What is Data Interoperability in Oil & Gas Asset Management?

Data interoperability is the capability of different software systems — engineering design tools, document management systems, CMMS, ERP, procurement platforms, and analytics solutions — to exchange and correctly interpret information without manual transformation or data loss. In oil and gas, energy, and heavy industry, interoperability is a critical enabler of efficient asset lifecycle management.

Without data interoperability, organisations are forced to re-enter or manually translate data as it moves between systems — a process that introduces errors, creates delays, and generates the data quality problems that drive operational inefficiency and safety risk.

Why data interoperability matters in asset-intensive industries

Typical oil and gas facilities involve dozens of software systems across the engineering and operational lifecycle: CAD and 3D modelling tools, EDMS, procurement systems, CMMS, ERP, inspection management, safety management, and increasingly digital twin platforms. Each of these systems needs access to asset data that originates elsewhere.

When these systems cannot exchange data reliably, the organisation faces: duplicate data entry with inconsistency between systems; inability to get a single view of an asset across systems; expensive manual reconciliation at project milestones; and data migration costs when replacing or upgrading systems.

Standards that enable data interoperability: ISO 15926, CFIHOS, and open APIs

Data interoperability in asset-intensive industries relies on:

• ISO 15926: Provides the semantic foundation for describing assets and their properties in a system-independent way — enabling different tools to mean the same thing when exchanging data about equipment
• CFIHOS: Defines the specific data requirements for project handover, built on ISO 15926, ensuring that handover data is immediately usable in owner-operator systems
• Open APIs and data exchange formats: REST APIs, standard file formats (JSON, XML, IFC), and platform-specific connectors enable practical system-to-system integration
• Common identifiers: Consistent use of equipment tag numbers and document numbers as shared keys that different systems use to refer to the same asset or document

Data interoperability vs data integration: what is the difference?

Data integration typically refers to the technical process of connecting systems and moving data between them (via ETL processes, APIs, or middleware). Data interoperability is the broader concept: whether the data from one system is actually meaningful and usable in another, without manual interpretation. Integration is a technical capability; interoperability is the quality outcome that integration enables.

Common data interoperability failures in engineering projects

• Tag numbers in engineering systems that do not match the format used in the CMMS — preventing automatic equipment record population at handover
• Equipment class definitions in supplier data that do not align with owner-operator templates — requiring manual remapping
• Document metadata schemas that differ between the EPC's EDMS and the owner's EDMS — causing import failures
• Unit systems or measurement conventions that differ between engineering and operational systems

Frequently asked questions about data interoperability

What is the difference between data interoperability and data integration?
Integration is about connecting systems technically; interoperability is about whether the exchanged data is actually meaningful and correct in the receiving system. You can have integration without interoperability if the data exchanged is ambiguous or mismatched.

How does Sharecat support data interoperability?
Sharecat aligns with open standards including ISO 15926 and CFIHOS, uses consistent equipment tag numbers as cross-system identifiers, and provides APIs for integration with CMMS, ERP, and analytics platforms — enabling asset data to flow reliably between engineering and operational systems.

Related concepts

• ISO 15926
• CFIHOS
• Asset Data Migration
• Digital Backbone
• Master Data Governance