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Abstract:
The wide variety of scientific user communities work with data since many years and thus have already a wide variety of
data infrastructures in production today. The aim of this paper is thus not to create one new general data architecture
that would fail to be adopted by each and any individual user community. Instead this contribution aims to design a
reference model with abstract entities that is able to federate existing concrete infrastructures under one umbrella. A
reference model is an abstract framework for understanding significant entities and relationships between them and
thus helps to understand existing data infrastructures when comparing them in terms of functionality, services, and
boundary conditions. A derived architecture from such a reference model then can be used to create a federated
architecture that builds on the existing infrastructures that could align to a major common vision. This common vision
is named as ’ScienceTube’ as part of this contribution that determines the high-level goal that the reference model
aims to support. This paper will describe how a well-focused use case around data replication and its related activities
in the EUDAT project aim to provide a first step towards this vision. Concrete stakeholder requirements arising from
scientific end users such as those of the European Strategy Forum on Research Infrastructure (ESFRI) projects underpin
this contribution with clear evidence that the EUDAT activities are bottom-up thus providing real solutions towards
the so often only described ’high-level big data challenges’. The followed federated approach taking advantage of
community and data centers (with large computational resources) further describes how data replication services
enable data-intensive computing of terabytes or even petabytes of data emerging from ESFRI projects.
