at the Helsinki University of Technology. Connect with Ora online LinkedIn Adrian's bio Adrian Gschwend is the founder of Qlevia AI, an operational knowledge platform for enterprise AI, designed to help organizations turn complex, evolving data landscapes into reliable, real-time systems. For more than a decade, Adrian has focused on making knowledge graphs scale, both technologically and in real-world applications. As an engineer, he has worked hands-on with enterprises and public institutions to solve complex data integration challenges, building systems that reflect how businesses actually operate and evolve over time. Adrian has a strong background in open source and open data, contributing to large-scale government platforms in Switzerland and Europe, as well as working with organizations such as BMW. He also serves as co-chair of the World Wide Web Consortium RDF 1.2 Working Group. His perspective is that while AI has advanced rapidly, most organizations still operate on fragmented and disconnected data. He is focused on closing that gap by building systems where data, context and decision-making come together into a reliable operational layer that adapts with the business. Connect with Adrian online LinkedIn email: adrian at qlevia dot com Resources mentioned in this interview RDF 1.2 Concepts and Abstract Data Model RDF 1.2 Semantics The Semantic Web, Scientific American, May 2001 Video Here’s the video version of our conversation: https://youtu.be/VlRsTyHDdY8 Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 50. The standards that make the World Wide Web work are built on the volunteer labor of experts like Ora Lassila and Adrian Gschwend. Ora and Adrian co-chair the working group that is bringing a powerful new capability to the W3C RDF standard. In previous versions of RDF, reification has been a verbose and complex process. RDF 1.2 introduces a new rdf:reifies property that simplifies and streamlines the ability to refer to other triples in a graph as first-class objects. Interview transcript Larry: Hi, everyone. Welcome to episode number 50 of the Knowledge Graph Insights Podcast. I am really delighted today to welcome to the show Ora Lassila and Adrian Gschwend. Sorry, Adrian. My German is horrible at this point, but Ora's just started a new job at Accenture. That's really exciting. Maybe we'll talk a little bit more about that. Most people know him as like a longtime Neptune person at AWS. Adrian is the also well-known long time at Zazuko and now is the CEO at Qlevia. Anyhow, welcome to both of you. Maybe Ora, start with you. Tell the folks a little bit more about what you're up to these days. Ora: Yeah, thanks, Larry. Well, you pretty much said the important part, I'm just in the process of having switched jobs, but I am also the co-chair of the RDF and SPARQL Working Group at W3C, and have been that for quite some time now. That's, I guess, the important part here. Of course, I've had long history with RDF and started this whole thing back in the late '90s. Larry: Yeah, that's a little bit of an understatement to say that you've been involved a little while, but we can talk more about that later. Adrian... Adrian: Thank you, Larry. Happy to be here as well. Yeah, so well known probably for Zazuko, for a lot of the open source tools we do in the RDF knowledge graph domain. Some people know me for Qlever and QLeverize as well, where I'm a chief commercial officer right now. Qlevia, is basically my try to not have to talk about graphs anymore, so I want to scale the technology but solve problems, and for the first time venture funded, so that will be the next hopefully fantastic years. Larry: Oh, that's exciting. Looking forward to hearing more about that, and I neglected as I introduced you, the reason you're here is that you're co-chairs of this committee. Adrian: True. Larry: Yeah, so one of you talk a little bit about, and maybe Ora, the history of the project and how the need to upgrade to 1.2 came about. Ora: Right. Well, so we go all the way back to the first version of RDF. In the late 90s, it introduced something that we call reification, which basically lets you talk about RDF statements, so RDF graphs are all about statements, where you say things like, "Adrian's nationality is Swiss." That would be like a statement, but then sometimes you need to talk about the statements themselves. So if, for example, if I wanted to say, "Adrian believes that the moon is made of cheese," I don't necessarily want to say the moon is made of cheese, but I want to talk about the fact that Adrian might think this way. And so, reification was a mechanism to accommodate something like this. Interestingly, if you look at the draft versions of the first RDF specification, the reification kind of started out fairly close to the top of the specification, and in consecutive version, it moves further and further back. I always think that, once it got published, it became sort of the most misunderstood and most hated part of RDF in many ways. Ora: It's a little cumbersome and misunderstood, because I think people took some of the stuff too literally, but over the years, people have suggested various ways of "fixing this," and a little over 10 years ago, there was a paper called Reification Done Right that was written by a couple of my former AWS colleagues. That got people sort of reengaged with the idea of reification really should be fixed somehow, and it turned into a community group at W3C, called RDF Star. Community groups at W3C have this kind of like a lightweight process. They cannot produce specifications. They can only produce final reports, which can then be input to working groups at W3C, which can be chartered to produce actual WTC recommendations. When I say recommendation, for those listeners of yours who don't know, recommendation is the term that W3C uses for something that some other organizations might call a standard. I think that sort of originally the term implies that W3C has no enforcement authority of any kind. People implement the recommendations if they think that they're a good idea and that they promote interoperability. Larry: Interesting. I always wondered, because the authority before, as a candidate recommendation, I always thought that was kind of odd language, but that explains that. Ora: Right, so the end goal here is to produce something or publish something that's called a recommendation,...
51 total episodes available with 25 transcripts
Recent guests on Knowledge Graph Insights
Guests from recent episodes — sign up to see every guest that has ever appeared on this show.
Lulit Tesfaye
Guest
Giancarlo Guizzardi
Guest
Daniel Davis
Guest
Robert Sanderson
Guest
Quentin Reul
Guest
Tom Plasterer
Guest
Mara Inglezakis Owens
Guest
Frank van Harmelen
Guest
Denny Vrandečić
Guest
Charles Ivie
Guest
Andrea Gioia
Guest
Jesús Barrasa
Guest
Similar Podcasts
Discover related shows you might enjoy
Practical AI: Machine Learning, Data Science
Practical AI LLC
GraphGeeks Podcast
Amy Hodler
Y Combinator
Y Combinator
Training Data
Sequoia Capital
a16z Podcast
Andreessen Horowitz
FalkorDB Podcast: Innovating at the Intersection of Graphs, AI, and Databases
FalkorDB
Everyday AI Podcast – An AI and ChatGPT Podcast
Everyday AI
The AI Podcast
NVIDIA
The Real Python Podcast
Real Python
DataFramed
DataCamp
Naval
Naval
Super Data Science: ML & AI Podcast with Jon Krohn
Jon Krohn
Thoughtworks Technology Podcast
Thoughtworks
Prof G Markets
Vox Media Podcast Network
Talk Python To Me
Michael Kennedy
Deep-dive analytics for Knowledge Graph Insights
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is Knowledge Graph Insights?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 7 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.