GeoPROV: A Domain-Specialised Provenance Model for Spatial Data Supply Chains

Spatial data supply chains (SDSCs) transform authoritative observations into widely reused spatial products, but users typically lack machine-actionable provenance describing lineage, processing configurations, and custodianship. We introduce GeoPROV, a domain-specialised provenance model that profiles the W3C PROV framework and aligns with OGC GeoSPARQL to support standards-based representation and querying of spatial provenance. GeoPROV extends the Entity–Activity–Agent pattern with spatially meaningful entity types, explicit supply-chain roles, and first-class configuration artefacts. The model is formalised through a conceptual UML model and implementation-ready physical schema. We instantiate a provenance repository using the Geoscape Administrative Boundaries dataset and evaluate GeoPROV under three SDSC-relevant workloads: bounded upstream lineage traversal, downstream impact analysis, and GeoSPARQL-enabled spatial provenance queries. GeoPROV-based provenance infrastructures provide predictable, scalable performance when applying bounded traversal, index-aware spatial filtering, and validation-before-persistence. Overall, GeoPROV offers a reproducible, interoperable, and operationally viable foundation for spatial provenance, addressing key transparency, trust, and governance requirements in contemporary SDSCs.