About Research Data Management (RDM)
- Reusing health care data
- Data collection tools
- Data storage and management
- Work and compute environments
- RDM Courses
- RDM Procedures and templates
- Data management plan (DMP)
- Research software management
- Data archiving & publication
Careful research data management is an essential step in making research reproducible and is a responsibility of every researcher. Moreover, funding bodies and new legislation are placing increasingly high demands on research data management (also known as Data Stewardship). The research data management process should therefore be organized according to FAIR principles (Findable, Accessible, Interoperable, Reusable) and, where applicable, WMO and ICH-GCP (Good Clinical Practice) requirements. All of this is documented in a data management plan (DMP).
RDM can provide support during the entire research process, as shown in the Research roadmap Amsterdam UMC, including the preparation, data reuse and/or new data collection, and the data processing and analysis. RDM can also provide advice on ensuring that your study and results are findable when they are prepublished, published, or archived. The underlying data should be made available ‘as open as possible and as closed as necessary’ for verifiability and future reusability.
You can get free advice from RDM Consultants/Developers on a wide range of RDM-related topics. We offer DMP consultations and reviews, as well as providing intake sessions and support on using Epic for research. You can also contact us for advice on tools and procedures for data collection via an appropriate study database and have your study database reviewed. Moreover, there are tools for surveys and monitoring data flows, pseudonymization and anonymization, privacy aspects of RDM, and more.
Some tasks can also be outsourced at internal hourly rates, such as building a study database or web survey. In such case we always prepare a quote first. The RDM domain also organizes various training courses.