The user support programme and the training infrastructure of the EGI Federated Cloud

The EGI Federated Cloud is a standards-based, open cloud system as well as its enabling technologies that federates institutional clouds to offer a scalable computing platform for data and/or compute driven applications and services. The EGI Federated Cloud is based on open standards and open source Cloud Management Frameworks and offers to its users IaaS, PaaS and SaaS capabilities and interfaces tuned towards the needs of users in research and education. The federation enables scientific data, workloads, simulations and services to span across multiple administrative locations, allowing researchers and educators to access and exploit the distributed resources as an integrated system. The EGI Federated Cloud collaboration established a user support model and a training infrastructure to raise visibility of this service within European scientific communities with the overarching goal to increase adoption and, ultimately increase the usage of e-infrastructures for the benefit of the whole European Research Area. The paper describes this scalable user support and training infrastructure models. The training infrastructure is built on top of the production sites to reduce costs and increase its sustainability. Appropriate design solutions were implemented to reduce the security risks due to the cohabitation of production and training resources on the same sites. The EGI Federated Cloud educational program foresees different kind of training events from basic tutorials to spread the knowledge of this new infrastructure to events devoted to specific scientific disciplines teaching how to use tools already integrated in the infrastructure with the assistance of experts identified in the EGI community. The main success metric of this educational program is the number of researchers willing to try the Federated Cloud, which are steered into the EGI world by the EGI Federated Cloud Support Team through a formal process that brings them from the initial tests to fully exploit the production resources. © 2015 IEEE

Future opportunities and trends for e-infrastructures and life sciences: Going beyond the grid to enable life science data analysis

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community

COMP Superscalar, an interoperable programming framework

COMPSs is a programming framework that aims to facilitate the parallelization of existing applications written in Java, C/C++ and Python scripts. For that purpose, it offers a simple programming model based on sequential development in which the user is mainly responsible for identifying the functions to be executed as asynchronous parallel tasks and annotating them with annotations or standard Python decorators. A runtime system is in charge of exploiting the inherent concurrency of the code, automatically detecting and enforcing the data dependencies between tasks and spawning these tasks to the available resources, which can be nodes in a cluster, clouds or grids. In cloud environments, COMPSs provides scalability and elasticity features allowing the dynamic provision of resources.This work has been supported by the following institutions: the Spanish Government with grant SEV-2011-00067 of the Severo Ochoa Program and contract Computacion de Altas Prestaciones VI (TIN2012-34557); by the SGR programme (2014-SGR-1051) of the Catalan Government; by the project The Human Brain Project, funded by the European Commission under contract 604102; by the ASCETiC project funded by the European Commission under contract 610874; by the EUBrazilCloudConnect project funded by the European Commission under contract 614048; and by the Intel-BSC Exascale Lab collaboration.Peer ReviewedPostprint (published version

Toward porting Astrophysics Visual Analytics Services to the European Open Science Cloud

The European Open Science Cloud (EOSC) aims to create a federated environment for hosting and processing research data to support science in all disciplines without geographical boundaries, such that data, software, methods and publications can be shared as part of an Open Science community of practice. This work presents the ongoing activities related to the implementation of visual analytics services, integrated into EOSC, towards addressing the diverse astrophysics user communities needs. These services rely on visualisation to manage the data life cycle process under FAIR principles, integrating data processing for imaging and multidimensional map creation and mosaicing, and applying machine learning techniques for detection of structures in large scale multidimensional maps

Exploitation and Sustainability Final Plan

This document describes StratusLab's plans for exploitation and sustainability be- yond the project lifetime. The plans cover commercial exploitation, primarily through commercial integration and support; and non-commercial exploitation, through use in national and international research e-infrastructures: for operating grid resources on private clouds, and for running research-oriented community clouds. In addition, we plan exploitation through partner projects such as EGI and through training and future research. Plans are in place to ensure the sustainability of the critical infrastructures used by the project partners, users and collaborating projects. Similarly, the software outputs of the project have been identified and a plan for the future development of each has been created. These plans include the formation of an open-source StratusLab community, identifying key partners to continue development of specific components, identifying funding options (public, private and community contributions) for continued development and engaging with collaborating projects to ensure that they will contribute to the maintenance and development of the components that they use

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

A survey of the European Open Science Cloud services for expanding the capacity and capabilities of multidisciplinary scientific applications

Open Science is a paradigm in which scientific data, procedures, tools and results are shared transparently and reused by society as a whole. The initiative known as the European Open Science Cloud (EOSC) is an effort in Europe to provide an open, trusted, virtual and federated computing environment to execute scientific applications, and to store, share and re-use research data across borders and scientific disciplines. Additionally, scientific services are becoming increasingly data-intensive, not only in terms of computationally intensive tasks but also in terms of storage resources. Computing paradigms such as High Performance Computing (HPC) and Cloud Computing are applied to e-science applications to meet these demands. However, adapting applications and services to these paradigms is not a trivial task, commonly requiring a deep knowledge of the underlying technologies, which often constitutes a barrier for its uptake by scientists in general. In this context, EOSC-SYNERGY, a collaborative project involving more than 20 institutions from eight European countries pooling their knowledge and experience to enhance EOSC\u27s capabilities and capacities, aims to bring EOSC closer to the scientific communities. This article provides a summary analysis of the adaptations made in the ten thematic services of EOSC-SYNERGY to embrace this paradigm. These services are grouped into four categories: Earth Observation, Environment, Biomedicine, and Astrophysics. The analysis will lead to the identification of commonalities, best practices and common requirements, regardless of the thematic area of the service. Experience gained from the thematic services could be transferred to new services for the adoption of the EOSC ecosystem framework