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Big Data and Infrastructure

Credit: ‘Hurricane Season 2010 as seen from a Satellite’ by Maximilian Reuter (distributed via

Big data is a widely used term to describe the collection and analysis of large quantities of data which are too vast to be evaluated using traditional methods. The term refers to a broad range of scientific research and innovation areas. The Earth and space sciences have, for a long time, been using and interpreting big datasets. Few other scientific disciplines can argue such an extensive history of dealing with substantial datasets. The Earth sciences’ use of big data is aiding advancement in climate change modelling, energy usage and generation, Earth observation and mapping, and natural hazard analysis (amongst others). In addition, our experience with handling these data can be applied to understanding other big data applications.

Current EU policy:

In July 2014, the Commission outlined a new strategy on Big Data with the aim to accelerate ‘the transition towards a data-driven economy in Europe’. The strategy aims to create better services and products for the EU citizens. The main focus areas include:

  • Environment (tackling climate change and reducing energy consumption using new national and local datasets)
  • Agriculture (safer food and increased productivity through a more efficient use of natural resources and by using real time weather and crop data)
  • Healthcare
  • Transport
  • Manufacturing and retail

Future challenges:

Current and future big data challenges exist within the data analysis. This is namely the volume, the frequency, the variety and the veracity of collected data. Data collected globally is currently expanding at a rate of 40 % per year. Robust analytical methods must be insured in order to extract meaningful and reliable conclusions.

Recent EGU papers covering big data in the geosciences:


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