Abstract-Big Data are becoming a new technology focus both in science and in industry. This paper discusses the challenges that are imposed by Big Data on the modern and future Scientific Data Infrastructure (SDI). The paper discusses a nature and definition of Big Data that include such features as Volume, Velocity, Variety, Value and Veracity. The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics in data management in modern e-Science. The paper proposes the SDI generic architecture model that provides a basis for building interoperable data or project centric SDI using modern technologies and best practices. The paper explains how the proposed models SDLM and SDI can be naturally implemented using modern cloud based infrastructure services provisioning model and suggests the major infrastructure components for Big Data Infrastructure.

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Abstract-This paper discusses the challenges that are imposed by Big Data Science on the modern and future Scientific Data Infrastructure (SDI). The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics in data management in modern e-Science. The paper proposes the SDI generic architecture model that provides a basis for building interoperable data or project centric SDI using modern technologies and best practices. The paper explains how the proposed models SDLM and SDI can be naturally implemented using modern cloud based infrastructure services provisioning model.

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Abstract-This paper describes the Infrastructure and Network Description Language (INDL). The aim of INDL is to provide technology independent descriptions of computing infrastructures. These descriptions include the physical resources and the network infrastructure that connects these resources. The description language also provides the necessary vocabulary to describe virtualization of resources and the services offered by these resources. Furthermore, the language can be easily extended to describe federation of different existing computing infrastructures, specific types of (optical) equipment and also behavioral aspects of resources, for example, their energy consumption.Before we introduce INDL we first discuss a number of modeling efforts that have lead to the development of INDL, namely the Network Description Language, the Network Markup Language and the CineGrid Description Language. We also show current applications of INDL in two EU-FP7 projects: NOVI and GEYSERS. We demonstrate the flexibility and extensibility of INDL to cater the specific needs of these two projects.

Current research networks allow end users to build their own application-specific connections (lightpaths) and Optical Private Networks (OPNs). This requires a clear communication between the requesting application and the network. The Network Description Language (NDL) is a vocabulary designed to describe optical networks based on the Resource Description Framework (RDF). These descriptions aid applications in querying the capabilities of the network and allow them to clearly express requests to the network. This article introduces NDL and shows its current applications in optical research networks.

Policy makers in regions such as Europe are increasingly concerned about the trustworthiness and sovereignty of the foundations of their digital economy, because it often depends on systems operated or manufactured elsewhere. To help curb this problem, we propose the novel notion of a responsible Internet, which provides higher degrees of trust and sovereignty for critical service providers (e.g., power grids) and all kinds of other users by improving the transparency, accountability, and controllability of the Internet at the network-level. A responsible Internet accomplishes this through two new distributed and decentralized systems. The first is the Network Inspection Plane (NIP), which enables users to request measurement-based descriptions of the chains of network operators (e.g., ISPs and DNS and cloud providers) that handle their data flows or could potentially handle them, including the relationships between them and the properties of these operators. The second is the Network Control Plane (NCP), which allows users to specify how they expect the Internet infrastructure to handle their data (e.g., in terms of the security attributes that they expect chains of network operators to have) based on the insights they gained from the NIP. We discuss research directions and starting points to realize a responsible Internet by combining three currently largely disjoint research areas: large-scale measurements (for the NIP), open source-based programmable networks (for the NCP), and policy making (POL) based on the NIP and driving the NCP. We believe that a responsible Internet is the next stage in the evolution of the Internet and that the concept is useful for clean slate Internet systems as well.

Environmental research infrastructures (RIs) support data-intensive research by integrating large-scale sensor/observer networks with dedicated data curation services and analytical tools. However the diversity of scientific disciplines coupled with the lack of an accepted methodology for constructing new RIs inevitably leads to incompatibilities between the data models, metadata standards and service descriptions used by different RIs, inhibiting their usefulness for interdisciplinary research. In the absence of a common global ontology of science and infrastructure, these inconsistencies may best be counteracted by selectively bridging the semantics of the various vocabularies, standards and models used by the RIs at present. Open Information Linking for Environmental RIs (OIL-E) was developed within the FP7 project ENVRI to provide a framework for semantic linking of knowledge resources used by different environmental RIs. Built around a multi-viewpoint reference model ENVRI-RM, OIL-E is intended to act as a central exchange for linking information fragments and identifying gaps in the conceptual models of RIs.