Federated Identity Management for Research Collaborations

This white-paper expresses common requirements of Research Communities seeking to leverage Identity Federation for Authentication and Authorisation. Recommendations are made to Stakeholders to guide the future evolution of Federated Identity Management in a direction that better satisfies research use cases. The authors represent research communities, Research Services, Infrastructures, Identity Federations and Interfederations, with a joint motivation to ease collaboration for distributed researchers. The content has been edited collaboratively by the Federated Identity Management for Research (FIM4R) Community, with input sought at conferences and meetings in Europe, Asia and North America

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

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. The European Open Science Cloud (EOSC) initiative is an effort in Europe to provide an open, trusted, virtual and federated computing environment to execute scientific applications and store, share and reuse 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. To meet those resource demands, computing paradigms such as High-Performance Computing (HPC) and Cloud Computing are applied to e-science applications. However, adapting applications and services to these paradigms is a challenging task, commonly requiring a deep knowledge of the underlying technologies, which often constitutes a general barrier to its uptake by scientists. 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’s 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 can be transferred to new services for the adoption of the EOSC ecosystem framework. The article made several recommendations for the integration of thematic services in the EOSC ecosystem regarding Authentication and Authorization (federated regional or thematic solutions based on EduGAIN mainly), FAIR data and metadata preservation solutions (both at cataloguing and data preservation—such as EUDAT’s B2SHARE), cloud platform-agnostic resource management services (such as Infrastructure Manager) and workload management solutions.This work was supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 857647, EOSC-Synergy, European Open Science Cloud - Expanding Capacities by building Capabilities. Moreover, this work is partially funded by grant No 2015/24461-2, São Paulo Research Foundation (FAPESP). Francisco Brasileiro is a CNPq/Brazil researcher (grant 308027/2020-5).Peer Reviewed"Article signat per 20 autors/es: Amanda Calatrava, Hernán Asorey, Jan Astalos, Alberto Azevedo, Francesco Benincasa, Ignacio Blanquer, Martin Bobak, Francisco Brasileiro, Laia Codó, Laura del Cano, Borja Esteban, Meritxell Ferret, Josef Handl, Tobias Kerzenmacher, Valentin Kozlov, Aleš Křenek, Ricardo Martins, Manuel Pavesio, Antonio Juan Rubio-Montero, Juan Sánchez-Ferrero "Postprint (published version

Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures

A standardized descriptive ontology supports efficient querying and manipulation of data from heterogeneous sources across boundaries of distributed infrastructures, particularly in federated environments. In this article, we present the Open-Multinet (OMN) set of ontologies, which were designed specifically for this purpose as well as to support management of life-cycles of infrastructure resources. We present their initial application in Future Internet testbeds, their use for representing and requesting available resources, and our experimental performance evaluation of the ontologies in terms of querying and translation times. Our results highlight the value and applicability of Semantic Web technologies in managing resources of federated cyber-infrastructures.EC/FP7/318389/EU/Federation for FIRE/Fed4FIREEC/FP7/732638/EU/Federation for FIRE Plus/Fed4FIREplu

Chapter 4 Data System and Data Management in a Federation of HPC/ Cloud Centers

Artificial Intelligence, Deep Learning, Machine Learning, Supercomputin

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