Big Data in Geoscience
Main organisers:Franz Kiraly, Detlef Hohl, Mark Girolami, John Aston
Dates: 25th – 27th January 2016
Location: British Library
The collection, processing, analysis, integration and understanding of all of Earth’s data is one of science’s grand challenges. Designing and implementing a geoscience knowledge system in the spirit of Google Earth but focusing on the interior of Earth, from the lithosphere to the core, is turning into a realistic objective in this era of “Big Data”.
A wide variety of geophysical data (potential fields, electromagnetic, seismic, etc) is acquired with very broad wavelength ranges, from surface sensor arrays, drilled wells, satellites and many other sources. It is a long standing ambition that they be combined into a scale- and detail-variant comprehensive image of the solid Earth and made available to a wide research and application community. Geophysical imaging and geodynamical modelling of the shallow and deep Earth are just two examples of relevant geoscience disciplines and technologies that can contribute to global energy solutions, as well as fundamental understanding of the Earth.
Challenges arise in the systematic acquisition and processing of large amounts of geoscientific data, their integration across modalities and scales, as well as their use in deriving and validating statistical models to answer scientific questions.
Tackling these challenges will require effort across research communities such as information processing (e.g., extreme-scale sensor and data technologies, massively parallel computing), physics-based modelling and inversion (e.g., inverse problems, tomography) statistics and machine learning (e.g., multivariate interpolation and prediction, uncertainty quantification) and in their intersections. Due to its scale, this endeavour will also require focused efforts of academic, industrial, and governmental partners to build an open research analytics platform for mapping of the solid Earth.
It is the purpose of this programme to join the required resources under the guidance of the Alan Turing Institute, to identify and to enable the necessary research agenda, and to foster a practice-guided exchange of research, application, and translation.