How do we get the data to build computational models?

We present a new approach to building radically distributed databases of neuroscience data. It aims to make available to modelers the huge amount of useful experimental data and notes which currently sits on experimenters PCs and lab notebooks. The approach has two components. The initial phase is a user friendly desktop application which experimental neuroscientists can use to markup data and build small catalogs of their data. The second phase is a server application which acts like a "smarter Google" which is able to combine and index catalogs from multiple researchers and labs so that modelers can download local copies of data relevant to their study. (C) 2004 Published by Elsevier B.V.