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Often the data products from a RI, derived from lower level/raw data, are pre-cooked. That means they are produced by applying some default processing algorithms and parameters, like spatial and temporal resolution, the use of model parameters, model and process selections. This demonstrator is an implementation results of IC_3 use case that describes a model that enables scientific researchers to re-process data by defining other selections of these inputs from other sources.

Scientific Objectives

EISCAT_3D is an environmental research infrastructure on the European Strategy Forum on Research Infrastructures (ESFRI) roadmap. Once assembled, it will be a world-leading international research infrastructure to study the high atmosphere in the Fenno-Scandinavian Arctic and to investigate how the Earth's atmosphere is coupled to space.

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The RTG was modified to run under GNU Octave, and to produce the plots in batch mode with some selected input parameters. The whole setup was installed into the D4Science gCube Virtual Research Environment, provided by ENVRIplus WP7. The D4Science gCube Data Analytics is executed via a web dashboard based GUI. The ticketing system of D4science has been effectively used for tracking the implementation and communicating with WP7 developers. Some initial results are shown in Figure 2, which demonstrates that in the gCube platform, the EISCAT RTG algorithms are translated into Octave, and compiled and published in an ENVRIplus community space. In the same way, an algorithm created by a single EISCAT user can be shared and reused by others. 

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The service prototype can be accessed at:

https://services.d4science.org/group/rprototypinglab/data-miner .

Simply request a use account, you will be able to login to the VRE. There, on ‘Executes an experiment’, selects ENVRI and Webtg V2.

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• Ingemar Häggström, EISCAT Scientific Association, ingemar.haggstrom@eiscat.se