Front office - Back office Model

"It is important to recognize the current uncertainty as to how data management support and services will be distributed among university, disciplinary, funder, national and international stakeholders. In this complex environment, an institution must actively determine how data services will be managed and distributed internally."  - OCLC(1)

    Main points

This section discusses the Research Data Netherlands 'front office - back office model' as a way to organise research data services.

Sharing data is becoming increasingly important in science. More and more, financiers demand that publically funded research is freely accessible and durably stored in data archives. Up until now, data archives mostly did business with individual researchers, but with the expected scale increase of depositing research data, DANS and 4TU.Centre for Research Data believe the time is ripe for adjusting this model and organising the stakeholders in front offices and back offices. Every stakeholder provides services that connect to their specific mission. In the case of data archives such as DANS and 4TU.Centre for Research Data, this mission is the durable storage of research data.

The first point of contact for researchers is the institute that the researcher is affiliated with. For example, several university libraries (together with their IT departments) can be a front office. The front office employee is the link between the client and the back office. For researchers, this means a single point of entry for questions regarding data management and archiving. It is a first signpost close to home.

Front office tasks Back office tasks
Maintaining and linking contacts Innovation in permanent storage, data management en reuse of research data (such ad 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 (Data Seal of Approval)
Data-acquisition
Supporting data storage during the research phase in collaboration environments (datalabs)

 

Organisations differ in disciplines, size and type of research data, staff capacity, ambition, etc. These differences can lead to completely different layouts. Some institutes will have only a front office and purchase their back office needs from a data archive such as 4TU.Centre for Research Data or DANS. Other institutes will have both a front and a back office.

The most important goal of the front office - back office distinction is to ‘not invent the wheel twice’. To make sure that everyone doesn’t start up their own back office but uses the experience and expertise already available. The activities of researchers, institutes, publishers, financiers, etc. must be finely attuned to create the necessary conditions for streamlining the expected scale increase in sharing and archiving research data.

This illustration is taken from the flyer from Research Data Netherlands on the Frontoffice - Backoffice model.(2)

   Sources

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Sources

  1. Erway, R. (2013). Starting the Conversation: University-wide Research Data Management Policy. OCLC Research. Retrieved from http://www.oclc.org/content/dam/research/publications/library/2013/2013-08.pdf
  2. Research Data Netherlands. A federated data infrastructure for The Netherlands:the front-office - back-office model. [folder]. Retrieved from https://researchdata.nl/fileadmin/content/RDNL_algemeen/Documenten/RDNL_FOBOmodel-UK-web.pdf

    Your additions

How is data support managed within your organisation? When looking at your role as a data supporter, do you have (or are you expecting) predominantly front office or back office tasks? What tasks do you prefer? Leave all your remarks on this subject in the comments.


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