INDIGO-DataCloud

INtegrating Distributed data Infrastructures for Global ExplOitation

CoordinatorINSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ AKADEMII NAUK ; CERN ; Utrecht University ; AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS ; CESNET ZAJMOVE SDRUZENI PRAVNICKYCH OSOB ; T-SYSTEMS INTERNATIONAL GMBH ; AGH University of Science and Technology ; Istituto Centrale per il Catalogo Unico Delle Biblioteche Italiane e per le Informazioni Bibliografiche ; INDRA SISTEMAS SA ; National Institute for Astrophysics ; European Grid Infrastructure Foundation ; Universitat Politècnica de València ; National Institute of Geophysics and Volcanology ; National Institute for Nuclear Physics ; Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine ; Rudjer Boskovic Institute ; Euro-Mediterranean Center for Climate Change ; CNRS - Institut des Sciences Biologiques ; SANTER REPLY SPA ; Atomic Energy and Alternative Energies Commission ; National Research Council ; ATOS SPAIN SA ; Karlsruher Institut für Technologie ; LABORATORIO DE INSTRUMENTACAO E FISICA EXPERIMENTAL DE PARTICULAS LIP ; SCIENCE AND TECHNOLOGY FACILITIES COUNCIL ; Deutsches Elektronen-Synchrotron
Grant period2015-04-01 - 2017-09-30
Funding bodyEuropean Union
Call numberH2020-EINFRA-2014-2
Grant number653549
IdentifierG:(EU-Grant)653549

Note: The INDIGO-DataCloud project (INDIGO for short) aims at developing a data/computing platform targeted at scientific communities, deployable on multiple hardware, and provisioned over hybrid (private or public) e-infrastructures. This platform will be built by leading European developers, resource providers, e-infrastructures and scientific communities in order to ensure its successful exploitation and sustainability. All members of the consortium share the common interest in developing advanced middleware to sustain the deployment of service models and user tools to tackle the challenges of the Big Data era. INDIGO will exploit the formidable know-how that was built in Europe along the past ten years of collaborations on scientific computing based on different consolidated and emerging paradigms (HPC, Grid and Cloud). Regarding Cloud computing, both the public and private sectors are already offering IaaS-type Cloud resources. However, numerous areas are of interest to scientific communities where Cloud computing uptake is currently lacking, especially at the PaaS and SaaS levels. The project therefore aims at developing tools and platforms based on open source solutions addressing scientific challenges in the Cloud computing, storage and network areas. INDIGO will allow application development and execution on Cloud and Grid based infrastructures, as well as on HPC clusters. The project will extend existing PaaS solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, PRACE and HelixNebula, to integrate their existing services, make them available through GEANT-compliant federated and distributed AA policies, guaranteeing transparency and trust in the provisioning of such services. INDIGO will also address the development of a flexible and modular presentation layer connected to the expanded PaaS and SaaS frameworks developed by the project and allowing innovative user experiences, also from mobile appliances.
     

Recent Publications

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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Report/Journal Article  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;
Likelihood analysis of the pMSSM11 in light of LHC 13-TeV data
The European physical journal / C 78(3), 256 () [10.1140/epjc/s10052-018-5697-0]  GO OpenAccess  Download fulltext Files  Download fulltextFulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Conference Presentation  ;  ;  ;  ;  ;  ;
Storage Quality-of-Service
Connectathon 2017, Santa ClaraSanta Clara, USA, 27 Feb 2017 - 3 Mar 20172017-02-272017-03-03 () [10.3204/PUBDB-2017-13914]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Preprint/Report  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;
Likelihood Analysis of the pMSSM11 in Light of LHC 13-TeV Data
() [10.3204/PUBDB-2017-11875]  GO OpenAccess  Download fulltext Files  Download fulltextFulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS

All known publications ...
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 Record created 2015-09-15, last modified 2023-02-10



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