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Front office - Back office Model

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. 

Distinct tasks

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)
Data-acquisition  
Supporting data storage during the research phase in virtual research environments  

 

Collaborate efficiently

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.). 

In the spotlight


FOBO model in practice (Radboud University)

Copied and translated from Jetten en WiIttenberg (2016).

FOBO model of data curation in practice
RIS Radboud supports sustainable archiving

A team of data librarians supports researchers at Radboud University in Nijmegen in sustainably archiving and making their research data accessible via the institution's Current Research Information System (CRIS). 

Each researcher at Radboud University has a personal RIS page, where data can be registered and uploaded via the institution's Current Research Information System (CRIS). The full text of the corresponding publications can also be uploaded. The link between dataset and publication, including full text, becomes visible in the Radboud Repository.

Support by data librarian

Once the dataset has been uploaded by the researcher, the data librarian of Research Information Services (RIS) checks the metadata for clarity and comprehensibility. In addition, the data librarians check whether the data is sufficiently documented, do not contain any privacy-sensitive information and whether the files have the correct format. If everything is in order, the data librarian sends the dataset to DANS' online archiving system EASY. Via a SWORD interface, metadata and research data automatically end up in EASY. A DANS data manager performs a final check and publishes the dataset. Moreover, the dataset automatically receives a DOI. The data are now sustainably archived and accessible for reuse.

Collaboration between Front Office and Back Office

With this method Radboud University and DANS implement the Front Office-Back Office model (FOBO) of data curation. DANS fulfils the role of back office and is responsible for the sustainable archiving and provision of research data. The RIS of the Radboud University, operational since early 2016, is the front office, is in direct contact with the researcher and ensures that research data is well documented and prepared for reuse.

Integrity and quality of research

At Radboud University, the existing CRIS system, Metis, has been made suitable for the registration of the metadata of datasets as well as the upload of the data files themselves. As a result, researchers only need to use one interface to register information about their research, publications and data. In this way, data and publications can also be linked directly (in the CRIS). This solution not only facilitates the researcher, but also ensures that insight and control with regard to the integrity and quality of the research is possible at an organisational level. After all, all research data are registered in one primary CRIS system, which also functions as a source for the institutional repository.

FOBO model in practice (Wageningen University & Research)

The University Library of Wageningen University & Research collaborates with DANS and 4TU.Centre for Research Data in the transfer of research data from the institution to a data archive (DANS, 2013).

In a double interview with researcher Frits van Evert (Agrosystems Research) and library employee Annemarie Patist, it becomes clear how this works in practice (Wageningen University & Research, 2013): 

The E-depot does now have data sets, but they won't stay there! We are working on sustainably archiving datasets , accompanied by a 'read me file' and a 'methodology file' in national archives like DANS (Data Archiving and Network Services) and 3TU Datacenter Delft. The data has to remain available over the long term. That’s why the data are converted into sustainable formats before they are sent to the national archives. The formats are independent of specific versions of software. After the datasets are checked by DANS or 3TU Datacenter employees, they are published. The persistent link received from the archive centre is then the only thing that is stored in the E-depot.


Sources

Click to open/close

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