Improved data management for more productive, transparent research
The project SIM4RDM (Support infrastructure models for research data management) promoted and facilitated the sharing of research data through use of public data systems. The six-member consortium worked to create mechanisms for good data storage and management – critical to productive research, and for generating economic and scientific progress and also preserving it for future generations. SIM4RDM analysed existing funding programme interventions within EU Member States and abroad, examining current RDM practices and aspirations. The team produced models, evaluation frameworks, and proposals for future national interventions, as well as pan-European and international coordination. Research resulted in a landscape report of European RDM practices and specific recommendations for funding organisations, national bodies, research institutions, infrastructure providers, and publishers. Targeting participation in an international data sharing system, the work supports improved data management practices and coordination of RDM interventions for each stakeholder group. To address the complex RDM landscape, partners devised a so-called core-plugin model The core element focused on a set of RDM issues likely to be encountered across Europe, and plug-ins covered medium and more advanced RDM issues that vary across countries and stakeholder groups. Five RDM areas were identified as critical: organisational, legal, technical, user experience and data reuse. Workshops were organised to validate and refine work on the project's funding and evaluation frameworks. Partners also conducted case studies for France, Hungary, the Netherlands and Nordic countries to test and improve these frameworks. The case study reports are available online. The project's main output is the Intervention Framework. This can be used by the various RDM actors to assess the current maturity of RDM practice and determine ideal maturity. It also includes a list of possible actions to take, including joint actions with other actors. Project work has helped to build the required skills and capacity for researchers to optimise the use of technical advances in both large and small scale data infrastructures. SIM4RDM outcomes thus contribute to making research more transparent through more easily verified and publicly accessible research data.
Keywords
Research data management, data infrastructures, researchers, SIM4RDM
