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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
Governing synergies and trade-offs with SDG2 in Kenya: a local to global study of climate-smart livestock in Kenya Data Management Plan NWO (September 2020) Wageningen University and Research (Netherlands) Rachel Gitundu (new window) Opens in new window
VR for Diversity Data Management Plan NWO (September 2020) Amsterdam University of Applied Sciences (Hogeschool van Amsterdam) Mirjam Vosmeer (new window) Opens in new window
Copy of Informal capacities aiding in reparation towards water sensitive India Data Management Plan NWO (September 2020) Erasmus University Rotterdam Neha Mungekar (new window) Opens in new window
Vici: Tracing Marine Macroplastics by Unraveling the Ocean’s Multiscale Transport Processes Data Management Plan NWO (September 2020) Utrecht University Erik van Sebille (new window) Opens in new window
Resilience in the picture Data Management Plan NWO (September 2020) Rijksuniversiteit Groningen Vera Heininga (new window) Opens in new window
Automatising the publication of CEUR-WS.org workshop proceedings Data Management Plan NWO (September 2020) Vrije Universiteit Amsterdam Ilaria Tiddi (new window) Opens in new window
The role of heterogeneity in controlling the geomechanical behaviour of sandstone reservoirs Data Management Plan NWO (September 2020) Other Johannes Miocic (new window) Opens in new window
Spatio-temporal canards and delayed bifurcations in continuous neurobiological networks Data Management Plan NWO (September 2020) Vrije Universiteit Amsterdam Daniele Avitabile (new window) Opens in new window
Vector valued Orthogonal Polynomials and Multiplicity Free Induction: Deformations and Quantizations Data Management Plan NWO (September 2020) Radboud University Erik Koelink (new window) Opens in new window
Quantification of meltwater storage in Greenland using a statistically-optimal estimation of mass anomalies with satellite gravimetry data Data Management Plan NWO (September 2020) Delft University of Technology Pavel Ditmar (new window) Opens in new window