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Public DMPs

Public DMPs are plans created using the DMPonline service and shared publicly by their owners. They are not vetted for quality, completeness, or adherence to funder guidelines.

Project title  Template  Organisation Owner Download
Development of modelling tools for vertical axis turbines University of Manchester Generic Template University of Manchester Omar Sherif Mohamed (new window) Opens in new window
Supporting FAIR-from-the-Start with Electronic Research Notebooks University of Manchester Generic Template University of Manchester Zuzanna Zagrodzka (new window) Opens in new window
Identifying Mechanisms of Failure of Cartilage Repair Surgery University of Manchester Generic Template University of Manchester Gwenllian Tawy (new window) Opens in new window
Engineering evolutionary trajectories in Bdellovibrio to develop sustainable crop protection University of Manchester Generic Template University of Manchester Danna Gifford (new window) Opens in new window
Fluoridation modifies the quantum coherence of near-infrared organic rare-earth molecules (FaMiQ) University of Manchester Generic Template University of Manchester Huanqing Ye (new window) Opens in new window
Understanding barriers and facilitators to hearing aid use in teenagers University of Manchester Generic Template University of Manchester Sumeya Abdi (new window) Opens in new window
PhD University of Manchester Generic Template University of Manchester Wei Bin Timothy Siew (new window) Opens in new window
Factors Influencing Usability and Perceived Satisfaction with a Continuous Monitoring and Deterioration Alerting System in a Non-ICU Setting: A Mixed-Methods Study University of Manchester Generic Template University of Manchester Jo-Fan Pan (new window) Opens in new window
Thesis for PhD Development Policy and Management, "Geopolitics and Upgrading in Global Value Chains: The Case of Palm Oil and Nickel in Indonesia" University of Manchester Generic Template University of Manchester Puji Basuki (new window) Opens in new window
Image Segmentation Using Deep Learning Techniques University of Manchester Generic Template University of Manchester Zeinab Tirandaz (new window) Opens in new window