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For large distributed environmental information systems built for projects of national significance, such as eReefs and Bioregional Assessments, it is crucial they be able to capture information about their data processing in order to be able to trace the lineage of their data products. Policy and decision makers may need to know great detail about the processes that created data products in order to trust them as they influence crucial and high profile political decisions. Scientists may even need to be able to recreate modelling or data manipulation processes long after their original implementation in order to verify results. There are a series of tools that help in this task: there is a W3C Recommendation for a 2 nd generation provenance data model and Semantic Web ontology that has been developed by an international team of provenance researchers, known as PROV-O (Moreau and Missier, 2013). It is intended that it be used to represent the provenance of generic processes and can therefore be used as a common information format for projects that contain heterogeneous processes. Researchers in the CSIRO have developed a Persistent ID Service (PID) that helps to manage the identity of 'things' (information resources and representations of real world features) (Golodoniuc, 2013) for which, when those things are generated by human processes, provenance can be recorded. Provenance information can be very complex and different for every single process recorded, thus making storage difficult. Even though there are mechanisms (triplestores) built to store data of the PROV-O type, they are not massively scalable so we have used a recently popular, schema-less, databases that is able to store large collections of data 'documents' without forcing structural constraints on them. Additionally, the use of Linked Data through a variant of the Linked Data API (Epimorphics, 2013), also by CSIRO members, can be used to provide access to different forms, or views, of the 'things' stored. Putting these four developments together allows us to represent, manage, store and provide access to provenance data in novel ways. Implementing this is the focus of this paper. A provenance architecture using the PROV-O ontology, PID Services, variant Linked Data APIs and several support services has been tested with several automated workflows, notably the Bureau of Meteorology's Australian Hydrological Geospatial Fabric's Contracted Catchments production workflow. We describe the development of this architecture and detail the componentry it uses - in particular the new Provenance Management System PROMS. The methodology and architecture described here, more than the specific tools detailed, are this paper's contribution to large, multi-part, information systems' provenance handling so we present this information in order to demonstrate and approach, not to evangelise the use of a specific tool.

piantadosi, j., anderssen, r.s. and boland j. (eds) modsim2013, 20th international congress on modelling and simulation

A method and example system for managing provenance information in a heterogeneous process environment – a provenance architecture containing the Provenance Management System (PROMS)