RDNL focuses primarily on research facilitators by supporting them in their work for researchers, data managers, universities and institutes. We do this using the front-office/back-office structure that has been chosen as the implementation mechanism of the federated data infrastructure in the Netherlands. | RDNL, n.d.
This section focuses on the front office - back office model (FOBO) of Research Data Netherlands. FOBO is a way of organising RDM services.
The importance of different roles
Data sharing is becoming increasingly important in science. Increasingly, funders are demanding that the data from publicly funded research be stored in data archives in a freely accessible and sustainable manner. Good and timely data management and the safe storage of data, both during and after the conclusion of the research, are an essential condition for the sharing of this data. Universities and universities of applied sciences have a clear role in formulating policy with regard to data management within their organisation. Good support for researchers and an adequate technical infrastructure are indispensable for the implementation of data policies. The increase in scale of the deposit of research data prompted Research Data Netherlands to create a model in which stakeholders organise themselves into front offices and back offices, the so-called front office - back office model (FOBO) of Research Data Netherlands (RDNL, n.d.).
The underlying idea is as follows: Each stakeholder provides services that fit their specific mission. At the back office of RDNL partners DANS and 4TU.Centre for Research Data that is the sustainable archiving of research data. SURF additionally offers services and tools for during the research.
The front offices are in direct contact with researchers. For example, university libraries (together with IT services) can form a front office. The front office employee is the link between the customer and the back office. For researchers, this means a single point of entry for questions about data management and archiving.
Organisations differ in their field of expertise, size and type of research data, personnel capacity, ambition, etc. These differences can lead to a different structure. There will be institutions with only front office tasks that will outsource the back office tasks to a data archive such as 4TU.Centre for Research Data or DANS. But there will also be organisations with both front office and back office tasks. For example, some institutions have different types of data stewards. Some of them deal with general data management issues and others work in the faculty, in a discipline-specific manner. Here, too, you could speak of a back office and front office, in this case within an organisation.
|Front office tasks||Back office tasks (RDNL-partners)|
|Maintaining and linking contacts||Innovation in permanent storage, data management and reuse of research data (such as developing a data policy, R&D activities)|
|Training researchers||Providing expertise to front office employees and researchers (e.g. by contributing to the development of training materials)|
|Referring to and cooperating with the back office||Long-term storage of research data in a trusted digital repository (CoreTrustSeal)|
|Supporting data storage during the research phase in virtual research environments|
The main purpose of the distinction between front office and back office is 'not to invent the wheel twice'. It isn't efficient if all organisations start a back office on their own. Instead, they can make use of the experiences and services that already exist. Good coordination between researchers, institutions, publishers, funders, etc. can create the necessary conditions to manage the expected increase in scale in the sharing and archiving of research data. You can read more about the model in the RDNL brochure (RDNL, n.d.).
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DANS (2013). WUR kiest voor duurzame dataoplsag bij DANS en 3TU. https://dans.knaw.nl/nl/actueel/nieuws/wur-kiest-voor-duurzame-data-opslag-bij-dans-en-3tu
Jetten, M., Wittenberg, M. (2016). FO-BO-model van datacuratie in de praktijk RIS Radboud ondersteunt bij duurzaam archiveren. E-DATA & RESEARCH juni 2016, p 3. https://dans.knaw.nl/nl/actueel/nieuws/EdataResearchjuni2016webversie.pdf
RDNL (n.d.) Research Data Netherlands. A federated data infrastructure for the Netherlands: the front-office – back-office model [Folder]. https://researchdata.nl/fileadmin/content/RDNL_algemeen/Documenten/RDNL_FOBOmodel-UK-web.pdf
Wageningen University & Research (2013). Data-archiving: a double interview. https://www.wur.nl/en/show/Dataarchivingdoubleinterview.htm