Effective use of PIDINST in the automation of data sets publication: Verifiable Research Objects using RO-Crate and PROV-O

This presentation details a technical framework for transforming static research data into Executable Research Objects (ERO). By leveraging the W3C Provenance Ontology (PROV-O) and the RO-Crate packaging standard, the framework enables the structural and logical verification of complex scientific simulations and experiments.

Key Concepts Addressed:

PIDINST Integration: The use of Persistent Identifiers for Instruments to anchor physical hardware metadata (calibration, manufacturer, and model) within the digital provenance chain.
Mathematical Graph Theory in RDM: An analysis of Graph Density, Semantic Entropy, and Mathematical Modularity (Q) to quantify the "Compactness vs. Richness" of institutional Knowledge Graphs.
Automated Auditing: How high modularity within a metadata graph facilitates automated consistency checks between control logic (e.g., MRAC) and specific execution environments (e.g., Darwin ARM64).
The 5-Star Data Path: Transitioning from structured RDF (4-star) to Linked Open Data (5-star) by connecting local research entities to global PID ecosystems (ORCID, ROR, DOI, and PIDINST).

The framework specifically addresses the "Semantic Gap" between raw data generation and scientific intent, providing a roadmap for independent auditors and automated orchestrators to verify the "Efficiency of Truth" in reproducible research.