We design and implement a query language for a secure, interoperable, and multi-granular provenance framework, referred to as QL-SimP. Our language supports two provenance representations (relational and graph-based) due to its independence from the underlying provenance representation. It also supports various queries that can be utilized for difference provenance applications. We integrate Computational Research Infrastructure for Science (CRIS) — a real-world system for managing scientific data — with our provenance framework, thus making it possible to query CRIS provenance information by using our provenance language. We have also evaluated our provenance queries based on relational and graph databases.
Managing Real-World System Configurations with Constraints
