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Data interoperability is the ability of different systems, applications, and organisations to exchange, understand, and use data consistently without repeated manual interpretation or transformation. Interoperable data is not simply transferred from one system to another — its structure, context, and meaning remain usable by the receiving system.
Data interoperability depends on systems agreeing not only on how data is transferred, but also on how that data is structured and interpreted. Common data formats and schemas define the structure of exchanged information, APIs and integration interfaces provide mechanisms for moving it, shared identifiers connect records to the same real-world objects, and reference data and metadata preserve meaning and context.
In asset-intensive industries such as oil and gas, energy, chemicals, and utilities, interoperability enables information to move reliably between engineering design tools, engineering document management systems (EDMS), procurement platforms, CMMS, ERP systems, and digital twin environments throughout the asset lifecycle.
Without interoperability, organisations may successfully transfer a file or dataset while still being unable to use the information automatically. Equipment identifiers may differ, attributes may have different names, units may be inconsistent, or two systems may interpret the same field differently.
The result is manual mapping, reconciliation, duplicate data entry, and avoidable data quality problems.
Data interoperability can be understood at several levels. A connection between two systems does not necessarily mean that the systems are fully interoperable.
For asset information, semantic interoperability is particularly important.
Two systems may technically exchange an equipment record, but if one classifies an item as a centrifugal pump while another uses an incompatible equipment hierarchy or different attribute definitions, additional mapping and interpretation are still required.
True interoperability therefore requires more than connectivity. The receiving system must be able to understand what the transferred information represents and use it correctly.
Data integration and data interoperability are closely related, but they are not the same thing.
Data integration generally describes the technical process of connecting systems and moving or combining information between them. This may involve APIs, ETL processes, middleware, connectors, or asset data migration.
Data interoperability describes whether that information can be exchanged and used consistently across those systems while retaining its meaning and context.
For example, an EPC may create an integration that transfers equipment records from an engineering database into an owner-operator's CMMS. The systems are technically integrated.
But if equipment classes, attribute names, units, or tag identifiers do not correspond, the transferred records may still require manual mapping before they can be used.
Put simply:
Integration creates the connection. Interoperability makes the exchanged data usable.
Capital projects generate asset information across many organisations and systems before that information reaches operations.
Engineering contractors create equipment and design data. Suppliers provide technical attributes and documentation. EPCs consolidate project information. Owner-operators then need that information in operational systems such as CMMS, ERP, EDMS, and digital asset platforms.
Without interoperability, every transition can become a mapping and reconciliation exercise.
Typical consequences include:
Interoperability reduces these barriers by establishing consistent structures, identifiers, definitions, and exchange mechanisms before information moves between systems.
This is closely connected to data quality management. Interoperability helps systems exchange and interpret information consistently, while data quality management ensures that the information being exchanged is complete, valid, consistent, and fit for purpose.
Standards are an important part of interoperability because they give different organisations and software systems agreed ways to structure and interpret information.
For engineering and asset information, two particularly relevant standards and specifications are:
Open APIs and commonly supported exchange formats provide technical mechanisms for transferring information, but technical connectivity alone does not guarantee interoperability. Systems must also agree on the meaning and structure of the information being exchanged.
Common identifiers are equally important.
A consistent equipment tag number, for example, can provide the shared key that allows engineering information, documents, maintenance records, and operational data to be associated with the same physical asset across different systems.
A governed Master Tag Register (MTR) can therefore play an important role in establishing consistent asset identity across the project and operational lifecycle.
Achieving interoperability is difficult when systems and organisations have developed their information structures independently.
Common challenges include:
These challenges explain why data interoperability is both a technology problem and an information-management problem.
Connecting two systems is relatively straightforward compared with ensuring that the information exchanged between them remains accurate, understandable, and usable.
Effective data interoperability allows organisations to use information across systems without repeatedly restructuring or reconciling it.
For asset-intensive organisations, potential benefits include:
The objective is not simply to move more data.
It is to ensure that the same information retains its meaning and usefulness as it moves between people, organisations, systems, and lifecycle phases.
Improving interoperability starts before systems are connected.
Organisations should first establish which information needs to move between systems, what that information means, and who is responsible for governing it. They can then standardise identifiers, classifications, attributes, units, metadata, and exchange requirements where appropriate.
A practical approach includes:
Interoperability and data quality therefore need to be managed together.
A technically perfect interface cannot make inaccurate source information trustworthy, just as high-quality data cannot flow efficiently between systems if every receiving application interprets it differently.
Consider a centrifugal pump being handed over from an EPC to an owner-operator.
The EPC's engineering systems may contain the equipment tag, manufacturer, model, design conditions, technical attributes, and associated drawings and documents.
The owner-operator may need different portions of that information in its CMMS, ERP, EDMS, and other operational systems.
With poor interoperability, each receiving system may require a separate mapping exercise. Equipment names may differ, attributes may need to be renamed, document relationships may need to be rebuilt, and units may require conversion.
With interoperable asset information, the pump is identified consistently across systems, its technical attributes use agreed definitions and units, and its documentation remains associated with the correct equipment tag.
The receiving systems can therefore process and use the information with substantially less manual interpretation.
The same principle applies across a complete document handover package: interoperability helps preserve the relationships between structured asset data, tags, metadata, and engineering documentation as information moves from project execution into operations.
Sharecat supports data interoperability by providing a governed environment for structuring and managing asset data and documentation as information moves from projects into operations.
Asset information can be organised around consistent equipment identifiers and defined information requirements, helping project teams identify mismatched classifications, missing attributes, inconsistent values, and other issues before information is transferred into downstream operational systems.
A controlled Master Tag Register provides a consistent asset identity, while technical attributes and engineering documentation can remain associated with the relevant equipment throughout project execution and handover.
By supporting structured asset information and alignment with standards and specifications such as ISO 15926 and CFIHOS, Sharecat helps create information that can be exchanged more consistently between engineering, project, and operational environments.
The objective is not simply system-to-system connectivity, but usable asset information that retains its context and meaning as it moves across the asset lifecycle.
What does data interoperability mean?
Data interoperability means that different systems can exchange data and use it consistently while preserving its structure, context, and meaning. It goes beyond simply transferring information between applications.
What is an example of data interoperability?
An example is equipment data moving from an EPC's engineering system into an owner-operator's CMMS while retaining the correct tag number, equipment classification, technical attributes, units, and associated documentation.
What is the difference between data interoperability and data integration?
Data integration creates the technical connection or process for moving and combining data. Data interoperability ensures that information exchanged through that connection remains understandable and usable by the receiving system.
What are the main types of data interoperability?
Data interoperability is commonly discussed at technical, syntactic, semantic, and organisational levels. Technical interoperability enables connectivity, syntactic interoperability aligns structures and formats, semantic interoperability preserves meaning, and organisational interoperability aligns processes and governance.
What is semantic data interoperability?
Semantic interoperability means that different systems interpret exchanged information with the same meaning. It typically relies on shared terminology, classifications, reference data, metadata, identifiers, and data models.
Why are standards important for data interoperability?
Standards provide common rules and definitions for representing, structuring, or exchanging information. In asset information management, standards such as ISO 15926 and specifications such as CFIHOS can reduce ambiguity and bespoke mapping between organisations and systems.
Is data interoperability the same as having an API?
No. An API provides a technical mechanism for systems to exchange information, but it does not by itself guarantee interoperability. The systems must also agree on identifiers, structures, definitions, context, and meaning for the exchanged data.
Why is data interoperability important during project handover?
Project handover brings together information from EPCs, suppliers, engineering applications, and document systems before it is transferred into an owner-operator's operational environment. Interoperability reduces the amount of manual mapping and interpretation required to make that information usable after handover.
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