This Agreements ontology is designed to model 'agreements' which are social contracts that include: licenses, laws, contracts, Memoranda of Understanding, standards and definitional metadata. Its purpose is to support data sharing by making explicit the relationships between agreements and data and agreements and Agents (people and organisations). Eventually it will also help with the interplay between different classes of agreements. We think of this ontology as a 'middle' ontology, that is one which specializes well-known, abstract, upper ontologies and is able to be used fairly widely but is expected to be used particular contexts in conjunction with detailed, domain-specific, lower ontologies. We have tried to rely on: existing agent, data manipulation, metadata and licence ontologies where possible. As such we specialise the ORG and FOAF ontologies; the PROV ontology; the Dublin Core Terms RDF schema & DCAT ontology; and the ODRS vocabulary & Creative Commons RDF data models for those areas, respectively

Geoscience Australia (GA) is an agency committed to providing transparent and reproducible information. It is currently implementing an enterprise approach to provenance management using the PROV Data Model as its conceptual base, generic Linked Data tooling and a dedicated provenance store for provenance information management and toolkits integrated into business process' software, or stand-alone interfaces, for provenance information capture, as recommended in a 2015 plan. Business Analytics have been conducted for several agency processes identifying provenance requirements, solutions for which are now being implemented. Preliminary provenance information from these systems has been collected.\\ Mapping processes to PROV and reporting integration has been straightforward however we've encountered difficulties in enabling Linked Data access to repositories and registries holding the processes' data and metadata due to their heterogeneity and existing perceptions about data stewardship. Such access to source data from scientific products via process' representations in PROV are required for reproducibility.