1. Leeds Aims : design a lightweight survey to maximise response understand data volume and variety for capacity planning raise awareness of new institutional policy How much research data would you typically generate in a year? What % of research data generated would you need to keep for others to validate your research findings? Fewer than 10% of respondents currently deposit their data with a national or international data repository. Interviews – build a picture of data management practices and requirements Test data – use research data to test virtualised storage (F5) and repository (DataFlow / EPrints) Training – pilot a face to face training session for PhD students Data management planning – test DMPOnline Case studies Test DMPOnline with case studies and beyond Feedback to DCC, adapt, re-test Embed practice in stakeholder workflows Gather example DMPs for training Has a data management plan ever been completed for any of your research projects? (data survey question) Test DMPOnline with case studies and beyond Feedback to DCC, adapt, re-test Embed practice in stakeholder workflows Gather example DMPs for training Has a data management plan ever been completed for any of your research projects? (data survey question) Further details: RoaDMaP web site: http://library.leeds.ac.uk/roadmap-project/ Contact: roadmap@leeds.ac.uk Poster acknowledgements: RoaDMaP teamhttp://library.leeds.ac.uk/roadmap-project/roadmap@leeds.ac.uk Training working group with cross team membership Identification of training stakeholders Pilot session for PhDs to be delivered by the Staff and Departmental Development Unit  Research focus - the digitisation of 2" 24-track magnetic tapes of film music recording sessions.  Research produces multi-track audio data plus associated written documentation.  Key challenge: potential deterioration of magnetic source media requiring the tapes to be 'baked' first by a specialist company. Research focus: to explore how personal and family relationships develop and change over time. Research data challenges: Relationship between institutional and subject specific repositories Identification of next steps and resources required to migrate data from one repository platform to another. Our case studies represent a range of subject disciplines and different phases of the research lifecycle: Pre-award: Music Live-award: Engineering (SpineFX) Post-award: Sociology (Timescapes); Music Funded 2007-2012 by ESRC. Created an archive of qualitative longitudinal (QL) data for preservation, sharing and re-use. Timescapes is an example of effective data management practice, bringing highly beneficial expertise to the RoaDMaP project. We are exploring different roles in data management through this case study – including Library staff. Visualization of MM lesions (larger than 3.2mm in diameter) SpineFX is a Marie Curie Initial Training Network (ITN) comprising 4 Universities and 3 SMEs. The research focus: treatment of spinal fracture arising from osteoporosis, metastatic bone disease and trauma. The research generates significant amounts of imaging and mechanical related data e.g. CT scan images, associated metadata and contextual documentation. Research data challenges: - scale of data (6Tb) - sharing with European colleagues - linking different data sets with context data and scans SpineFX is a Marie Curie Initial Training Network (ITN) comprising 4 Universities and 3 SMEs. The research focus: treatment of spinal fracture arising from osteoporosis, metastatic bone disease and trauma. The research generates significant amounts of imaging and mechanical related data e.g. CT scan images, associated metadata and contextual documentation. Research data challenges: - scale of data (6Tb) - sharing with European colleagues - linking different data sets with context data and scans Anticipated benefits to SpineFX: long term storage of accessible data compromising linked data sets “Always seems a good idea but takes time we don't really have - and for a novice it is difficult to know where to start.” Leeds Research Data Management Policy (Extract) A data management plan that explicitly addresses the capture, management, integrity, confidentiality, preservation, sharing and publication of research data must be created for each proposed research project or funding application. Leeds Research Data Management Policy (Extract) A data management plan that explicitly addresses the capture, management, integrity, confidentiality, preservation, sharing and publication of research data must be created for each proposed research project or funding application. The approach to training is influenced by the cycles of Kolb, experiential learning, and Deming, management process. Institutional research data steering and working groups & diverse stakeholder involvement DMP links with new grants management system, other IT systems Sustainable financial model – in conjunction with central Finance Sustainable ownership of RDM policy and guidance Embedding