Data Provenance and the Future of Africa's Global Fashion Value Chain: A Framework for Trusted, Traceable and Interoperable Industrial Systems

This paper establishes data provenance as cross-cutting industrial infrastructure for Africa's Global Fashion Value Chain (GFVC). Expanding the concept beyond product traceability, it defines provenance across nine dimensions — material, geospatial, process/method, knowledge, technological, custody, certification, cultural and circular — and introduces "method provenance" as a defined concept: the evidentiary record of how a material or product was produced, transformed, recovered or regenerated. The paper maps methods, knowledge and technologies across a nine-stage value chain (Soil/Origin → Production → Transformation → Manufacturing → Logistics → Market/Shelf → Use → Recovery → Regeneration), proposes a provenance architecture organised around five dimensions (Place, Material, Method & Knowledge, Technology & Transformation, Custody & Verification) beneath a layer of trust, governance and interoperability, and specifies a ten-field provenance data model built on open standards (GS1 EPCIS/CBV 2.0, W3C Verifiable Credentials, UN Transparency Protocol). Governance provisions cover data ownership, four-tier access (public / B2B / regulatory / custodian-restricted), Indigenous and traditional knowledge governance, and a registration–verification–certification–monitoring lifecycle. The work is being developed for integration into GFVC Africa's existing institutional and industrial architecture, with Smart Textile Valley as the operational demonstration environment, and invites multidisciplinary partners to contribute to its development, testing and governance. Applications span EU Digital Product Passport readiness, AfCFTA rules of origin, ESG and anti-greenwashing, circularity, cultural intellectual-property protection, TVET and industrial planning.