Enabling model and simulation provenance and data transparency with Provena
Provena is a cloud-based provenance management system that enables users to register, manage, and publish knowledge artefacts (e.g. datasets, software) used and generated within a scientific or modelling workflow (see https://provena.io). It allows the capture of any simulation or model run, their results, and associated data (including preceding model run records and existing datasets) in an integrated, linked and consistent manner which enables traceability of a portfolio of modelling activities. Provenance captured in Provena is structured using an extension to the Prov Ontology (Prov-O), a W3C standard for describing provenance. Provena is being applied in the Modelling and Decision Support (MDS) subprogram of the Reef Restoration and Adaptation Program (RRAP) and in the National Bushfire Intelligence Capability (NBIC). Both MDS and NBIC require provenance capture to enable transparency of the results from the modelling and in support of data reproducibility. In this talk, we will give an overview of how Provena is being applied to manage data and their lineage as part of an ensemble of models and decision support tools in both MDS (for advising Great Barrier Reef intervention deployments), and NBIC (for developing bushfire hazard and risk maps). We show how Provena can be applied in other modelling and simulation activities and projects with similar needs in other domains.
Institutions
- Commonwealth Scientific and Industrial Research Organisation (AU)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-10-31
- DOI
- https://doi.org/10.5281/zenodo.15293612
- Primary Topic
- RNA Interference and Gene Delivery
- Type
- article
- Field-Weighted Citation Impact
- 0.00