provenanceontologia

Provenanceontologia is a field that combines provenance management with ontology engineering to describe the origin, history, and transformation of data and digital objects in machine-interpretable terms. It seeks to enable traceability, reproducibility, and trust by providing formal representations of where information comes from, how it was produced, under what conditions, and by whom. Core ideas include representing entities such as artifacts, activities, and actors, and modeling the relations that connect them, such as generation, usage, derivation, and attribution.

A widely used reference in provenanceontologia is the W3C PROV data model and its ontology serialization, PROV-O, which offer a minimal set of classes and properties for expressing provenance across domains. Domain-specific ontologies build on PROV-O to capture context—for example scientific datasets, digital libraries, or manufacturing processes. Techniques used include annotating data with provenance metadata, aligning domain ontologies with upper or foundational ontologies, and applying reasoning rules to infer new provenance facts.

Applications include ensuring reproducibility of scientific experiments, enabling data governance and compliance, supporting scholarly communication and data integration, and improving the trustworthiness of digital objects in heritage or cultural domains.

Challenges include achieving semantic interoperability across heterogeneous sources, handling large-scale and streaming provenance, protecting privacy and security of provenance data, and managing evolving provenance as systems change.

See also: PROV, PROV-O, data provenance, ontology engineering, metadata, data lineage.