Knowledge Graph Insights

Chris Mungall Capturing knowledge in the life sciences is a huge undertaking. The scope of the field extends from the atomic level up to planetary-scale ecosystems, and a wide variety of disciplines collaborate on the research. Chris Mungall and his colleagues at the Berkeley Lab tackle this knowledge-management challenge with well-honed collaborative methods and AI-augmented computational tooling that streamlines the organization of these precious scientific discoveries. We talked about: his biosciences and genetics work at the Berkeley Lab how the complexity and the volume of biological data he works with led to his use of knowledge graphs his early background in AI his contributions to the gene ontology the unique role of bio-curators, non-semantic-tech biologists, in the biological ontology community the diverse range of collaborators involved in building knowledge graphs in the life sciences the variety of collaborative working styles that groups of bio-creators and ontologists have created some key lessons learned in his long history of working on large-scale, collaborative ontologies, key among them, meeting people where they are some of the facilitation methods used in his work, tools like GitHub, for example his group's decision early on to commit to version tracking, making change-tracking an entity in their technical infrastructure how he surfaces and manages the tacit assumptions that diverse collaborators bring to ontology projects how he's using AI and agentic technology in his ontology practice how their decision to adopt versioning early on has enabled them to more easily develop benchmarks and evaluations some of the successes he's had using AI in his knowledge graph work, for example, code refactoring, provenance tracking, and repairing broken links Chris's bio Chris Mungall is Department Head of Biosystems Data Science at Lawrence Berkeley National Laboratory. His research interests center around the capture, computational integration, and dissemination of biological research data, and the development of methods for using this data to elucidate biological mechanisms underpinning the health of humans and of the planet. He is particularly interested in developing and applying knowledge-based AI methods, particularly Knowledge Graphs (KGs) as an approach for integrating and reasoning over multiple types of data. Dr. Mungall and his team have led the creation of key biological ontologies for the integration of resources covering gene function, anatomy, phenotypes and the environment. He is a principal investigator on major projects such as the Gene Ontology (GO) Consortium, the Monarch Initiative, the NCATS Biomedical Data Translator, and the National Microbiome Data Collaborative project. Connect with Chris online LinkedIn Berkeley Lab Video Here’s the video version of our conversation: https://youtu.be/HMXKFQgjo5E Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 37. The span of the life sciences extends from the atomic level up to planetary ecosystems. Combine this scale and complexity with the variety of collaborators who manage information about the field, and you end up with a huge knowledge-management challenge. Chris Mungall and his colleagues have developed collaborative methods and computational tooling that enable the construction of ontologies and knowledge graphs that capture this crucial scientific knowledge. Interview transcript Larry: Hi everyone. Welcome to episode number 37 of the Knowledge Graph Insights podcast. I am really delighted today to welcome to the show Chris Mungall. Chris is a computational scientist working in the biosciences at the Lawrence Berkeley National Laboratory. Many people just call it the Berkeley Lab. He's the principal investigator in a group there, has his own lab working on a bunch of interesting stuff, which we're going to talk about today.

Emeka Okoye, a seasoned Knowledge Engineer and Semantic Architect with over 20 years in knowledge engineering, dives into the world of the Semantic Web. He shares insights on the transformative Model Context Protocol (MCP) and its impact on AI applications. Emeka discusses his RDF Explorer, a tool that allows developers easy access to semantic data without specialized language skills. The conversation also touches on the evolution of ontology engineering, his history in tech innovation in Nigeria, and the importance of making semantic technologies accessible globally.

In this discussion, Tom Plasterer, Managing Director at XponentL Data and a leading expert in data strategy, delves into the origins and significance of FAIR data principles. He unpacks how the concept evolved from the semantic web to address the need for discoverable data in research and industry. Tom reveals the 15 facets of the FAIR acronym and emphasizes the critical role of knowledge graphs in implementing these standards. His journey from bioinformatics to data management showcases the importance of collaboration and shared terminology in enhancing data practices, especially in pharmaceuticals and life sciences.

Mara Inglezakis Owens, an enterprise architect at Delta Air Lines, blends her humanities background with digital anthropology to shape user-focused architecture. She discusses how mentoring shaped her approach and emphasizes the need for understanding actual stakeholder behaviors over self-reports. Mara also shares insights on justifying financial investments in her work, the significance of documentation in knowledge engineering, and lessons learned about embracing imperfection in digital systems design. Her human-centered focus exemplifies the evolution of enterprise architecture in modern businesses.

Frank van Harmelen, a leading AI professor at Vrije Universiteit in Amsterdam, discusses the integration of human and machine intelligence. He emphasizes the importance of hybrid collaboration, advocating for AI systems that enhance rather than replace human capabilities. Topics include the emergence of neuro-symbolic systems, the evolution of conversational interfaces, and the challenges of managing interdisciplinary research teams. He also highlights innovative applications of AI in healthcare and the need for a shared worldview to foster effective collaboration.

Join Denny Vrandečić, Head of Special Projects at the Wikimedia Foundation and founder of Wikidata, as he discusses the groundbreaking Abstract Wikipedia initiative. He shares insights on how it aims to democratize knowledge sharing by allowing contributions in any language. Denny reflects on his journey from the creation of Wikidata to exploring how Abstract Wikipedia can enhance multilingual knowledge accessibility. He also dives into the potential of community collaboration and the use of language models to create structured knowledge representations.

Charles Ivie, a Senior Graph Architect at Amazon Web Services with over 15 years in the knowledge graph community, debunks the myth that the semantic web has failed. He argues it's a 'catastrophically successful failure' with over half of the web utilizing RDF annotations. The discussion explores how RDF serves as a Rosetta Stone for knowledge representation, enabling better communication and innovative solutions. Ivie emphasizes the importance of domain-specific ontologies and the growing adoption of knowledge graphs in enterprises, showcasing their transformative potential.

Andrea Gioia In recent years, data products have emerged as a solution to the enterprise problem of siloed data and knowledge. Andrea Gioia helps his clients build composable, reusable data products so they can capitalize on the value in their data assets. Built around collaboratively developed ontologies, these data products evolve into something that might also be called a knowledge product. We talked about: his work as CTO at Quantyca, a data and metadata management consultancy his description of data products and their lifecycle how the lack of reusability in most data products inspired his current approach to modular, composable data products - and brought him into the world of ontology how focusing on specific data assets facilitates the creation of reusable data products his take on the role of data as a valuable enterprise asset how he accounts for technical metadata and conceptual metadata in his modeling work his preference for a federated model in the development of enterprise ontologies the evolution of his data architecture thinking from a central-governance model to a federated model the importance of including the right variety business stakeholders in the design of the ontology for a knowledge product his observation that semantic model is mostly about people, and working with them to come to agreements about how they each see their domain Andrea's bio Andrea Gioia is a Partner and CTO at Quantyca, a consulting company specializing in data management. He is also a co-founder of blindata.io, a SaaS platform focused on data governance and compliance. With over two decades of experience in the field, Andrea has led cross-functional teams in the successful execution of complex data projects across diverse market sectors, ranging from banking and utilities to retail and industry. In his current role as CTO at Quantyca, Andrea primarily focuses on advisory, helping clients define and execute their data strategy with a strong emphasis on organizational and change management issues. Actively involved in the data community, Andrea is a regular speaker, writer, and author of 'Managing Data as a Product'. Currently, he is the main organizer of the Data Engineering Italian Meetup and leads the Open Data Mesh Initiative. Within this initiative, Andrea has published the data product descriptor open specification and is guiding the development of the open-source ODM Platform to support the automation of the data product lifecycle. Andrea is an active member of DAMA and, since 2023, has been part of the scientific committee of the DAMA Italian Chapter. Connect with Andrea online LinkedIn (#TheDataJoy) Github Video Here’s the video version of our conversation: https://www.youtube.com/watch?v=g34K_kJGZMc Podcast intro transcript This is the Knowledge Graph Insights podcast, episode number 30. In the world of enterprise architectures, data products are emerging as a solution to the problem of siloed data and knowledge. As a data and metadata management consultant, Andrea Gioia helps his clients realize the value in their data assets by assembling them into composable, reusable data products. Built around collaboratively developed ontologies, these data products evolve into something that might also be called a knowledge product. Interview transcript Larry: Hi, everyone. Welcome to episode number 30 of the Knowledge Graph Insights podcast. I'm really happy today to welcome to the show Andrea Gioia. Andrea's, he does a lot of stuff. He's a busy guy. He's a partner and the chief technical officer at Quantyca, a consulting firm that works on data and metadata management. He's the founder of Blindata, a SaaS product that goes with his consultancy. I let him talk a little bit more about that. He's the author of the book Managing Data as a Product, and he's also, he comes out of the data heritage but he's now one of these knowledge people like us.

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...

Ole Olesen-Bagneux, a globally recognized authority in metadata management and Chief Evangelist at Actian, discusses the concept of the Meta Grid—a framework that simplifies enterprise metadata management. He explains that metadata exists everywhere in an organization and outlines how the Meta Grid can connect this scattered data. Ole compares the Meta Grid to complex architectures like microservices and Data Mesh, emphasizing its practicality. He also shares insights about his forthcoming book, advocating for a collaborative approach to effective data management.