K5. Data governance

As data capture, storage, and processing technology improves, and the range of data types and volume of available data increases, the development of formalised data management systems within an organisation is becoming increasingly important. Researchers require data to be accessible, logically structured, secure, properly archived, legally obtained, and to have demonstrable integrity. This highlights the need to understand and define data provenance so that the genesis of data can be clearly demonstrated, as well as having a well-defined set of processes that encompass data governance. This session invites papers describing aspects of data management systems including: Data governance processes; Data provenance; Establishing data management policy and culture; The development of appropriate data management tools such as a metadata catalogue, data storage and delivery methods; Data publishing and data discovery; Data custodianship and curation; Data licensing processes, including defining intellectual property rights and developing inter-agency data sharing agreements; The development of workflow processes for generating reports, creation of audit trails for checking reported results and for regenerating data if necessary; and The analysis of data uncertainty and quality control and assurance. This session provides a forum for the exchange of ideas and methods for the provision of robust data management solutions, which are integral support platforms for science delivery and the long-term maintenance of information. Abstracts addressing these topics, or closely related issues, are welcome.