Building collaborations – report from the BigSkyEarth meeting in Helsinki

Building collaborations – report from the BigSkyEarth meeting in Helsinki

The main topic of the BigSkyEarth meeting in Helsinki on 10-11 October, 2016, at the Finnish Geospatial Research Institute and co-organized by the University of Helsinki, Department of Physics,  was preparation of the ITN proposals and how to boost collaborative work within BigSkyEarth network.

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Presentations from the BigSkyEarth conference

Presentations from the BigSkyEarth conference

The BigSkyEarth conference in Sorrento, Italy, addressed the question of how to train a new generation of astronomy and Earth observation scientists in the age of interdisciplinarity driven by big data.

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WG2 and 4 Meeting in Finland

WG2 and 4 Meeting in Finland

The WG2&4 Meeting will take place in Masala, Finland (close to Helsinki) on 10-11 October. 2016, at the Finnish Geospatial Research Institute and co-organized by the University of Helsinki, Department of Physics. The main topic of the meeting is preparation of the ITN proposals and how to boost collaborative work within BigSkyEarth network.

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Data preservation in the age of Big Data

Data preservation in the age of Big Data

PERICLES does not want to invent another preservation system. It wants to understand how to realise a world where preservation policies – human-defined, human-understandable policies – can shape and change a model of preservation that must, consequently, be implemented in a dynamic architecture with no reliance on any particular (implementation of any particular) computational component.

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BigSkyEarth Conference – Education in Big Data Era

BigSkyEarth Conference – Education in Big Data Era

Big data trends in modern astronomy and Earth observation make those fields increasingly dependent on computer science. Actually, so dependent that often they have to be considered as new interdisciplinary fields of research. This collides with the traditional educational programs where students in astronomy and Earth observation do not receive training adequate for the era of big data. 

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