Elastic-R

Copyright © 2007-2013 Karim Chine

Executive Summary

EN - Science and education in the cloud: Towards a ubiquitous and collaborative environment for research and e-learning.

Cloud computing holds the promise to trigger a radical evolution of the scientific and statistical computing tools' ecosystem. it will unquestionably have a major impact on research and education. Elastic-R is the first platform to make this potential become a reality: The on-demand, elastic and programmable infrastructure (the cloud) and the most important scientific computing software such as R, Python, Scilab, Mathematica, etc. are merged into a single ubiquitous and collaborative virtual environment.

Henceforth, Researcher, Educator and Student can acquire very easily compute and storage resources and use them to work virtually with R, python, Scilab, Mathematica, etc. on their own or collaboratively without any memory, data size or data location constraints. Any device (PC, iPad, mobile phone, etc.) and any client application (web browser, Word, Excel, Local R Sessions) can be used to access the virtual remote environment. Geographically distributed collaborators can access a shared session and interact in real-time to analyse their data collaboratively, build together models, spread sheets, interactive User Interfaces and dashboards, scientific applications and workflow components, etc. Any static or dynamic/interactive artefact produced within Elastic-R can be instantly published with a simple URL. A data analysis session and all its artefacts can be check pointed and resumed on a different machine with a different capacity. Those artefacts can be stored, shared and reused. Elastic-R makes the cloud infrastructure and its manipulation become part of the R functions and Scientist can easily, from within a local R session, run massively parallel computations on the cloud seamlessly.

FR - Science et éducation dans le cloud : vers un environnement virtuel collaboratif ubiquitaire pour la recherche et l'enseignement.

Le cloud computing porte en lui la promesse d'une évolution radicale de l'écosystème des outils de calcul scientifique et statistique. Il aura un impact majeur sur la recherche et l'éducation. Elastic-R est l'une des premières plateformes à concrétiser une partie de ce potentiel : l'infrastructure à la demande, élastique et programmable (le cloud) et les outils tels que R, Python, Scilab, Mathematica,etc. sont fusionnés au sein d'un seul environnement virtuel collaboratif ubiquitaire.

Le chercheur, l'enseignant et l'étudiant peuvent désormais mobiliser sans difficulté des ressources de calcul et de stockage et les utiliser pour travailler avec R, python, etc. seuls ou collaborativement sans contraintes ni de mémoire ni de taille de données ni de localisation de ces données. N'importe quel équipement (PC, téléphone, iPad,etc.) et n'importe quelle application cliente (navigateur web, Word, Excel, Session R locales, etc.) permet d’accéder à cet environnement. Des collaborateurs géographiquement distribués peuvent accéder à une session partagée et interagir en temps réel pour analyser leurs données ou produire ensemble des modèles, des feuilles de calcul, des interfaces interactives, des composants d'applications ou de workflows analytiques/scientifiques. Tout artefact produit, statique ou dynamique/interactif, est instantanément publiable par simple URL. Une session d'analyse et tous les artefacts qui s'y rattachent peuvent être enregistrés, reproduits ou partagés. L'infrastructure et sa manipulation deviennent des "fonctions" de R ou de python et des calculs massivement parallèles peuvent être lancés avec une grande simplicité.

Published Articles

  • Chine K (2010) Open science in the cloud: towards a universal platform for scientific and statistical computing. In: Furht B, Escalante A (eds) Handbook of cloud computing, Springer, USA, pp 453-474. ISBN 978-1-4419-6524-0.

    Springerlink - PDF

  • Karim Chine, "Learning math and statistics on the cloud, towards an EC2-based Google Docs-like portal for teaching / learning collaboratively with R and Scilab," icalt, pp.752-753, 2010 10th IEEE International Conference on Advanced Learning Technologies, 2010.

    IEEExplore - PDF - DOC

  • Karim Chine, "Scientific computing environments in the age of virtualization, toward a universal platform for the cloud" pp. 44-48, 2009 IEEE International Workshop on Open Source Software for Scientific Computation (OSSC), 2009.

    IEEExplore - PDF - DOC

  • Karim Chine, "Biocep, towards a federative, collaborative, user-centric, grid-enabled and cloud-ready computational open platform" escience,pp.321-322, 2008 Fourth IEEE International Conference on eScience, 2008.

    IEEExplore - PDF

Author


    Karim

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    Chine

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    karim.chine@cloudera.co.uk

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    Short Biography:


    Karim chine is a Cloud Computing expert, a software architect and a social entrepreneur. After graduating from the French Ecole Polytechnique and Telecom ParisTech, he occupied various positions within Industry and Academia. Karim was a stuff member respectively at Schlumberger, IBM, EBI and Imperial College London. He is the founder of cloud era, a start-up specializing in Scientific software-as-a-service. Karim's interests include large scale distributed software design, HPC, pervasive computing and cloud computing applications in research and education. Since 2009, he has been a member of the European Commission panel of experts for the EU Research Infrastructure programme. Karim is the author and designer of Elastic-R, a pioneering Virtual Research Environment for scientific computing, reproducible research and collaboration in the cloud.

Talks, Tutorials, Conferences

Presentations Slides



They Wrote about Elastic-R


  • Will the Cloud Reign for Pharma? - Bio-IT World Magazine - Kevin Davis - here

  • SC10 Disruptive Technology Preview: The First Cloud Portal to “R” and Beyond - HPC in the Cloud - Nicole Hemsoth here

  • The Biocep R Project Brings Open Science to the Cloud - ReadWriteCloud - Audrey Watters here

  • Interview with the author (e-taalim) here

  • Interview with the author (Tekiano) here

  • Tekiano article here

  • Interview with the author (Decisionstats) here

  • Hans Gilde's weblog here

  • CRAN Task Views - High Performance Computing here

  • State-of-the-art in Parallel Computing with R -Technical Report Number 47, 2009 - Department of Statistics-University of Munich State-of-the-art in Parallel Computing with R here

  • BusinessWeek Cloud Computing Ad Section here

  • DecisionStats blog here

  • R & BioConductor Manual here

  • Bitlab Wiki- here

  • Enabling reproducible research: licensing for scientific innovation here

  • e-Taalim, Cloud computing for science and education here

  • e-Taalim, Cloud computing: Recherche scientifique, éducation et solidarité numérique here

Acknowledgements


    ACS: Madi Nassiri Amazon: Simone Brunozzi, Deepak Singh AT&T Research Labs: Simon Urbanek ATUGE: Imen Essafi, Béchir Tourki, Ilyes Gouja, HatemHachicha, Amine Elleuch Banca d'Italia: Giuseppe Bruno Bio-IT World :Kevin Davies Cambridge Healthtech Institute: Cindy Crowninshield City University of New York: Mario Morales, Makram Talih Columbia University: Omar Besbes Dataspora: Michael E. Driscoll EBI: Alvis Brazma, Wolfgang Huber, Kimmo Kallio, Misha Kapushesky, Michael Kleen, Alberto Labarga, Philippe Rocca-Serra, Ugis Sarkans, Kirsten Williams, Eamonn Maguire EPFL: Darlene Goldstein Esprit: Farouk Kamoun, Tahar Ben Lakhdar ETH Zürich: Yohan Chalabi, Diethelm Würtz, Martin Mächler e-Taalim.com: Nadhir Douma FHCRC: Martin Morgan, Seth Falcon, Nianhua Li FVG LLC: Lisa Wood Google: Olivier Bosquet Harvard Business School: Ousseynou Nakoulima Harvard University: Tim Clark, Sudeshna Das, Douglas Burke, Paolo Ciccarese IBM: Jean-Louis Bernaudin, Pascal Sempe, Loic Simon, Lea A Deleris, Alex Fleischer, Alain Chabrier Imperial College London: Asif Akram, Vasa Curcin, John Darlington, Brian Fuchs Indiana University: Michael Grobe INRIA: David Monteau JISC: David Flanders Johnson & Johnson - Janssen Pharmaceutica: Patrick Marichal Lancaster University: Robert Crouchley, Daniel Grose Leibniz Universität Hannover: Kornelius Rohmeier Limagrain: Zivan Karaman Mekentosj: Alexander Griekspoor Microsoft: Eric Le Marois, Tony Hey Mubadala: Ghazi Ben Amor Nature Publishing Group: Ian Mulvany, Steve Scott NCeSS: Peter Halfpenny, Rob Procter, Marzieh Asgari-Targhi, Alex Voss, YuWei Lin, Mercedes Argüello Casteleiro, Wei Jie, Meik Poschen, Katy Middlebrough, Pascal Ekin, June Finch, Farzana Latif, Elisa Pieri, Frank O'Donnell, Kenny Baird New York Java User Group: Frank D Greco OeRC: Dimitrina Spencer, Matteo Turilli, David Wallom, Steven Young OMII-UK: Neil Chue Hong, Steve Brewer OpenAnalytics: Tobias Verbeke Oracle: Dominique van Deth, Andrew Bond OSS Watch: Ross Gardler Platform Computing: Christopher Smith San Diego Supercomputer Center: Nancy R. Wilkins-Diehr Sanger Institute: Daniel Jeffares, Matt Wood, Phil Butcher Shell: Wayne.W.Jones, Nigel Smith Stanford University: John Chambers, Balasubramanian Narasimhan, Gunter Walther SYSTEM@TIC: Karim Azoum Technische Universität Dortmund: Uwe Ligges, Bernd Bischl The Generations Network: Jim Porzak Tunisian Ministry of Communication Technologies: Naceur Ammar, Lamia Chaffai-Sghaier, Mohamed Saïd Ouerghi Tunisian Ecole Polytechnique: Riadh Robbana UC Berkeley: Noureddine El Karoui, Terry Speed UC Davis: Rudy Beran, Debashis Paul, Duncan Temple Lang UCLA: Ivo Dinov UCSF: Tena Sakai Université Catholique de Louvain: Christian Ritter University of Cambridge: Ian Roberts, Robert MacInnis,Peter Murray-Rust, Jim Downing University of Manchester: Carole Goble, Len Gill, Simon Peters, Richard D Pearson, Iain Buchan, John Ainsworth University of Plymouth: Paul Hewson University of Split: Ivica Puljak UTK: Ajay Ohri Wirtschaftsuniversität Wien: Stefan Theussl World Bank Group-IFC: Oualid Ammar Yahoo: Laurent Mirguet, Rob Weltman Independent: Charles Dallas, Romain François, Manfred Duchrow, Joerg Mueller, Slava Pestov