e-Science City!

e-Science projects are global collaborations that rely on international computing infrastructures. They link together continents and connect different disciplines with grids, clouds and high performance computers. But behind the technology you’ll find people making it all work – people with very diverse backgrounds and interests. Here in People bay you can find the faces behind e-science and what they do, with information on where they're based and brief biographies. If you'd like to be added to People Bay, email [email protected]. Explore our online city and find out more about the world of grids, volunteer computing, supercomputing, and networks.

The e-ScienceCity is brought to you by e-ScienceTalk, reporting on the success stories of Europe's e-Infrastructures through blogs, videos, policy briefings, social media, websites and an international newsletter, International Science Grid This Week.

The e-ScienceCity builds on the award-winning GridCafé website.

Want to discuss anything on the site? Why not vist our Facebook page?

The e-ScienceCity region is also hosted in 3D on the New World Grid, a virtual world run by the non-profit organisation Virtus, based on OpenSim technology. Our new virtual e-ScienceCity island is part of an OpenSim pilot, to create and evaluate a virtual venue dedicated to e-science and e-learning. You are warmly invited to explore our new island – entrance is free and transport should be trouble-free!

We hope you enjoy exploring e-ScienceCity. As you may know we're still building and growing the site so if you have any comments or suggestions for us we'd love to hear them! Just drop us an email

Big Science today is all about big, open data – or so we're told. But what does that mean exactly? Take a stroll around data park, and find out. Things are hopefully well signposted, but if you have trouble getting around, just tell the Park Ranger! For starters, you might want to take a look at Data in 30 seconds, where you can find out about what data is, some of the computer formats data can come in, and what big data and open data actually mean. You might also be interested in looking at how computers handle data, the future of data, some of the hot topics surrounding data, grids and distributed data and data projects. If you want to read about these topics in more depth, you can download our PDF briefings on these topics: Open Data, Open Science, Big Data, Visualisation, Research Networks.

What is grid computing?

Although "the Grid" is still just a dream... grid computing is already reality. Imagine several million computers from all over the world, and owned by thousands of different people. Imagine they include desktops, laptops, supercomputers, data vaults, and instruments like mobile phones, meteorological sensors and telescopes... Now imagine that all of these computers can be connected to form a single, huge and super-powerful computer! This huge, sprawling, global computer is what many people dream "The Grid" will be. "The Grid" takes its name from an analogy with the electrical "power grid". The idea was that accessing computer power from a computer grid would be as simple as accessing electrical power from an electrical grid".

Computational problems

There are many different ways to describe computational problems. Here are a few that are important to grid technology: Parallel calculations: Parallel calculations can be split into many smaller sub-calculations. This means that each sub-calculation can be worked on by a different processor, so that many sub-calculations can be worked on "in parallel". This allows you to speed up your computation. Embarrassingly parallel calculations: A calculation is embarrassingly parallel when each sub-calculation is independent of all the other calculations. For example, analyzing a large databank of medical images is embarrassingly parallel, since each image is independent of the others. Coarse-grained calculations: Coarse-grained calculations are often embarrassingly parallel. "Monte Carlo simulations", where you vary the parameters in a model and then study the results, are also coarse-grained calculations. Fine-grained calculations: In a fine-grained calculation, each sub-calculation is dependent on the result of another sub-calculation. For example, when calculating the weather, each calculation in one volume of atmosphere is affected by surrounding volumes. Fine-grained parallel calculations require very clever programming to make the most of their parallelism, so that the right information is available to processors at the right time.