D4Science is a Hybrid Data Infrastructure combining over 500 software components and integrating data from more than 50 different data providers into a coherent and managed system of hardware, software, and data resources. The D4Science infrastructure drastically reduces the cost of ownership, maintenance, and operation thanks to the exploitation of gCube.
As an infrastructure, D4Science offers a rich array of services to its end users directly or to Infrastructure Managers and Service Providers.
Enabling to quantify the usage of the entire pool of resources hosted by the Infrastructure (e.g. storage space, CPUs). This service is offered by a user friendly web-based interface accessible via a web-browser. It helps administrators to define policies on the usage of the infrastructure.
Software Dynamic Deployment
Enabling to easily deploy and activate software bundles on hosting machines dynamically acquired from the infrastructure. The main benefits are reducing management costs, outsourcing the management to infrastructure facilites, benefitting from the capability to exploit distributed resources.
Enabling to check the operational state of services and hosting nodes deployed on the infrastructure, including alerts when the quality of service is not as expected. It is offered via a number of communication channels including web-based interfaces accessible via a plain web-browser and a messaging system.
Mastering Resource Lifecycle
Enabling to seamlessly manage services and hosting nodes operated by the infrastructure and activating/deactivating them, assigning them dynamically to the operational contexts of Virtual Organisations or Virtual Research Environments, publishing their profiles in the infrastructure registry, the Information System, to enable their discovery and use.
Controlled Sharing and Security
Enabling to control resources usage and prevent their exploitation from unauthorized accesses both at the level of data and services. Administrators are provided with easy to use facilities to define fine-grained authorization policies clearly characterising "who" can do "what" with a given resource in the context of a Virtual Organisation or a Virtual Research Environment. It cater for interoperability, e.g. identity federation.
VREs as a Service
Enabling to easily and dynamically create Virtual Research Environments, i.e. web-based, community-oriented, comprehensive, flexible, and secure working environments conceived to serve the needs of modern science by dynamically acquiring data, services, and tools from the infrastructure.
Research Data Sharing
Enabling to seamlessly sharing files, database tables, workflows, datasets, and any research product in accordance whith scientific practices. Shared objects are subject to discussion via forums, posts, and connections. Coworkers get alerted by personalized notifications via several different media channels.
Enabling to register, deploy and activate datasets on the Infrastructures by relying on a help-desk and a rich array of storage technologies offered with the as-a-Service approach to manage relational databases, geospatial databases, column stores, and document stores.
Research Data Curation
Enabling to generate comprehensive and feature-rich metadata in standard formats, to perform disambiguation and validation, to ensure data integrity and consistency, to make data accessible through standard protocols, to manage data access policies, to ensure data identification, traceability, provenance, attribution and reusability.
Data Analytics at Scale
Enabling to support definition and efficient execution of (potentially) computation-intensive workflows involving registered or user-provided datasets and algorithms. It allows to run any Linux-based executable and R script and combine it with the rest of data and algorithms available to build workflows. It dynamically acquires the computing resources from the infrastructure to maximise the performance of the computation.