RDM @ UHasselt

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What is RDM? Why RDM? UHasselt RDM policy Funder requirements Horizon Europe proposals

What is RDM?

Research Data Management (RDM) refers to the way research data are managed throughout a research project: where do you store your data, how do you secure them, how do you analyze them, how do you document and organize them, etc. It also includes archiving your scientifically valuable data in a sustainable way after the research project is finished, and preferably making them available to the public. The best way of managing your data is making your data FAIR (findable, accessible, interoperable and reusable).

Why should RDM be important to you?

Research efficiency

Apply a clear structure to your folders, use logical file names, use version control and provide elaborate documentation for your project. Store your data in a secure location and create back-ups regularly. These are important data management practices that will help you to stay on top of your research and prevent risk of data loss. At Hasselt University, you can use the institutional Google shared drive to organize and store your data.

Scientific integrity

Besides an efficient organization and documentation of your project, thorough data management means that you implement data quality assurance processes. Share this information alongside your data so that your research findings can be validated and reproduced, leading to more transparent research. At the same time, be aware of sensitive data that should be shared with restrictions, or cannot be shared at all. Reflecting on possible ethical and legal issues, and handling them in an appropriate manner (e.g. data security), is also an essential aspect of data management.

Visibility and impact

Your research becomes more visible when you upload your (meta)data in a (meta)data repository, which can lead to more citations and opportunities for collaboration. At Hasselt university, it is recommended to deposit your metadata in the UHasselt metadata repository. These records will appear on your researcher profile together with your publications.

Institutional and funder requirements

Open Science has become a priority for the Flemish research institutes and funders. As a researcher, you should be aware of existing rules and guidelines:

UHasselt RDM policy

The Hasselt University RDM Policy Plan (pdf, 184 KB) sets a framework for all researchers to safeguard the quality, availability, and accessibility of their research data and it provides a basis for evaluating compliance with laws and regulations (e.g. GDPR) and codes of conduct. The Hasselt University RDM Policy Plan defines the responsibilities of all researchers affiliated with Hasselt University through five basic principles:

  1. All researchers must store, manage and provide access to their research data as stipulated in the RDM Policy Plan and adhere to its guidelines;
  2. Personal and sensitive data can only be collected and used when essential for specific research;
  3. All research projects require a data management plan (DMP);
  4. Researchers adhere to the Acceptable Use Policy (AUP) and Identity and Access Management (IAM).
  5. The RDM Policy Plan complements existing legislation, regulations, research ethics, and integrity guidelines.

Hasselt University has the responsibility to support its researchers, ranging from providing tools and secure data storage infrastructure to providing support and training on data management planning and expert advice on personal data processing. The researchers themselves are responsible for ensuring that their data management is in line with the RDM policy.

Funder requirements for data management and open data

Based on KU Leuven RDM website

In general, research funders require and/or recommend:

  • That you develop a data management plan at the start and implement it during the research project.
  • That you preserve the data for a certain period after the end of the research project.
  • That you publish the data and make them available in a (trusted) data repository.

Overview of funder research data requirements from proposal to end of project

Funder

Proposal

Initial DMP

(month 6)

Final DMP

(end of project)

Data preservation

Data publishing

FWO

5 RDM questions in application form

Submit to rdm@uhasselt.be

Submit to FWO

5 years

Advice: data linked to publications

BOF/IOF

5 RDM questions in application form

Submit to rdm@uhasselt.be

Submit to rdm@uhasselt.be

5 years

Advice: data linked to publications

VLAIO-cSBO

5 RDM questions

Submit to rdm@uhasselt.be

Submit to rdm@uhasselt.be

5 years

BELSPO

5 RDM questions (provisional DMP) in grant application

Submit to BELSPO

Submit to BELSPO

Long-term in repository

All data and metadata in certified and trusted repository, as open as possible

Horizon Europe

RDM for FAIR data and Open Science practices

Submit to EC portal

Submit to EC portal

Long-term in repository

All data and metadata in certified and trusted repository, as open as possible

For FWO and BOF-IOF: UHasselt guide for the FWO/BOF application DMP

Open Science and Research Data Management for Horizon Europe proposals

For Horizon Europe programmes, Open Science is a priority, focusing on freely sharing research results without barriers or pay-walls. Open Science and Research Output Management (including data) are addressed most prominently in the Horizon Europe Programme Standard Application Form, Project Proposal – Technical Description (Part B), Excellence – Methodology (section 1.2). Besides, best Open Science practices can likewise be included in Project Proposal – Technical Description (Part B), Quality and Efficiency of the Implementation – Capacity of Participants and Consortium as a Whole (section 3.2) and in Application Form (Part A), list of 5 top achievements.

When addressing Open Science and Research Data Management in section “Part B – 1.2”, the key take-away is to be as concrete and specific as possible. Proposers will have to demonstrate how they plan to comply with the mandatory Open Science practices (see below, 1-2). Failure to sufficiently address this, will result in a lower evaluation score. Conversely, a clear explanation of how they will adopt recommended practices (see below, 3), as appropriate for their projects, will result in a higher evaluation score. If proposers believe that none of the Open Science practices apply to their project, then they have to provide a justification. 

Mandatory Open Science practices: open access to publications and data
  • Reproducibility of research outputs

Reproducibility is the possibility for the scientific community to obtain the same results as the originators of the specific findings. It is important as it increases the performance of research and innovation, it limits waste of resources, it increases the quality and reliability of research, and, as a result, it may increase the trust of citizens in science.

In addition, Horizon Europe requires information via the repository about the research outputs, tools and instruments needed to validate the conclusions of scientific publications or to validate or re-use research data.

 

Measures to ensure reproducibility include, but are not limited to:

 

  • Open Access to scientific publications

Peer-reviewed publications must be open access by depositing the final version or peer-reviewed manuscript in a trusted repository at the latest at the time of publication. For journal articles, you should choose a CC BY or equivalent open licence. For publishing long texts, CC BY-NC/ND are also allowed. In addition, you should deposit in a trusted repository the research outputs, tools or instruments that are necessary to validate the publications’ conclusions. Metadata of deposited publications must be open under a CC0 licence, in line with the FAIR principles.

 

More information on open access to publications at Hasselt University

 

  • Open Access to research data

Research data should be deposited in a trusted repository as soon as possible after data production and at the latest by the end of the project. Beneficiaries have to ensure open access to research data generated in the project under the principle ‘as open as possible, as closed as necessary’. This means that data is open by default, unless there are legitimate reasons to (temporarily) restrict access to some or all research data. Such valid reasons may include, for example, the protection of personal information or valorisation potential. For research data, you should choose a CC BY, CC0 or equivalent open licence. Metadata of deposited datasets must be open under a CC0 licence, in line with the FAIR principles.

 

More information on sharing research data at Hasselt University

 

Mandatory Open Science practices: FAIR Research Data Management

In this separate methodological section (maximum one page), beneficiaries should outline how the research data (and other research outputs) will be managed responsibly in line with the FAIR principles (Findable, Accessible, Interoperable, Re-usable). At this stage, a full Data Management Plan is not yet required; this will only be a deliverable within six months after the actual start of the project.

In this section, the following topics related to Research Data Management should be addressed:

  • Description of the research data

Sound data management starts with identifying a complete and detailed list of all data you will collect, generate, and (re)use. You can elaborate on the origin of the research data (generating new data vs. re-using existing data), their materiality (digital vs. physical), their stage in the research project (raw vs. processed vs. analysed), the data collection method, their estimated size and technical file format.

 

More information on data description at Hasselt University

 

  • Measures to ensure the Findability of the research data

This means that data are discoverable via trusted repositories, have machine-readable metadata and a unique persistent identifier.

 

More information on FAIR data at Hasselt University

 

  • Measures to ensure the Accessibility of the research data

This does not necessarily mean that data are openly available, but the access protocol should be clear and preferably machine-readable.

 

More information on FAIR data at Hasselt University

 

  • Measures to ensure the Interoperability of the research data

Data and metadata are interoperable when they can be combined and exchanged with other (meta)data. You can, for example, use standardized and consistent language, as well as open file formats.

 

More information on FAIR data at Hasselt University

 

  • Measures to ensure the Reusability of the research data

Data are reusable when they are clearly structured, documented and provided with a data usage license.

 

More information on FAIR data at Hasselt University

 

  • Estimation of the curation and storage/preservation costs

Data management and sharing activities need to be costed into research, in terms of the time and resources needed. By planning early, costs can be significantly reduced. Costs associated with open access to research data, can be claimed as eligible costs of any Horizon Europe grant during the duration of the project under the conditions defined in the Grant Agreement: they must already be budgeted and accepted in the grant proposal, and note the “during the duration of the project”.

 

More information on budgeting for Research Data Management in Horizon Europe

 

In order to attest to the compliance of your research data to these FAIR principles, you can use an intuitive assessment grid developed by the international Research Data Alliance.

Recommended Open Science practices
  • Early and open sharing of research

This means making research work, methodologies, outputs, such as data and software, among others, and findings available as soon as possible in the research process. Examples include preregistration, registered reports and pre-prints.

More information on early and open sharing of research at Hasselt University

 

 

  • Open Access to other research outputs

Open access to other research outputs, such as software, workflows and others, will ensure that these outputs are freely accessible to all. This will promote transparency, efficiency and reproducibility, as well as trust in science, and will facilitate access for citizens.

In addition to publications and data, you can provide open access to, among others:

 

  • Participation in open peer review

Open peer review is an umbrella term for various alternative review methods that seek to make classical peer review more transparent and accountable. It has neither a standardized definition, nor an agreed schema of its features and implementations. In an open peer review process authors and reviewers are, for example, aware of each other’s identity. Or the review reports may be published alongside the corresponding article.

More information on open peer review at Hasselt University

 

 

  • Involvement of all relevant knowledge actors

Beneficiaries are encouraged to open up the research process to society to develop better, more innovative and more relevant outcomes, and to increase societal trust in science. Citizens, civil society and end-users may be included to participate as sources of ideas, knowledge and/or data, as data collectors and/or analysers, as testers and/or end-users.

More information on citizen science at Hasselt University

 

More information

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