Part 2 of the Busy Engineer’s Guide to Data Governance

If you’ve ever tried to make sense of industrial data standards, you know the feeling: alphabet soup, overlapping frameworks, and a lot of well-meaning PowerPoints that don’t tell you where to start. 

But in brownfield facilities—where systems weren’t designed to play nice—standards can be your best tool for untangling the mess and enforcing good Data Governance. The key is knowing which ones actually matter for your site, your systems, and your goals. 

So… What Are These Standards For? 

Standards help ensure your systems speak the same language. They define how data is structured, classified, and shared—so that when you modernize or integrate new systems, everything fits together. 

Without them, you’re stuck with: 

• Inconsistent tags, data and asset hierarchies 

• Manual rework every time systems change 

• Risky handoffs between departments or vendors 

• Manual re-work to align data sets for every single use case for digital transformation 

The Heavy Hitters (and What They Do) 

Here’s a quick breakdown of the most common industrial data standards, minus the jargon: 

Standard	Why It Matters
ISO 81346	Organizes and classifies assets using a consistent naming system. Ideal for cleaning up your tag chaos.
ISO 18101	Oil and Gas Interoperability Technical Specification.  Life-cycle management of the key technical and engineering-oriented information across the asset intensive industries.
ISA-95 (IEC 62264)	Defines how data flows between enterprise systems (like ERP) and control systems (like SCADA/MES).  Provides a basis for establishing asset hierarchies and data pedigree.
MIMOSA CCOM	Helps standardize asset condition and health monitoring—important for predictive maintenance.  Provides the basis for alias principle name translation.
OPC UA	Enables secure, structured communication between systems, regardless of vendor.
MQTT	Lightweight messaging protocol great for modern, scalable data movement (especially in edge/cloud setups).
MTP	Namur standard for Module Type Package.  Establishes modular, service-oriented automation and plug-and-play integration.

You Don’t Need All of Them 

Not every site needs every standard. Here’s a rough guide based on your industry: 

• Life Sciences: Start with ISA-95, GS1, MTP and ISO 81346 for alignment and traceability. 

• Water/Wastewater: Focus on ISO 81346 and OPC UA for consistent asset models and connectivity. 

• Food & Beverage: ISA-95, GS1, and MQTT help with traceability and integration. 

• Oil & Gas: MIMOSA, ISO-18101, ISO 15926, and ISO-81346 support asset lifecycle and digital twins. 

Don’t let the perfect be the enemy of the useful. Even adopting one standard consistently can drastically improve your data quality and system interoperability. 

How Standards Support Bigger Goals 

These aren’t just paperwork exercises. When you apply standards, you: 

• Make your data easier to trust 

• Enable faster integration during upgrades 

• Lay the foundation for digital twins, analytics, and AI 

• Reduce risk during audits and handovers 

The integration of smart devices into existing environments, rather than new (greenfield) installations, is a significant trend in the industrial sector. Estimates suggest that a substantial majority of smart device deployments will occur in these existing environments. According to various industry reports and market analyses, it’s projected that around 70-80% of all industrial IoT (IIoT) devices will be installed in brownfield environments, meaning existing facilities. 

In Brownfield applications, standards are equality critical to establish good Data Governance.  You may have heard of the Unified Name Space.  The concept of a unified namespace sounds great…. First, agree on a namespace (based on standards) and then implement that for all systems ideally using a publish-subscribe model (PUB-SUB) where context is provided consistently from the lowest elements of the stack (ideally smart sensors, etc.) … BUT, in the real world of brownfield with established systems and enterprises; it is impractical.  A better approach is to consider the federated integration of namespaces as a more practical and achievable goal.  Standards such as ISA 95 Part 7 Alias Service Model and MIMOSA CCOM provide for establishing an interoperable, enterprise-scalable federated namespace. 

Coming Up Next 

In Part 3, we’ll show how poor governance can derail your digital twin—or any analytics project—and what clean, structured data makes possible.