Data Integrity and FAIR Evidence for Photopolymer Qualification: Raw Data, Metadata, Audit Trails and Reuse

Photopolymer qualification increasingly depends on digital evidence: formulation and lot records, printer configuration, exposure data, environmental logs, post-processing history, instrument files, images, spectra, derived tables, scripts and release decisions. Retaining a final PDF report is not enough to reconstruct how a result was generated, while retaining large volumes of raw files without usable metadata does not make the evidence interpretable. Data integrity and FAIR data stewardship address different failure modes and should not be treated as synonyms. Integrity asks whether a record is attributable, legible, contemporaneous, original, accurate, complete, consistent, enduring and available. FAIR asks whether digital objects and their metadata are findable, accessible under stated conditions, interoperable and reusable. A dataset can satisfy one family of principles while failing the other. This review develops a qualification architecture for photopolymer manufacturing and testing in which raw data, contextual metadata, transformations, audit trails and decision records remain linked as a versioned evidence graph. It adapts established FAIR principles, provenance models and additive-manufacturing data frameworks to the material-process-workflow state of vat photopolymerisation. The minimum package records material identity and lot, machine and firmware, optical and thermal state, build definition, post-processing, specimen conditioning, instrument identity and calibration, test method, software and script versions, data transformations, exclusions and release criteria. Hashes and immutable identifiers protect object identity; provenance records explain lineage; audit trails preserve who changed what and when; controlled vocabularies and machine-readable formats enable comparison and reuse. The central conclusion is non-compensatory: a result should not support qualification if its origin cannot be reconstructed, if critical context is missing, or if transformations cannot be reproduced, even when the final number appears plausible.

ER-298 · Version 0.3.