A researcher from the Swiss Federal Institute of Technology has joined forces with a group of scientists to create a grandiose computer project capable of simulating everything we know. 

Dr. Dirk Helbing, chairman of the FuturICT project at the Swiss Federal Institute of Technology, along with a team of scientists, have begun to collaborate on an Earth project that could change how we see the world -- literally. 

The computer project has been nicknamed the Living Earth Simulator (LES), and the idea behind it is to simulate everything on Earth, such as the spread of diseases, congestion on roads, international financial transactions and weather patterns. The project is aimed to epitomize both human and environmental actions that shape our world. 

Up until now, technology like the Large Hadron Collider, which is a particle accelerator created by Cern, has been one of the only Earth projects that provides a larger perspective of the universe. But Helbing argues that projects like the Large Hadron Collider do not provide enough information about our own planet, and that we need an accelerator that combines different branches of knowledge about Earth alone. 

"Revealing the hidden laws and processes underlying societies constitutes the most pressing scientific grand challenge of our century," said Helbing. 

Helbing and his team are looking to feed this computer system a "mammoth" amount of data, and then teach it how to understand what all the data means so it can interpret changes and patterns. Every piece of data involving activity on Earth will have to be logged into the simulator, and this simulator will be powered by supercomputers that can crunch these numbers on a large scale. According to Helbing, "much of the data is already being generated." They are already currently using more than 70 online data sources such as Google Maps and Wikipedia. 

After integrating a monstrous amount of data into the simulator, Helbing and his team will use the knowledge of computer scientists, social scientists and engineers to build a framework to convert this data into models that mimic what is happening on Earth at that moment. 

The next step is to help the simulator understand what all the data and models mean. According to Helbing, the supercomputers will be able to do this over time. With semantic web technology, researchers will be able to encode the data alongside a description of the data, which helps the simulator to better understand exactly what it is reading. This not only applies to environmental, financial, or medical data, but human behavior as well.

"Many problems we have today - including social and economic instabilities, wars,disease spreading - are related to human behavior, but there is apparently a serious lack of understanding regarding how society and the economy work," said Helbing. 

While the simulator will follow human behavior, it will also "strip out" any information in its data that relates directly to the person so that no personal information is leaked or shared. An approach to carrying out such an amount of economic and social data still needs to be agreed upon by researchers, but once they cross that threshold, supercomputers will be built to suit this particular task as well. 

Helbing noted that generating the amount of computational power to run the LES will be challenging, but will in no way halt the project. Researchers working for the FuturICT project hope the LES will lead to better methods of measuring the state of society, which could further help with environmental, health and educational problems. 

"Economics and sociology have consistently failed to produce theories with strong predictive powers over the last century, despite lots of data gathering," said Helbing. "I'm skeptical that larger data sets will mark a big change. It's not that we don't know enough about a lot of the problems the world faces, from climate change to extreme poverty, it's that we don't take any action on the information we do have."

But Helbing also says that the technology that will be used for the LES will only become available in the coming decade, meaning that it will be able to produce models and images as well as learn data in a whole new way, which will ultimately help researchers and world leaders develop new methods of improving societal issues.

"Over the past years, it has for example become obvious that we need better indicators than the gross national product to judge societal development and well-being," said Helbing.