About

We support from three core pillars: research data management, research tooling, and research infrastructure. Our training, advice and expertise guides researchers through all four phases of the Research Data Lifecycle.


Contact

dr. Bart Oosterholt
RTC coordinator

You can visit our weekly consultation hour, on Mondays 13.00 - 14.00 on route 114.

Contact our team:
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Expertises and services


Let us enhance your research

A quick overview of our training offerings, policy & guidance documents, data management support, supported tools, and available infrastructure, to support your research data.

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Let us enhance your research

We support researchers by providing training, advice and expertise from our three core pillars: I. research data management, II. research tooling, and III. research infrastructure. Doing so, we guide researchers through all four phases of the Research Data Lifecycle.



Research Data Lifecycle and its four phases

Your research data typically undergoes four phases: planning & design, collect & create, store & analyze, and archive & share. These are all equally important to maximize scientific impact.

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Our three core pillars

  • Training, Data Management Plan (DMP) review and support for management of your data.

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    I. Research data management

    Training, Data Management Plan (DMP) review and support for management of your research data. 

    We provide support for individual researchers, departments and consortia in all four phases of the Research Data Lifecycle.

    FAIR Research Data Management

    • Explore the four phases of the Research Data Lifecycle.
    • Follow our FAIR RDM course to get a head start in the FAIR RDM terminology, tools and regulation.
    • Contact our data stewards (see the general contact button on the RTC DS main webpage) for support and advice on tailored RDM solutions that are compliant with the Radboudumc policy.

    Data management plans (DMP)

    • DMPs are mandatory for PhDs, required by most funders and necessary to acquire local feasibility approval.
    • To get started, follow the DMP training.
    • Make sure to select the Radboudumc template in DMPonline (intranet) for NWO and ZonMW funded studies and for local feasibility applications.
    • Make use of the example texts for data management paragraph in PhD theses or EU funded studies.
    • Ask for advice or have your DMP reviewed by our data stewards (you can contact them via the general contact button on the RTC DS main webpage).

Impact


Our impact

We collaborate with internal and external partners to share knowledge and develop new solutions and platforms for research data management.

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Our impact

We collaborate with internal and external partners to share knowledge and develop new solutions and platforms for research data management.

Many researchers recognize the importance of research data management and the FAIR principles, however, applying them is often difficult and time-consuming. We aim to address this by:

  • Providing clear guidelines and instructions;
  • Developing secure & intuitive tools and infrastructure;
  • Sharing knowledge and connecting experts.

Policy and guidelines

Throughout the Research Data Lifecycle, policy and guidelines apply. These are available on Radboudumc's Qportal and IQS. Consult these before start.

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Policy and guidelines

Throughout the Research Data Lifecycle, policy and guidelines apply. These documents are available on Qportal and IQS. Read them before you start your project.

Policies and guidelines on Qportal

Example text for Data Management Plan (DMP)

Use the DMPonline tool to prepare your DMP and make use of the guidelines and example answers for each topic. Make sure to use the Radboudumc template, also when preparing a DMP for funders such as ZonMW and NWO.

FAIR manual on Qportal

Making your data FAIR is a challenging task. For researchers it is difficult to decide where to start and what choices to make in the process. To help researchers, Health-RI have written a FAIR manual that guides you step-by-step to apply the FAIR principles to research data. Click here to access it.


Health-RI

We actively participate in Health-RI, the Dutch organization which stands for better re-use of health data for research, policy and innovation.

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Open Science

Open Science is about free access to scientific knowledge, data and methods throughout a research project, increasing cooperation, transparency and reproducibility of research.

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Open Science

Open Science is about free access to scientific knowledge, data and methods throughout a research project, increasing cooperation, transparency and reproducibility of research.

Three important aspects of Open Science are:

  1. Pre-registration of your research project, allows you to claim your ideas in an early stage, and increases the credibility of your results. Many journals (>300) also use the Registered reports publishing format: methods and proposed analyses are pre-registered and peer-reviewed prior to research being conducted. Manuscripts that survive pre-study peer review receive an in-principle acceptance that will not be revoked based on the outcomes, but only on failings of quality assurance, following through on the registered protocol, or unresolvable problems in reporting clarity or style.
  2. Open access to methods for data collection and analysis. This makes your results more reproducible, enhancing the value of your findings. Moreover, other researchers can credit your work when they reuse your methods and procedures.
  3. Open access to research data so that others can verify your results, and reuse your data.

More information by Radboud University and partners

For more information on Open Science, contact the experts at the RU Library, or visit the following websites:


FAIR principles

The FAIR principles help to make your data have impact beyond your research project and publications, and increase the visibility of your scientific achievements.

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FAIR principles

The FAIR principles help to make your data have impact beyond your research project and publications, and increase the visibility of your scientific achievements.

Making data FAIR

FAIR is an acronym for ‘Findable’, ‘Accessible’, ‘Interoperable’ and ‘Reusable’.

  • Findable: The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process.
  • Accessible: Once the user finds the required data, they need to know how can the data be accessed, possibly including authentication and authorization.
  • Interoperable: The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.
  • Reusable: The ultimate goal of FAIR is to optimize the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.

More information by Radboud University

The Radboud University has established the following minimum requirements concerning data "FAIRness": 'Research data underlying scientific publications authored by Radboud University or Radboudumc employees should be Findable and Accessible.'

The FAIR guidelines are known to many researchers but are not yet universally applied in practice. We at Radboudumc are obliged to have all research data comply at least with the F (sustainably findable) and the A (proper access management). Read more on the website of the Radboud University.

Organization and people


Getting here

Entrance: Business center
Route: 237

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Getting here

Visiting address

Business center
FC Donderslaan 2
6525 GJ Nijmegen

Directions

Enter building at: Business center
Follow route 237

Our experts

The Data Stewardship team consists of nine members, all experts in the field of research data management.