2023 Trends in Data Modeling – Spotlight on Human-Centric Taxonomies

Data modeling remains foundational to every facet of the data ecosystem—from governance to analytics. The InsideAI News editorial underscores that developments in data modeling mirror broader shifts across data-driven practices. As modeling workflows become increasingly automated and embedded across tools like data catalogs, BI platforms, and virtualization layers, it’s clear that the focus is shifting toward ease of use and semantic richness.

Build Taxonomies Like a Game of Points

Jans Aasman offers a memorable metaphor for taxonomy construction:

“You must look at a taxonomy like a game where you get a point for every concept you get out of the documents … The question is who can get the most points. Meaning, how can I make as many alternative synonyms for the most important concepts that I need?”

This perspective invites us to think of knowledge modeling not merely as a technical task, but as a creative endeavor—one where exhaustiveness and linguistic nuance boost the value of a model. The more synonyms, context, and alternative phrasing captured, the more robust and flexible that taxonomy becomes.

As enterprises automate their data workflows and shift toward semantic, domain-aware modeling, embracing Franz’s taxonomy approach encourages inclusivity, clarity, and usability. Data models aren’t static documentation—they’re living, language-rich structures waiting to be explored.