<p>Through the experiences of building several information infrastructures in Australia we have come to wanting to calculate the properties of data licenses in as automated a fashion as possible. To do this, we have trialed decomposing licenses into individual requirements, building on the Creative Commons Rights Expression Language (CC REL) information model (http://creativecommons.org/ns). Such a decomposition, along with the separation of rights management from licenses as per the Open Data Rights Statement vocabulary (ODRS) model (http://schema.theodi.org/odrs/), allows us to model very many different licenses as simple collections of common requirements. In Car & Stenson (2015) we posited requirement resolution actions that systems or people can undertake that satisfy individual requirements and show how systems can b e made to automatically satisfy certain classes of requirements but certainly not all. <p>We are not currently able to automate every aspect of license requirement adherence and we believe that full automation is impossible, however every bit of automation improves the efficiency of data delivery. <p>In this presentation we report on some aspects of our license model, including the modelling of requirements and their resolutions. We also show how such modelling can enhances data access by comparing the status quo and possible future delivery of data via a large multi -agency, Australian data generation project; the Bioregional Assessments Programme.

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