Have Meaning, Will Travel: Why Apache Ossie Needs You

Here’s a heretical question worth considering: what if standards are actually beside the point for semantic layers? Apache Ossie was recently announced as the open standard successor to the Open Semantic Interchange (OSI) initiative. Its mission is to create a standard format for defining semantic metadata that enables systems to exchange intent and meaning along with its underlying data. 

The pitch for interoperability always sounds virtuous: open formats, no vendor lock-in, everyone finally speaking the same language. But standards bodies move at the pace of consensus. In a space where AI and data practices are evolving daily, isn’t betting on a standard a bet against speed and innovation? I don’t believe so, but I want you to sit with the question for a minute before I get to why, because most of the industry hasn’t actually resolved it.

What Semantic Layers Already Got Right

Standardized or not, semantic layers have earned their place in the modern AI stack. They let enterprises define “comparable-store sales growth %,” “comparable-store transactions,” or “buy-online-return-in-store (BORIS) rate” exactly once, so every AI Skill, automated AI workflow, AI cowork interaction, BI dashboard, and Excel spreadsheet gets the same governed answer, instead of five different ones. That’s the difference between an AI app that answers a business question correctly and one that hallucinates a plausible-looking number. And it gives data governance teams a real lever: one place to define, audit, and change the meaning of a metric, instead of chasing it through a dozen systems. It’s also why handing an agent a skill file or a README isn’t the same as giving it a governed semantic layer.

Beyond Lock-In, The Bigger Risk Is Agents Making Confident, Wrong Decisions

If meaning can’t travel between systems, you end up with vendor lock-in: metric definitions get stuck in whatever platform you modeled them in, and switching turns into a multi-year migration project. While that’s a costly headache, trust in autonomous agents should worry you more than lock-in.

Picture an AI agent authorized to adjust inventory reorder thresholds, or one negotiating a price against another company’s procurement agent. If “margin” means one thing in your system and something subtly different in theirs, you get a confident, wrong decision, executed at machine speed. Multiply that across a fleet of agents talking to other fleets of agents, each carrying its own private dialect of “cost” and “risk.” You end up with the Babel problem: everyone’s technically fluent, and nobody actually understands the other guy.

Protocols like Agent2Agent (A2A) are being built so agents can talk to each other, but a shared wire format is useless if the meaning riding on top of it doesn’t travel too. Gartner has already put a number on what happens when it doesn’t, predicting that by 2030, half of AI agent deployment failures will trace back to insufficient governance over multisystem interoperability. 

Apache Ossie is our opportunity to solve that trust challenge.

Why OSI Became Apache Ossie

This is why the Open Semantic Interchange formed a little over a year ago: a coalition of vendors and practitioners betting that semantic metadata deserves the same open, portable treatment we’ve already given data formats and query engines. Recently, that bet went further. In the belief that true vendor neutrality can’t be owned by any single company, including the ones who founded it, OSI submitted its work to the Apache Software Foundation under the name Apache Ossie.

In practice, Apache Ossie is working toward a truly open semantic protocol. If, for example, Snowflake’s Semantic Views comply with Ossie, it means customers can use AtScale to repurpose those same definitions on top of Databricks. Then use Codex, if it understands the Ossie spec, to talk to that same set of semantic definitions without needing to reprogram them. 

The name has changed but the goal hasn’t: standardize how we exchange semantic metadata (metrics, dimensions, relationships, and the logic behind them) so any tool or agent can consume it without losing meaning. What changes is who’s accountable for keeping that promise. Under Apache governance, no single vendor gets to steer the standard for its own benefit. 

Consensus Needs Collaboration 

Interoperability isn’t a spec you write once and walk away from. It’s a community you keep building. Ossie begins incubation with five inherited working groups already active: Advanced Metrics & Expression Language, Composability, Catalog Integration, Ontology Representation, and Model Converters & Developer Tools. That’s a solid starting point.

The roadmap ahead includes a more expressive metrics language, converters for the tools enterprise teams actually use, deeper catalog integration, industry-specific semantic models for healthcare, financial services, and retail. Whoever shows up to do the work sets the agenda. Getting that right takes practitioners who’ve hit the edge cases and vendors who’ve built workarounds for them. 

Why AtScale Is All In on Ossie

We’ve spent 13 years in the guts of semantic engine complexity: multidimensional modeling, advanced calculations, model composability, the grinding, thankless work of keeping hierarchies and aggregation logic intact as enterprises move off legacy platforms. That expertise is exactly what today’s AI-driven use cases will demand tomorrow, and it shouldn’t stay locked inside any one vendor’s product.

The industry needs an open ecosystem where meaning travels across databases, data warehouses, and tools that contain essential context about your business. Not just within a company, but between partners, customers, supply chains, and global communities. Semantics have to be open enough so that humans and compound AI systems can use them. Portability and consistency is good for customers. It’s good for the industry too, including companies like ours that would rather compete on execution than on trapping customers’ metadata.

How to Embrace Ossie 

Picture your business a few years from now, where every system, partner, and agent you work with shares real, portable meaning instead of reinventing it. What does that open up for your services, your integrations, your customers? What would it mean for your industry if “customer lifetime value,” “claims risk,” or “yield” meant exactly the same thing everywhere it was used?

You have a real say in this. Join a working group. File an issue. Propose a converter. Or just show up to a discussion. Sign up to be an Apache Ossie contributor.

Meaning doesn’t travel on its own. Somebody has to build the road. And if you’d like to build it full time, funded by a company that’s genuinely betting its future on open semantic standards, contact me. I’d love to talk.

Reviewed by: Mark Palmer