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D4Science Virtual Research Environments and their services are presented as supporting the entire data management life cycle.

An activity to define the mission statement of the initiative, assess the type of business model centred on a public partnership, propose a business plan for sustaining the iMarine baseline activities, and prepare the ground for a business plan under a growth scenario

Scientific activities are nowadays highly multidisciplinary, involve researchers of different institutions, and need innovative working environments. In this context, the Networked Multimedia Information Systems Laboratory (NeMIS) of the CNR Institute of Information Science and Technology (ISTI) has designed and realized an approach for the creation and management of Virtual Research Environments based on Hybrid Data Infrastructures. Such environments, accessible through a web browser, offer the whole set of resources necessary to fully respond to the needs of a specific application context (data, services and computational resources). These resources are dynamically acquired by means of an infrastructure that is capable of interfacing with existing services and Grid/Cloud infrastructures. This approach has been successfully applied in application contexts ranging from managing of catch statistics to the production of species distribution maps based on probabilistic models taking into account environmental factors.

Modern science call for innovative practices to facilitate research collaborations that span institutions, disciplines, and countries. Scientists and practitioners are called to produce enhanced forms of scientific communication thus to make it possible for others to identify errors, to support, reject or refine theories and to reuse data for further understanding and knowledge. This scenario can benefit a lot from Internet-based services aiming at providing individual users having at their disposal scarce resources with interaction-oriented facilities, i.e., social computing, and elastic access to facilities on demand, i.e., cloud computing. In this paper, we present the Hybrid Data Infrastructure, D4Science, developed to serve the needs of various communities of practice yet based on a technology which is domain agnostic. By leveraging social computing and cloud computing D4Science realises an integrated web-based working environment where scientists have at their fingertips what is needed to accomplish a scientific investigation. We present the large scale data management and processing facilities obtained through the use of services compliant with the cloud paradigms. Moreover, we present the large array of collaboration-oriented facilities obtained by integrating social networking paradigms with virtual research environments.

This final report gives an account of the objectives and results of the D4S Project. The main objectives of D4Science were to create a production quality e-Infrastructure for addressing the needs of two major target disciplines: Environmental Monitoring and Fisheries and Aquaculture Resources Management. This e-Infrastructure has been obtained by deploying, progressively enriching and consolidating the ones built by the EGEE and DILIGENT projects, and now it gives scientists of the addressed and other challenging areas more facilities for creating Virtual Research Environments (VREs) based on shared computation, storage, and generic service resources as well as on data and domain-specific service resources. Computation, storage, and generic service resources are offered by EGEE, project partners and their collaborators at a European level, while data and domain-specific service resources are offered by large international organizations, such as the European Space Agency, the Food and Agriculture Organization of the United Nations, and the Consultative Group on International Agriculture Research. The D4Science e-Infrastructure is expected to provide a multiplicative benefit to many scientific fields, and also act as a catalyst for the kind of cooperation and cross fertilization among multiple communities that is necessary for addressing many grand challenges of science and society.

This paper presents the gCube system, a software system specifically conceived to develop and operate large scale e-Infrastructures, enabling the declarative definition and automatic deployment and operation of VREs.

Fisheries Resources Management has an ever increasing demand for capture data with ever finer geographical resolution, and an ever greater number of environmental variables to take into account. The management information process requires access to relevant documentation and source data. To support such demanding scenarios a promising approach is based on e-Infrastructures. By definition, an e-Infrastructure is a framework enabling secure, cost-effective and on-demand resource sharing across domain boundaries.The potentially unlimited availability of resources allows a new development paradigm based on the notion of Virtual Research Environment, i.e., an integrated environment that provides seamless access to resources and offers facilities for communication, collaboration and interaction among scientists and researchers. This presentation focuses on the implementation of this innovative approach in the context of D4Science.

e-Infrastructure is the term coined for innovative research environments that provide modern scientists with seamless access to shared, distributed and heterogeneous resources. Virtual Research Environments (VREs) are applications whose constituents are dynamically borrowed from the e-Infrastructure, bound (and deployed) instantly, just at the time and for the period they are needed. In this paper we describe D4Science, an e-Infrastructure supporting the design and deployment of VREs.

gCube is a new service-oriented application framework that supports the on-demand sharing of resources for computation, content and application services. gCube enables the realization of e-infrastructures that support the notion of Virtual Research Environments (VREs), ie collaborative digital environments through which scientists, addressing common research challenges, exchange information and produce new knowledge. gCube is currently used to govern the e-infrastructure set up by the European integrated project DILIGENT (A Digital Library Infrastructure on Grid-Enabled Technology).

D4Science provides production-quality facilities for creating and managing (VREs) based on an e-infrastructures composed of shared computational, storage, data and service resources. Through this, it enables scientists to organize, retrieve, access and analyse heterogeneous and widely distributed information in order to generate new knowledge.

This papers discusses how DLs are evolving into "Virtual Research Environments, i.e., distributed frameworks for carrying out cooperative activities like "in silico experiments", data analysis and processing, production of new knowledge using specialised tools. They are largely based on retrieval and access of always updated knowledge from diverse heterogeneous content sources. The knowledge produced is preserved and made available for other usages inside and outside the VRE.

The DILIGENT Project is presented with special emphasis on its aspects that make it a means that will allow to construct Dynamic Universal Knowledge Environments serving a large number of research communities

EUBrazilOpenBio is a collaborative initiative addressing strategic barriers in biodiversity research by integrating open access data and user-friendly tools widely available in Brazil and Europe. The project deploys the EU-Brazil cloudbased e-infrastructure that allows the sharing of hardware, software and data on-demand. This e-Infrastructure provides access to several integrated services and resources to seamlessly aggregate taxonomic, biodiversity and climate data, used by processing services implementing checklist cross-mapping and ecological niche modelling. The concept of Virtual Research Environments is used to provide the users with a single entry point to processing and data resources. This article describes the architecture, demonstration use cases and initial experimental results.