Thanks to the new common solutions developed by the INDIGO DataCloud project, teams of
first-­line researchers in Europe are using public and private Cloud resources to get new results
in Physics, Biology, Astronomy, Medicine, Humanities and other disciplines.

INDIGO-­developed solutions have for instance enabled new advances in understanding how
the basic blocks of matter (quarks) interact, using supercomputers, how new molecules involved
in life work, using GPUs, or how complex new repositories to preserve and consult digital
heritage can be easily built.
The variety of the requirements coming from these so diverse user communities proves that the
modular INDIGO platform, consisting of several state-­of-­the-­art, production-­level services, is
flexible and general enough to be applied to all of them with the same ease of use and
efficiency.These services allow to federate hybrid resources, to easily write, port and run scientific
applications to the cloud. They are all freely downloadable as open source components, and are
already being integrated into many scientific applications, some of which are reported below.

The same solutions are also being explored by industry, to provide innovative services to EU
companies: for example, modelling water reservoirs integrating satellite information, improving
security in cyberspace, or assisting doctors in diagnostics through medical images.

Many INDIGO components will find place in the unified service catalogue provided by EOSC-­
hub, a new H2020 project submitted under the coordination of INDIGO-­DataCloud, EGI and
EUDAT. EOSC-­hub will contribute to the EOSC implementation by enabling seamless and open
access to a system of research data and services provided across nations and multiple

Some sample applications using INDIGO components:

  • High-­energy physics: the creation of complex clusters deployed on several Cloud
    infrastructures is automated, in order to perform simulation and analysis of physics data
    for large experiments.
  • Lifewatch: parameters from a water quality model in a reservoir are calibrated, using
    automated multiple simulations.
  • Digital libraries: multiple libraries can easily access a cloud environment under central
    coordination but uploading and managing their own collections of digital objects. This
    allows them to consistently keep control of their collections and to certify their quality.
  • Elixir: Galaxy, a tool often used in many life science research environments, is
    automatically configured, deployed on the Cloud and used to process data through a
    user-­friendly interface.
  • Theoretical physics: the MasterCode software, used in theoretical physics, adopts
    INDIGO tools to run applications on Grids, Clouds and on HPC systems with an efficient,
    simple-­to-­use, consistent interface.
  • In DARIAH, a pan-­european social and technical infrastructure for arts and humanities,
    the deployment of a self-­managed, auto-­scalable Invenio-­based repository in the cloud is
  • Climate change: distributed, parallel data analysis in the context of the Earth System
    Grid Federation (ESGF) infrastructure is performed through software deployed on HPC
    and cloud environments in Europe and in the US.
  • Image analysis: in the context of EuroBioImaging, a distributed infrastructure for
    microscopy, molecular and medical imaging, INDIGO components are used to perform
    automatic and scalable analysis of bone density.
  • Astronomical data archives: big data consisting of images collected by telescopes are
    automatically distributed and accessed via INDIGO tools.