Our expertise, built up in national and European projects, is reflected in the following expert services of DANS, intended for researchers, research institutions, research funders, data professionals and other archives, to help with (background information about) the sustainable storage and sharing of data.
FAIR and Open data
Research funders require that your data are maximally available and suitable for reuse and reproduction of research. In other words: data must be Findable, Accessible, Interoperable and Reusable (FAIR).
The data experts at DANS know what FAIR means in various disciplines and can help you to make and keep research data FAIR. This is how we make research and researchers more visible together.
Research Data Management
Where do you store data during and after your research, who is allowed to access it and when, and what are you going to document and archive? In a data management plan (DMP), you describe these and other steps to efficiently and safely manage all versions of your data.
DANS does not require a DMP, but is glad to help you plan the subsequent archiving in time. We are pleased to share DANS’ experience in writing and reviewing DMPs for international projects and research financiers.
Certification of digital archives
DANS helps heritage institutions that want to start with the certification of their digital archive. Together with the Dutch Digital Heritage Network (NDE), a guide for the certification of digital archives was developed (Wegwijzer Certificering). DANS manages the Dutch website with information on setting up and performing a certification procedure.
The knowledge and experience that DANS has in the area of certification for digital archives is also shared in webinars, training courses and projects.
Monitoring and analysis
DANS collects, analyses and presents quantitative information on data repositories, FAIR data practices and the state of Open Science in the Netherlands. Comparisons are also made with other countries. This knowledge is shared through reports, seminars and workshops.
DANS actively seeks cooperation with external experts and offers the possibility of a DANS fellowship. This is a long-term collaboration related to a concrete project in the field of long-term archiving. New knowledge from this programme is shared through events such as webinars and presentations.
Together with others
DANS participates in national and international projects and infrastructures. Together with our collaborating partners, we contribute to sustainable access to research data.
Training and Outreach
We are happy to share our knowledge with researchers, data professionals, research institutions, research funders and other repositories. We regularly organise interactive workshops on data publishing, archiving, reusability and interoperability. The developments in the field of Open Science, research data management planning and tools are also addressed.
In addition, DANS organises successful interactive training courses together with others, such as: RDNL Essentials 4 Data Support, RDNL AVG and develops training materials such as the DANS Data Game and CESSDA Data Management Expert Guide.
With consultancy and project-based support, DANS helps to improve permanent access to digital research data. Our data experts have extensive experience within various scientific disciplines and have advised parties such as Erasmus University Rotterdam, NWO and the European Commission and Science Europe.
We offer advice and support on: embedding data management more firmly within your organisation, the rules and developments regarding Open Access and the sharing of research data, assistance in implementing and assessing data management plans, tools to assess the FAIRness or reusability of data and obtaining a CoreTrustSeal certificate.
DANS shares expertise and experience in the form of practical tools and resources, such as FAIR-Aware and Text Fabric.
Text Fabric: file format, data model, API and apps for processing texts and related annotations. It is used for some significant (old) tekst corpora for which Jupyter notebook tutorials are available.
FAIR-Aware was developed by DANS under the umbrella of the FAIRsFAIR project. It helps researchers to become more aware of the FAIR data principles and learn how they can increase the quality of their datasets by applying them.