Effectively managing data on a grid

Advances in parallel computing have resulted in the emergence of grid computing, a field that strives to integrate multiple distributed and heterogeneous resources, which are typically under distinct administrative domains, into a single, coherent system that can be efficiently and effectively used to solve complex and demanding problems in a fashion that is transparent to the end user [1–3]. Such resources include compute systems, storage systems, sensors, visualization devices, rendering farms, imaging systems, and a wide variety of additional Internet-ready instruments. Grids of various sorts are quite fashionable and are being deployed in many fields, including structural biology, computational chemistry, cancer research, biomedical informatics, astronomy, environmental science, and high-energy physics, to name a few.