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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 tasksBack office tasks
Maintaining and linking contactsInnovation in permanent storage, data management en reuse of research data (such ad developing a data policy, R&D activities)
Training researchersProviding 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.

    Case

The 'Zandmotor'

The Zandmotor(2) (The Sand Motor) is a man-made peninsula on the Dutch coast, near Ter Heijde. Here, scientists research whether this project can urge nature to spread sand along our coast. The project is a collaboration between researchers of the TU Delft(3) (department of civil engineering and geosciences) and STW Nature Coast Teams(4) and is being led by the Dutch Directorate-General for Public Works and Water Management (Rijkswaterstaat(5)).

The research data of this project is stored and sharedhttp://researchdata.4tu.nl/over-4turesearchdata/nieuws/nieuwsbericht/?tx_ttnews[tt_news]=154&cHash=3bace40dee489c4338a445efbab1e0c8(6) in an OpenEarth(7) data lab. This data lab was developed by the research community itself, by Deltares researchers. Deltares(8) is an independent institute of applied knowledge in the fields of water, subterranean and infrastructure.

The department of civil engineering and geosciences has made a helpdesk available to the researchers who are going to work with the data lab. Deltares is training a number of students in handling the data types en data formats used in the OpenEarth data lab. 4TU.Centre for Research Data provides the infrastructure, development capacity and security. It transfers the data to 4TU.Centre for Research Data when the articles are published and when the project is finished.

The illustration is a worked-out example of an illustration from a Research Data Netherlands brochure on the Front office - Back office model.(9)

   Sources 

Click to open/close

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. De Zandmotor. Retrieved from http://www.dezandmotor.nl/en
  3. TU Delft. Hydraulic Engineering. Retrieved from http://www.citg.tudelft.nl/en/about-faculty/departments/department-of-hydraulic-engineering/sections/coastal-engineering/research/nemo/
  4. STW. Nature-drive nourishment of coastal systems (NatureCoast). Retrieved from stw.nl/nl/programmas/nature-driven-nourishment-coastal-systems-naturecoast
  5. Rijkswaterstaat. Zandmotor: pilotproject voor natuurlijke kustbescherming. Retrieved from http://www.rijkswaterstaat.nl/water/waterbeheer/bescherming-tegen-het-water/maatregelen-om-overstromingen-te-voorkomen/zandmotor/index.aspx
  6. 3TU.Datacentrum. (2014, April 9). Sand Motor Monitor data lab live. [news]. Retrieved from http://researchdata.4tu.nl/en/about-4turesearchdata/news/news-item/?tx_ttnews[tt_news]=154&cHash=997ad0a2f7f07c1bc155af09688bc669
  7. OpenEarth. Retrieved from http://publicwiki.deltares.nl/display/OET/OpenEarth
  8. Deltares. Retrieved from http://www.deltares.nl/en
  9. Research Data Netherlands. A federated data infrastructure for The Netherlands:the front-office - back-office model. [folder]. Retrieved from http://www.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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Eric Rumondor - Bij de TU Delft vermoed ik dat de frontoffice-taken en backoffice-taken even belangrijk zijn. Mijn eigen voorkeur gaat naar de backoffice-taken, en ik realiseer me dat een goede samenwerking met de frontoffice heel belangrijk is.

2 years 9 months ago · 
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Rick Vermunt - Binnen de VU zijn datasupport, net als data management en data vaardigheden nog in ontwikkeling. Momenteel wordt infrastructuur ingericht.

2 years 8 months ago · 
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Marjo Bakker - Bij het NIOD is de researchdata support als vanzelf volgens het front- en backoffice georganiseerd. Als datasupporter bij het NIOD zit ik dus in de frontoffice, DANS is onze backoffice. Lijkt mij een prima opzet. Ik vind alle bovengenoemde taken van de frontoffice leuk om te doen, hoewel ik echt training geven nog niet gedaan heb. Tot nu toe ligt dat meer in individuele uitleg.

2 years 3 months ago · 
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Annemiek Ouwerkerk - Bij de Universitaire Bibliotheken Leiden is een duidelijke frontoffice situatie. Er zijn twee gekwalificeerde datalibrarians, er is een loket, er wordt samengewerkt met vertegenwoordigers van de verschillende faculteiten. Er is uitgebreide informatie op de website. Zie: http://www.bibliotheek.leidenuniv.nl/doceren-onderzoeken-publiceren/publiceren-en-opslaan-van-onderzoek/data-management/
Er worden trainingen voor onderzoekers gegeven, waarover ook een blog is. Zie: http://blogs.library.leiden.edu/researchdata/

1 year 4 months ago · 
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