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

One of the well-established methods used to ease data sharing between organisations and even teams within organisations is to use standards for data structure, metadata and interfaces. Standards are a form of agreement, as are MoUs, charters, deeds, licences, rules of the road and even the definitions for words. Man y of these other sorts of agreements are also important for data sharing communities too. In this paper we look to improve the efficiency of dealing with different forms of agreement within a data sharing scenario by presenting a prototype agreements ontology which models agreements themselves as ¿things¿ and the relationships between them and between them and data and them and agents. Having an agreements ontology allows us to start automating tasks that require knowledge of them. This may take the form of data repositories that can make intelligent choices about how to deliver or with old data without human intervention. We position 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 in particular contexts in conjunction with detailed, domain-specific, lower ontologies. We have relied on existing agent, data manipulation, and metadata ontologies where possible and as such we specialise the ORG and FOAF ontologies, the PROV ontology and DCAT and ODRS ontologies for those areas respectively. This paper and ontology supports work that we report elsewhere at SciDataCon2016, namely The Role of Social Architecture in Information Infrastructure (Box & Lemon) and Describing and Automating Requirements within Licenses and their Resolutions (Car & Stenson).