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The EUDAT project aims to contribute to the production of a Collaborative Data Infrastructure (CDI). The project´s target is to provide a pan-European solution to the challenge of data proliferation in Europe's scientific and research communities. The EUDAT vision is to support a Collaborative Data Infrastructure which will allow researchers to share data within and between communities and enable them to carry out their research effectively. EUDAT aims to provide a solution that will be affordable, trustworthy, robust, persistent and easy to use. EUDAT comprises 26 European partners, including data centres, technology providers, research communities and funding agencies from 13 countries. B2FIND is the EUDAT metadata service allowing users to discover what kind of data is stored through the B2SAFE and B2SHARE services which collect a large number of datasets from various disciplines. EUDAT will also harvest metadata from communities that have stable metadata providers to create a comprehensive joint catalogue to help researchers find interesting data objects and collections.
B2SHARE is a user-friendly, reliable and trustworthy way for researchers, scientific communities and citizen scientists to store and share small-scale research data from diverse contexts and disciplines. B2SHARE is able to add value to your research data via (domain tailored) metadata, and assigning citable Persistent Identifiers PIDs (Handles) to ensure long-lasting access and references. B2SHARE is one of the B2 services developed via EUDAT and long tail data deposits do not cost money. Special arrangements such as branding and special metadata elements can be made on request.
B2SAFE is a robust, safe and highly available service which allows community and departmental repositories to implement data management policies on their research data across multiple administrative domains in a trustworthy manner. A solution to: provide an abstraction layer which virtualizes large-scale data resources, guard against data loss in long-term archiving and preservation, optimize access for users from different regions, bring data closer to powerful computers for compute-intensive analysis