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  1. VIDIA

    11 Sep 2019

    Virtual Infrastructure for Data Intensive Analysis (VIDIA) unites SUNY Oneonta and University at Buffalo's Center for Computational Research to support the analysis of large datasets by social science students at Primarily Undergraduate Institutions (PUIs). VIDIA is...

  2. GlobalHUB

    11 Sep 2019

    GlobalHUB is a virtual global community of students, faculty, and practitioners, interested in global engineering and global citizenship. The specific mission of GlobalHUB is to create an online community of scholars, practitioners, and students to advance global...

  3. e-Biogenouest

    11 Sep 2019

    e-Biogenouest is an open, web-based platform for scientific collaboration in Life Sciences. It represents the gate towards a Western France Virtual Research Environment (VRE) disseminating e-Science concepts into Life Sciences. This VRE is a first step to go towards...

  4. ATLAS@Home

    19 Aug 2019

    ATLAS@Home is a research project that uses volunteer computing to run simulations of the ATLAS experiment at CERN. You can participate by downloading and running a free program on your computer.

  5. CyVerse

    26 Sep 2017

    CyVerse fills a niche created by the computing epoch and a rapidly evolving world. Developing solutions to today’s grand scientific challenges means that we must understand how the organisms that contribute to our food, fuels, and ecosystem are shaped by interactions...

  6. VRE4EIC

    13 Jan 2017

    The VRE4EIC project addresses key data and software challenges in supporting multidisciplinary data driven sciences

  7. Earth Science Information Partners (ESIP)

    10 Jan 2017

    The Federation of Earth Science Information Partners (ESIP) is an open, networked community that brings together science, data and information technology practitioners. Participation in ESIP is beneficial because it provides an intellectual commons to expose, gather...

  8. VRE4EIC

    19 Dec 2016

    The VRE4EIC project addresses key data and software challenges in supporting multidisciplinary data driven sciences