{
  "researchId": "JPC-26-00131",
  "researchUrl": "https://jipcet.org/r/JPC-26-00131",
  "articleUrl": "https://jipcet.org/articles/jipcet-2026-0131",
  "articleRef": "JIPCET-2026-0131",
  "externalDoi": null,
  "title": "A Reference Architecture for Industrial IoT Data Governance: Provenance, Retention and Cross-Plant Access Control",
  "authors": [
    {
      "name": "Ethan Hale",
      "affiliation": "University of Wollongong, Australia",
      "orcid": null
    },
    {
      "name": "Aisha Rahman",
      "affiliation": "Universiti Teknologi Malaysia, Malaysia",
      "orcid": null
    },
    {
      "name": "Nils Bergstrom",
      "affiliation": "University of Wollongong, Australia",
      "orcid": null
    }
  ],
  "abstract": "Background. Industrial telemetry commonly outlives the control systems, vendors and plant configurations that produced it, so questions of provenance, retention and cross-plant access recur years after ingestion was designed. Existing industrial data platforms treat governance as a policy layer applied after the fact, which leaves provenance unreconstructable once source systems are decommissioned. Objective. We propose a reference architecture that makes provenance a first-class ingestion concern and evaluate whether it can be adopted in operating plants without degrading ingestion performance. Methods. The architecture separates ingestion, an append-only provenance ledger and policy enforcement into independently versioned layers, with a schema-evolution contract between them. We evaluated it through four deployments — automotive stamping, food processing, speciality chemicals and discrete electronics assembly — over nine months, measuring sustained ingestion throughput and end-to-end latency against pre-adoption baselines, provenance query completeness on 240 audit questions drawn from real incident and compliance requests, and engineering effort. Results. All four sites sustained baseline throughput (aggregate 1.4 million points per second) with a median 3.1% latency increase and 11% storage overhead for ledger metadata. Provenance queries were answerable for 96% of audit questions against 41% on the pre-existing platforms, and mean time to answer fell from 6.4 hours to 9 minutes. Retention policy could be applied per data class rather than per store at three of four sites; the fourth was blocked by a vendor historian without deletion primitives. Conclusion. Treating provenance as an ingestion-time obligation rather than a later annotation is achievable at industrial throughput and materially improves auditability, but requires source systems that expose deletion and identity primitives.",
  "keywords": [
    "industrial IoT",
    "data governance",
    "provenance",
    "manufacturing systems",
    "reference architecture",
    "data retention"
  ],
  "area": "Emerging Technologies",
  "issue": "JIPCET 2026; 3(1)",
  "pageRange": "35–66",
  "published": "2026-02-26",
  "received": "Received 12 Aug 2025",
  "version": "1.0",
  "versions": [
    {
      "version": "1.0",
      "date": "2026-02-26",
      "note": "Version of record published after editorial decision."
    }
  ],
  "articleType": "Research Article",
  "reviewStatus": "Peer reviewed under named human editorial supervision",
  "peerReviewed": true,
  "handlingRecord": "Handled by a named JIPCET editor of record, who read the manuscript, oversaw review and approved the decision.",
  "methodology": "Research Article",
  "dataAvailability": "Available from the corresponding author on reasonable request, in line with participant and organisational agreements.",
  "codeAvailability": "Analysis procedures are documented in full in the methods section of the article.",
  "referenceCount": 6,
  "references": [
    "Hale, E. & Rahman, A. (2025). Provenance ledgers in manufacturing telemetry. Proceedings of IoT-SE, 45–59.",
    "Bergstrom, N. (2024). Logical identity across equipment replacement. Computers in Industry 156, 104–121.",
    "Rahman, A., Hale, E. & Bergstrom, N. (2026). Retention primitives in industrial historians. JIPCET 2(2), 66–89.",
    "Osei, P. (2025). Append-only stores for regulated telemetry. ACM Transactions on Storage 21(2), 1–24.",
    "Tan, M. (2025). Metadata growth bounds in time-series governance. Journal of Data Engineering 12(3), 210–233.",
    "Marsh, S. & Ng, A. (2024). Governance layering in operational technology. Journal of Manufacturing Systems 73, 401–418."
  ],
  "replications": "No independent replication recorded to date.",
  "corrections": "No corrections issued. Any correction is published as a new version with a dated entry in the version history.",
  "license": "CC BY 4.0",
  "fullTextHtml": "https://jipcet.org/articles/jipcet-2026-0131",
  "fullTextPdf": null,
  "publisher": {
    "name": "JIPCET Editorial Office",
    "url": "https://jipcet.org",
    "email": "editor@jipcet.org"
  },
  "journal": {
    "title": "Journal of Innovation, Product, Computing & Emerging Technologies",
    "short": "JIPCET"
  }
}