Scientists aim to simulate everything on Earth

Scientists aim to simulate everything on Earth

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UK: Living Earth Simulator (LES) – one of the most large-scale computer projects undertaken, aims to simulate everything that happens on Earth – global weather patterns, spread of diseases or international financial transactions.
More than 70 online data sources have already been identified by an international team who is handling the project. Wikipedia, Google Maps and the UK government’s data repository Data.gov.uk are just some of them. The next step is creating a framework to turn that morass of data in to models that accurately replicate what is taken place on Earth today.
Semantic Web technology will encode a description of data alongside the data itself, enabling computers to understand the data in context. Next, it will be necessary to build supercomputer centres needed to crunch that data and produce the simulation of the Earth, said Dr Helbing from Swiss Federal Institute of Technology. Dr. Helbing chairs the FuturICT project which aims to create the simulator.
LES would be a result of a knowledge accelerator colliding different branches of knowledge to reveal the hidden laws and processes underlying societies constitutes the most pressing scientific grand challenge of our century, he said.
To start, the LES would need to be populated by data covering the entire gamut of activity on the planet, said Helbing. Although the hardware has not yet been built, much of the data is already being generated, he said.
About data processing“If you look at the data-processing capacity of Google, it’s clear that the LES won’t be held back by processing capacity. Getting access to the data will be much more of a challenge, as will figuring out something useful to do with it,” said Pete Warden, founder of the OpenHeatMap project and a specialist on data analysis.
Simply having lots of data isn’t enough to build a credible simulation of the planet, argued Warden. “Economics and sociology have consistently failed to produce theories with strong predictive powers over the last century, despite lots of data gathering. I’m sceptical that larger data sets will mark a big change,” he said.
Source: BBC