e!DAL - a framework to store, share and publish research data
The life-science community faces a major challenge in handling big data, highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, analysis, and publication are the three pillars in the big data life cycle. The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall.
data publication research data management persistent identifier metadata annotation shared repositories java api