Sunday Discussions and Workshops
discussions
Sunday Morning Conversation: Letter from a Fish - Text, Data, and the Boundaries Between Worlds
The fundamental binary logic of computing—ones and zeros—sets hard boundaries for what technology can achieve in the field of semantics. Boolean logic, derived from mathematician George Boole's work combining Aristotelian reasoning with equational expressions, ultimately defined the logical ports in computer hardware. All bits travel through this logic, making it the physical limit of how data can be processed. The very infrastructure through which we process semantics technologically is hardwired to formal reasoning.
In his 2025 Data Day Texas talk, computer scientist and author Bill Inmon applied his thinking on data to the world of text. As a figure of speech, Bill called himself "a human who lived on land—the world of data." The world of text, however, was water, and he could not express his thinking as if he were a fish; he had to express himself as a human of data. That's how the textual warehouse came into being—a functional evolution of the data warehouse enabled through semantic disambiguation.
But what happens when we reverse the lens? When the world of text approaches the world of data? When fish make their way onto land? What will they see? What will they say?
This Sunday morning conversation is a letter from a fish—Ole Olesen-Bagneux responding to Bill Inmon's metaphor. Drawing on the pioneering work of library and information science giants Suzanne Briet, Henriette Avram, and Elaine Svenonius, Ole tells the story of how we've pushed text forward as "an enormous splash of semantic ambiguity" beyond Boolean logic. The discussion explores where formal reasoning meets human meaning, and what these boundaries mean for the limits of AI.
Join two distinct perspectives—one rooted in data architecture, one in metadata and information science—as they navigate the edges where precision meets ambiguity.
“AI-Ready Data”: Switch, Spectrum, or Just Buzzword?)
Everyone claims to have AI-ready data — but what does that even mean? Is it about perfect pipelines, labeled datasets, or governance frameworks? Or is “AI-ready” just the new “data-driven” — a shiny phrase that hides more than it reveals?
In this unconference session led by Jean-Georges “jgp” Perrin, chair of the Bitol project at the Linux Foundation, we’ll put the concept of AI readiness under the microscope. Through an open, collaborative debate, we’ll explore questions like:
• Is AI readiness a switch you flip or a maturity model you evolve through?
• Who defines readiness — data engineers, data scientists, compliance teams, or the AI itself?
• What role do semantic layers, ontologies, and knowledge graphs really play in achieving AI readiness? Are they enablers of understanding or just another abstraction layer with good PR?
• Can open standards like ODCS (Open Data Contract Standard) and ODPS (Open Data Product Standard) help transform “AI-ready” from a marketing slogan into something measurable, testable, and trustworthy?
We’ll take inspiration from the community-driven success of Defining Data Products: A Community Effort — a reminder that shared understanding doesn’t come from ivory towers, but from practitioners challenging each other’s assumptions.
Expect sharp insights, respectful arguments, and perhaps a few existential moments about what “readiness” actually means in the age of AI. No slides. No scripts. Just truth-seeking.
How to Elevate your Data and Analytics Teams
This will be an open group discussion for Data Leaders - people who currently lead and manage Data and Analytics teams - where we will talk about what's working right now, what's not working, what I see in the industry, and I will share actionable tips and advice from my playbook for elevating your data teams and connecting them with the business.'
workshops
Build Your Solopreneur Roadmap: A Workshop for Data Professionals (2 hour workshop)
In this workshop we'll discuss the real stuff people need to figure out when thinking about going solo. I will walk participants through an actual calculation of what they presently make an hour, exploring how this compares to typical hourly rates for contractors from large contracting companies. This exercise will demonstrate that individuals working in a solopreneur capacity are much more competitive than they realize in this market. This will then be the basis for an exercise on setting rates, where a lot of people get stuck. From there we will discuss the nuts and bolts of setting up a business such as legal structures, taxes, and contracts. This will include practical, from-the-trenches advice for getting started. Finally, we will discuss strategies for landing your first client, following the philosophy that it is easier to land your first client than your next job.
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These organizations support the data community by making Data Day Texas accessible to practitioners at all career stages.
