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A reference data library (RDL) is a managed collection of standardized classes, properties, definitions, units of measure, and permitted values used to describe equipment, materials, documents, and other asset information consistently.
Rather than every contractor, supplier, engineering discipline, or software system using its own terminology, a reference data library provides a shared vocabulary. This allows asset information to retain the same meaning as it moves between organizations, projects, and systems.
In asset-intensive industries such as oil and gas, energy, chemicals, and utilities, reference data libraries support consistent asset information throughout the lifecycle. They also provide an important foundation for industry standards such as CFIHOS and ISO 15926.
A reference data library defines the standardized concepts used to classify and describe asset information.
Depending on the standard and implementation, an RDL can include:
For example, an RDL can define centrifugal pump as an equipment class and establish the technical properties expected for that class. EPCs, suppliers, and owner-operators can then structure pump information according to the same definitions instead of creating separate naming conventions and attribute structures.
This provides a consistent foundation for asset master data management across projects, facilities, and systems.
Large engineering projects generate information across many organizations, disciplines, suppliers, and software systems.
Without common reference data, the same equipment type or technical property may be described differently by different participants. One supplier may use one property name, another may use an abbreviation, while the owner-operator's system may expect an entirely different classification.
Those inconsistencies create mapping, validation, and reconciliation work when information needs to be consolidated, handed over, migrated, or integrated.
A shared reference data library helps organizations:
Reference data therefore provides part of the semantic foundation required for effective data interoperability.
Reference data libraries become particularly important when asset information needs to move between different organizations and systems.
ISO 15926 provides a framework for representing and exchanging lifecycle information about process plant assets using standardized semantics and reference data. Its different parts address the data model, reference data, implementation methods, and requirements for reference data libraries.
CFIHOS applies standardized information requirements and reference data to practical information exchange across capital projects and the asset lifecycle.
The CFIHOS Reference Data Library provides standardized classes, properties, units of measure, permitted values, and related reference information that allow owner-operators, EPCs, suppliers, manufacturers, and systems to describe asset information consistently.
The two are therefore closely related but not identical. ISO 15926 provides a broader semantic framework for plant lifecycle information, while CFIHOS uses standardized reference data as part of a practical specification for information requirements and handover.
Organizations do not necessarily rely on a single universal reference data library.
An industry-standard RDL provides a common baseline that can be shared between owner-operators, EPCs, suppliers, manufacturers, and software systems. This improves consistency across organizational boundaries and reduces the amount of project-specific mapping required.
However, an owner-operator or individual project may require additional classes, properties, or permitted values that are not covered by the industry baseline.
A project- or company-specific RDL can extend the standard to accommodate these requirements.
The challenge is extending reference data without introducing incompatible terminology that undermines the benefits of using a shared standard in the first place.
For this reason, ownership, approval workflows, version control, and controlled changes to reference data are important components of master data governance.
Connecting two systems technically does not necessarily mean that they understand exchanged information in the same way.
For example, an engineering system may use a different equipment classification, property name, or unit from the receiving CMMS or ERP system. An API can successfully transfer the record while the receiving application still interprets the information incorrectly or requires manual mapping.
A reference data library addresses the semantic part of this problem.
By giving systems and organizations common definitions for classes, properties, units, and values, reference data helps information retain its meaning when it moves between environments.
This is a fundamental part of data interoperability: information should not only move successfully between systems, but also remain understandable and usable when it arrives.
Reference data defines the standardized vocabulary, classifications, and permitted values used to describe information.
Master data represents the actual business objects or assets described using those standards.
For example, a reference data library might define:
The organization's asset master data then contains the actual pumps, equipment tags, manufacturers, design pressures, technical attributes, and other information associated with individual assets.
In simple terms:
Reference data defines how assets should be described. Master data describes the actual assets.
The two therefore work together. Reference data provides the standardized structure needed to create and maintain consistent asset master data.
The reference data library defines the vocabulary, while the Master Tag Register (MTR) contains the actual tagged assets within a project or facility.
For example, an RDL may define a particular equipment class and specify the properties associated with it. Individual tags in the MTR can then be classified according to that definition and populated with the appropriate technical information.
This relationship helps ensure that thousands of individual equipment records follow a consistent information structure rather than relying on project-specific, contractor-specific, or supplier-specific terminology.
The RDL therefore defines what the data means and how it should be structured, while the MTR applies those definitions to the actual tagged equipment population.
Reference data becomes particularly valuable during project information handover.
During engineering and procurement, asset information is generated by EPCs, package vendors, equipment manufacturers, and other suppliers. Without shared classifications and definitions, each organization may deliver information using different terminology and data structures.
At handover, those differences must then be mapped to the owner-operator's required structure before the information can be loaded into operational systems.
A reference data library allows those requirements to be defined earlier.
Suppliers and contractors can classify equipment and populate properties against agreed reference data while the information is being created. Validation can then identify incorrect classifications, missing properties, invalid units, or non-permitted values before final delivery.
This shifts data quality work upstream and reduces the amount of manual reconciliation required during handover and subsequent asset data migration.
Sharecat uses standardized reference data to structure and validate asset information received from EPCs, suppliers, and other project participants.
Tag and equipment data can be aligned with standardized equipment classes, properties, units, permitted values, and project information requirements before becoming part of the controlled asset information record.
This allows inconsistencies to be identified earlier in the information lifecycle, including:
Combined with a controlled Master Tag Register, data validation, and governance processes, reference data helps create consistent asset information that can be exchanged and reused across engineering and operational systems.
Instead of waiting until final handover to reconcile incompatible supplier datasets, reference data requirements can be applied while information is being submitted and validated.
What is a reference data library used for?
A reference data library provides standardized classes, properties, definitions, units, and permitted values so different organizations and systems can describe information consistently. In asset-intensive industries, RDLs are commonly used to standardize engineering and asset information across projects, suppliers, and operational systems.
What does RDL stand for?
RDL stands for Reference Data Library. It is a managed collection of standardized reference data used to classify and describe information consistently.
What is the difference between reference data and master data?
Reference data defines standardized classifications, properties, terminology, and permitted values. Master data contains the actual assets or business objects described using those definitions. For example, reference data may define the class centrifugal pump, while master data contains the individual pumps installed at a facility.
Why is a reference data library important for data interoperability?
A reference data library gives different organizations and systems a common vocabulary. This reduces semantic differences and helps ensure that exchanged information retains the same meaning in the receiving environment instead of requiring manual interpretation or mapping.
What is the CFIHOS Reference Data Library?
The CFIHOS Reference Data Library provides standardized reference information used to support consistent asset information exchange across capital projects. It includes classifications, properties, units of measure, permitted values, and related reference information used by project participants to structure asset data consistently.
Is the CFIHOS Reference Data Library the same as ISO 15926?
No. They are closely related but distinct. ISO 15926 provides a broader framework for representing and exchanging lifecycle information about process plants, while CFIHOS provides practical standardized information requirements and reference data for capital project information exchange and handover.
Can an owner-operator extend an industry reference data library?
Yes. An organization may need additional classes, properties, or controlled values for company- or project-specific requirements. These extensions should be governed carefully so they do not create unnecessary incompatibility with the underlying industry standard.
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