Data management planning thinking in advance about what will happen to data produced during the research process is increasingly required by national research funding agencies, and data management guidelines for Horizon 2020 research projects were released by the EU in December 2013 (Guidelines on Data Management in Horizon 2020). Similar guidelines have been issued by the US Department of Energy (Statement on Digital Data Management), Australia (ANDS Data Management Plans) and across many other countries.The EUDAT project exists in part to disseminate and promote best practice in data management for twenty-first century research, and to provide support for communities in adopting basic principles such as data registration, metadata creation and data movement.As part of its mission to help researchers and research communities manage and preserve their data, EUDAT works with the world-recognised Digital Curation Centre on a version of their widely-used DMPonline tool which will capture the H2020 guidelines in a data management planning tool tailored to the emerging needs of European research.EUDAT's is building a Collaborative Data Infrastructure (CDI) as a pan-European solution to the challenge of data proliferation and associated management in Europe's scientific and research communities. The CDI will allow researchers to share data within and between communities and enable them to carry out their research effectively. Our mission is to provide a solution that will be affordable, trustworthy, robust, persistent, open and easy to use.

Facilitating open access to research data is a principle endorsed by an increasing number of countries and international organizations, and one of the priorities flagged in the European Commission's Horizon 2020 funding framework [1][2]. But what do researchers themselves think about it? How do they perceive the increasing demand for open access and what are they doing about it? What problems do they face, and what sort of help are they looking for?

In recent years significant investment has been made by the European Commission and European member states to create a pan-European e-Infrastructure supporting multiple research communities. In the data area, efforts are being driven by the EUDAT project, a pan-European data initiative that started in October 2011. The project brings together a unique consortium of 26 partners - including research communities, national data and high performance computing (HPC) centers, technology providers, and funding agencies - from 13 countries. EUDAT aims to build a sustainable cross-disciplinary and cross-national data infrastructure that provides a set of shared services for accessing and preserving research data, for large scientific communities, but also for small and medium size communities and even individual or "citizen" scientists. The B2Share service is one example of a service targeting this audience.

The EUDAT project is a pan-European data initiative that started in October 2011. The project brings together a unique consortium of 25 partners – including research communities, national data and high performance computing (HPC) centres, technology providers, and funding agencies – from 13 countries. EUDAT aims to build a sustainable cross-disciplinary and cross-national data infrastructure that provides a set of shared services for accessing and preserving research data.

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.

The EUDAT project is a pan-European data initiative that started in October 2011. The project brings together a unique consortium of 25 partners - including research communities, national data and high performance computing (HPC) centres, technology providers, and funding agencies - from 13 countries. EUDAT aims to build a sustainable cross-disciplinary and cross-national data infrastructure that provides a set of shared services for accessing and preserving research data. The design and deployment of these services is being coordinated by multi-disciplinary task forces comprising representatives from research communities and data centres. This short paper presents the achievements of the project during its first year and describes the services that have been chosen to meet the requirements of the initial research communities involved in the project.