Digital methods and collaborative research in virtual research environments are gaining in importance for the arts and humanities. The EU-funded project DARIAH aims to enhance and support digitally-enabled research across these disciplines.The most basic but nevertheless fundamental task of DARIAH is to provide sustainable storage for research data. Information contained in data like images, texts or music needs to be secured and to remain accessible even if the original information carrier becomes lost or corrupted. The heterogeneity of the humanistic data and the need for distributed, performant access are the main challenges in designing an archiving system for the arts and humanities.Using the "Virtual Scriptorium", a digitisation project in Trier, Germany, this paper exemplary identifies the humanistic researchers' storage needs and derives requirements for an infrastructure. As a solution, a generic architecture for a federated data zone based on the iRODS technologies is proposed. The system implemented in Trier and Karlsruhe is described and will be extended to other locations as the researchers benefit from the initial set-up.
This article focuses on measuring, describing, monitoring and publishing the quality and performance of grid resources. Life science communities can employ Service Level Agreements (SLAs) with their resource providers to ensure the delivery of services. For this, it is important for both the life science communities and their providers to understand and quantify the performance and service quality of different grid environments. However, measuring service quality in grid infrastructures utilizing different middlewares, as in the German Grid Initiative, is a complex problem. We describe the state of quality metrics which are currently used by the German life science communities MediGRID, Services@MediGRID and PneumoGrid. We also identify further quality metrics for defining and monitoring grid resource quality in D-Grid. It is important to publish and exchange the quality information by grid information systems, which are the entry points to grid services. Therefore, we also present how quality information can be handled by the GLUE v2.0 Schema, which is the upcoming standard data model used by grid information systems. For measuring and monitoring the quality metrics in multi-middleware environments two approaches are discussed. The first approach extracts quality information from an external benchmarking system and loads it to the grid information systems. The second solution targets life science communities that do not utilize legacy benchmarking systems, but operate traditional monitoring systems, like Nagios.
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