Open Science

Life cycle and taskforce

Radboud University and our research institute (Radboudumc Research Institute for Medical Innovation) see Open Science as the norm in 2030.

This means much more than publishing all papers in Open Access journals. Open Science is about increasing impact in the scientific and societal domains by sharing research materials and codes, making data available for reuse, enhancing reproducibility of research, and involving all relevant stakeholders, including citizen and patients. Our research institute's taskforce (the Open Science Taskforce) is there to stimulate the cultural, policy and professional changes to roll out Open Science in its fullest scope.

The entire research cycle can be open. The taskforce focuses on four domains:

• Open Access
• Open and FAIR data
• Citizen Science and Public Engagement
• Reproducibility

(image designed by Radboudumc's Jaisson Cenci)

Open Access

Open Access of publications provides direct, free and online access to scientific publications without copyright restrictions of publishers. Open Access significantly increases the visibility of a publication.

Radboudumc endorses the principles of Open Access and monitors the percentage of articles that are published in Open Access.

The Radboud University Library supports Radboudumc researchers in publishing their research articles Open Access, including financial deals with scientific journals, making the publication available free of charge via the Radboud Repository and the publication services of Radboud University Press. Advice is also given on Open Access licensing an dhow to avoid publishers of dubious quality. Visit the website of the Radboud University for all available support concerning the Open Access. Curious on how and where you can publish your research? Please visit this page.

Additional information can be found on the general website on Open Access.

FAIR data and open data

Making your data available for other researchers increases the visibility of your scientific achievements and allows your data to have an impact beyond your research project and publications. The FAIR (acronym for Findable, Accessible, Interoperable and Reusable) principles help to make your data ready for reuse. However, FAIR data is not always open data.

All data should be FAIR, some data can be open

Data that contains privacy-sensitive or confidential information cannot be published open access. Often sensitive data can be shared with restricted access, allowing reuse after signing a data use agreement (DUA) stating the terms and conditions under which the data can be used. Other solutions for sharing sensitive data include anonymization, data aggregation or data visiting. Data that are not sensitive nor confidential should always be published open access to enable reuse. The Radboud Data Repository (RDR) is our preferred general data repository. For certain research domains, there are alternative repositories in use.

Which data should be shared?

At Radboud University and Radboudumc, all data underlying published scientific manuscripts authored by Radboud affiliated researchers should at least be Findable and Accessible (F And A of FAIR), with programs like Radboud HealthyData supporting interoperability aspects.

The shared dataset should be also useful for other researchers. Especially datasets that were costly or time-consuming to create, were not used to their fullest potential yet (big data), or were derived from a unique population, are valuable for reuse.

How to make 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 the data can be accessed, possibly including authentication and authorization.
• Interoperable: The data usually needs to be integrated with other data. In addition, the data needs to interoperate with applications or workflows for analysis, storage, and processing.
• Reusable: To be able to reuse the data, metadata and data should be well-described so that they can be replicated and/or combined in different settings.

More information on the FAIR principles and how to apply them:

• GO-FAIR
• 'The Metroline' - steps for your FAIRification workflow

Questions about FAIR and data publishing?

See RTC Data stewardship and/or contact their data stewards.

Citizen Science and public engagement

Citizen Science refers to the participation of lay people or non-professional scientists in scientific research. Their participation can take place in various fields, on different levels and in different research phases.

Citizen science in the fields of ecology, biodiversity, astronomy, and climate science often entail data collection activities through environmental monitoring. That is, volunteers are asked to record local wildlife sightings (e.g. De Nationale Tuinvogeltelling), track changes in air quality or weather patterns (e.g. Curieuze Neuzen), or classify galaxies from telescope images (e.g. Galaxy Zoo).

The rise of the internet and mobile technology enables people to participate in scientific projects from around the world, making it easier to contribute from anywhere. This involvement allows large-scale data collection that might be otherwise difficult or expensive to achieve.

Although monitoring activities are present in fields such as medicine, health, and social sciences (e.g., through eHealth apps), ‘citizen science for health’ can extend beyond simple data collection. In these areas, lay people may also engage with professional scientists in activities like formulating research questions, designing appropriate recruitment and data collection methods, gathering information, conducting experiments, analyzing data, and helping to disseminate findings in ways that effectively reach the wider public.

This active engagement enables citizen scientists to contribute to multiple stages of the research process, facilitating a more inclusive and comprehensive approach to scientific inquiry. The benefits of citizen science include their empowerment, increased scientific literacy among participants, and community engagement. It also democratizes science by making it accessible to a broader population.

It is advised to work according to the 10 principles of citizen science.

Reproducibility

Replicability and reproducibility are increasingly recognized as essential to scientific progress and integrity.

Open science practices play an essential role in supporting these concepts. Replicability (or the extent to which the design, implementation, analysis, and reporting of a study enable a third party to repeat the study and assess its findings), is highly dependent on the openness of, for example, research protocols, methods and data. We cannot replicate research if we have insufficient information about the original study.

Openness in science is therefore a vital driver of replicability. Replication, in turn, allows for an assessment of reproducibility, (or the extent to which the results of the original study agree with those of replication studies - see the figure below). In the end, reproducibility increases our confidence in research findings and promotes the credibility and reliability of science, and open science practices are essential to achieve this goal.

More information about ongoing EU projects on reproducibility can be found on:

• iRISE
• TIER2
• OSIRIS