Metadata in research data Australia and the open provenance model: a proposed mapping

Research Data Australia (RDA) is a flagship data discovery service provided by Australian National Data Service (ANDS). RDA consists of two major components: a collection registry component that harvests metadata from a range of data providers and a data discovery component that makes metadata visible and searchable over the web. Metadata maintained at RDA are encoded according to the RIF-CS (Registry Interchange Format - Collections and Services) schema. RIF-CS is based on an international standard information model ISO2146:2010 that contains descriptive and administrative metadata for collections and related services, parties (people and organisations) and activities, and also supports the expression of relationships between those entities. In the past, metadata ingested to the RDA registry have had a focus on metadata describing data collections once created, and less on the data provenance describing how a data collection came to be. As data provenance has been gaining increasing importance in areas such as data intensive research and policy making, more and more data providers intend to capture and publish data provenance information in order to enhance data's trustfulness and reproducibility. ANDS partners are at different maturity stages in implementing systems to capture, represent and publish data provenance information. In terms of provenance representation, some data providers may conform to the W3C recommended provenance data model (PROV-DM), some may use a discipline specific data model which may or may not conform to a community endorsed standard, and others may use just free text. This paper compares the RIF-CS data model with PROV-DM and suggests a mapping between RIF-CS schema and the W3C recommended provenance ontology (PROV-O). The paper also discusses how one might go about linking provenance to RIF-CS records. This work will help to derive PROV data from contextual rich RIF-CS records and thus promote awareness and adoption of data provenance by ANDS partners.