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Peter Wittenburg



e-Infrastructure Group

This group will focus on the interaction and involvement of the big data and computing centres in the FDO related work. These big data centres have an even more important role in the future since they need to take care of persistent services that go beyond their traditional business in providing basic networking, storage and computing services. If FDO wants to be accepted, they need to support essential registries of all sorts (PIDs, Types, Assertions, etc.) in a persistent and 24/7 availability mode.

The FDO-eING will thus start working on a variety of testbeds and reference architectures together with eInfrastructure providers to demonstrate the viability of the FDO concept. It will do this in collaboration with the FDO BIG group which will focus on establishing a stable service landscape.

The FDO-eING group will discuss the following items

  • discuss the FDO concept in detail and its requirements with respect to persistent services
  • development of suitable testbeds to fully understand the operational aspects of FDOs and to demonstrate the viability of the FDO concept
  • help in specifying requirements for the needed infrastructure services

To achieve this goal, it will organise workshops together with organisations such as eIRG, XSEEDE, etc.

It should be noted that members of this group are already active in building a first limited testbed to establish a functioning DOIP based infrastructure which includes a few repositories and first clients relevant for researchers


The group is co-chaired by Peter Wittenburg. For requests/comments send an email to

Latest group news

Call for papers

Call for Papers on Canonical Workflow Frameworks for Research

Data Intelligence is seeking papers for a special issue devoted to Canonical Workflow Frameworks for Research. Deadline for abstract submissions: March 14, 2021.

The journal is seeking papers describing practical experience on the design and deployment of effective workflows, supporting major phases of the research data lifecycle; especially those phases surrounding (either side of) the core activities of experimentation, data processing and analysis i.e., those phases concerned with hypothesis and investigation planning, data management planning, organization and operation, reproducibility planning, provenance recording, and data curation and publication in successive steps.

More details can be found on the OSF CWFR page.