FAIR Lineage

FAIR lineage refers to documenting and tracing how data is created, transformed, moved, and used over time in a way that aligns with the FAIR data principles: Findable, Accessible, Interoperable, and Reusable. In industrial and regulated manufacturing environments, it is used to understand where critical data came from, how it has changed, and which systems, processes, or decisions have relied on it.

Key elements

FAIR lineage typically includes:

• Provenance information: the original source of the data, such as a machine, test stand, inspection station, or external supplier system.
• Transformation history: records of calculations, aggregations, mappings, and edits applied to the data in systems like MES, ERP, PLM, QMS, or analytics tools.
• System and workflow context: where the data was stored and used, including applications, interfaces, and integration points.
• Reference and versioning: identifiers, timestamps, and version numbers that make specific datasets findable and distinguishable over time.

When implemented, FAIR lineage information is often captured through audit trails, event logs, integration metadata, and standardized identifiers across OT and IT systems. This supports traceability of product genealogy, quality records, and compliance evidence without being limited to any one software product or platform.

Operational relevance in manufacturing

In manufacturing operations, FAIR lineage commonly appears as:

• Linking sensor or machine data to specific work orders, lots, or serial numbers used in traceability and genealogy.
• Showing how inspection results flow from metrology equipment into FAI reports, AS9102 forms, or electronic DHR records.
• Tracking how routing, work instructions, or specifications from PLM or ERP are transformed before being displayed in MES or digital traveler systems.
• Providing evidence of which data and versions were used during analysis, CAPA investigations, or audits.

FAIR lineage does not require that all data be publicly shared. It focuses on structured, well-documented metadata and traceability so that authorized stakeholders can reliably discover, interpret, and reuse data across systems and over time.

Common confusion

• FAIR lineage vs. product genealogy: Product genealogy describes the physical history of a part or assembly (materials, processes, and operations). FAIR lineage describes the history of the data about that part, often used to support or explain the genealogy.
• FAIR lineage vs. simple audit logs: An audit log may show who changed a record and when. FAIR lineage emphasizes a more complete, structured view of data sources, transformations, and relationships so data remains findable, interpretable, and reusable across tools.

Relation to FAIR principles

FAIR lineage is one practical way to apply FAIR principles in regulated operations. By maintaining clear data lineage, organizations make it easier to:

• Locate specific datasets and their origins (Findable).
• Retrieve them through documented systems and formats (Accessible).
• Use them across heterogeneous OT/IT platforms (Interoperable).
• Reanalyze or repurpose them with confidence in their history (Reusable).