Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
Tim Berners-Lee has an interesting habit of coming up with ideas that seem hard to explain at the outset, remain all hard to understand even… Read More »How Solid Pods May End Up Becoming the Building Blocks of the Metaverse
In the last few years, a very interesting concept has emerged from the realm of semantics: data shapes. This idea has been touched upon elsewhere… Read More »The Shape of Data
It’s the last week of the year. The gifts have been opened (well, the ones that aren’t currently still sitting in a dock in Los… Read More »Trends Towards 2022
High-rise construction in the Denny Triangle area of Seattle. Source: Bruce Englehardt, Wikimedia Commons, May 2020 I’ve been looking for fresh use cases that tell… Read More »Building a hypergraph-based semantic knowledge sharing environment for construction
Semantic data consultant @EmekaOkoye made a couple of great points on Twitter back in November and early December 2021: “I am amused how some of… Read More »Lying to blockchains and other Web3 dilemmas
Okay, so I am still confused by the concept of a Data Mesh (I’m a slow learner). Recently, I wrote a blog that posed the… Read More »Are Data Meshes Really Data Marts with Conformed Dimensions?
Artificial Intelligence has a long history of oscillating between two somewhat contradictory poles. On one side, exemplified by Noam Chomsky, Marvin Minsky, Seymour Papert, and… Read More »Where Semantics and Machine Learning Converge
Manufacturing Line, Wikimedia Commons, 2014 Fakery certainly isn’t limited to news and social media. The Organisation for Economic Co-operation and Development (OECD) estimated in 2016… Read More »How data decentralization is already benefiting enterprises–and society
Enterprise machine learning deployments are limited by two consequences of outdated data management practices widely used today. The first is the protracted time-to-insight that stems… Read More »Improving Machine Learning: How Knowledge Graphs Bring Deeper Meaning to Data
The other day, I came across a Quora question I just had to answer. This is not unusual for me. It wasn’t that the question… Read More »Data intelligibility and the quest for mutually understood meaning
