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Found 4 result(s)

B2SHARE

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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.

Phaidra Universität Wien

Permanent Hosting, Archiving and Indexing of Digital Resources and Assets

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Phaidra Universität Wien, is the innovative whole-university digital asset management system with long-term archiving functions, offers the possibility to archive valuable data university-wide with permanent security and systematic input, offering multilingual access using metadata (data about data), thus providing worldwide availability around the clock. As a constant data pool for administration, research and teaching, resources can be used flexibly, where continual citability allows the exact location and retrieval of prepared digital objects.

Edinburgh DataShare

DataShare

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Edinburgh DataShare is a digital repository of research data produced at the University of Edinburgh, hosted by the Research Data Service in Information Services. Edinburgh University researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.

B2SAFE

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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