This presentation is from the 'Opening UCL: An Afternoon Symposium on Open Education' event which was held at UCL on 13 March 2019.

As defined by the European Commission, Open Science consists of 8 pillars of understanding, amongst which are FAIR data and the European Open Science Cloud. Drawing on the results of the EC-funded LEARN project, this paper will look at the challenges which research data management brings to the research institution in an Open Science landscape where research data are at least as equally valued as publications. How, in Rewards systems, can FAIR and/or Open research data be valued as a route to reward and promotion? The paper will look at how these concepts have been embodied into the new UCL Academic Promotions Framework. In terms of skills development, what needs to happen to equip researchers (especially early career researchers) with the knowledge they need to work in a data-intensive environment? A recent European report has shown that, for the EU, the cost of not using FAIR data will be 10.2 bn euros a year. A second report promotes policy recommendations to make the FAIR data model sustainable. The paper will conclude by looking at the research infrastructure being put in place by UCL (University College London) to deliver on the research data agenda by studying in detail the launch of its new research data repository, which takes Open and FAIR data as the default. Sponsoring Organisation: Focus on Open Science Workshops 2019. https://www.focusopenscience.org/

Case studies of the use of open data as open educational resources. This collection presents the stories of our contributors’ experiences and insights, in order to demonstrate the enormous potential for openly-licensed and accessible datasets (Open Data) to be used as Open Educational Resources (OER). Open Data is an umbrella term describing openly-licensed, interoperable, and reusable datasets which have been created and made available to the public by national or local governments, academic researchers, or other organisations. These datasets can be accessed, used and shared without restrictions other than attribution of the intellectual property of their creators. While there are various definitions of OER, these are generally understood as openly-licensed digital resources that can be used in teaching and learning. The first case study presents an approach to educating both teachers and students in the use of open data for civil monitoring via Scuola di OpenCoesione in Italy, and has been written by Chiara Ciociola and Luigi Reggi. The second case, by Tim Coughlan from the Open University, UK, showcases practical applications in the use of local and contextualised open data for the development of apps. The third case, written by Katie Shamash, Juan Pablo Alperin & Alessandra Bordini from Simon Fraser University, Canada, demonstrates how publishing students can engage, through data analysis, in very current debates around scholarly communications and be encouraged to publish their own findings. The fourth case by Alan Dix from Talis and University of Birmingham, UK, and Geoffrey Ellis from University of Konstanz, Germany, is unique because the data discussed in this case is self-produced, indeed ‘quantified self’ data, which was used with students as material for class discussion and, separately, as source data for another student’s dissertation project. Finally, the fifth case, presented by Virginia Power from University of the West of England, UK, examines strategies to develop data and statistical literacies in future librarians and knowledge managers, aiming to support and extend their theoretical understanding of the concept of the ‘knowledge society’ through the use of Open Data. http://education.okfn.org/open-data-as-open-educational-resources-case-studies-of-emerging-practice/ DOI: http://dx.doi.org/10.6084/m9.figshare.1590031