Any physicist who will analyse data from the LHC experiments will have to deal with data and computing resources which are distributed across multiple locations and with different access methods. GANGA helps the end user by tying in specifically to the solutions for a given experiment ranging from specification of data to retrieval and post-processing of produced output. For LHCb and ATLAS the main goal is to assist in running jobs based on the Gaudi/Athena C++ framework. GANGA is written in Python and presents the user with a single GUI rather than a set of different applications. It interacts with external resources like experiments bookkeeping databases, job configuration, and Grid submission systems through plug-able modules. The user is upon start-up presented with a list of templates for common analysis tasks and GANGA persists information about ongoing tasks between invocations. GANGA can also be used through a command line interface that has a tight connection to the GUI to ease the transition from one to the other. Examples will be presented that demonstrates the integration into the distributed analysis systems of the LHCb and ATLAS experiments as used during their 2004 data challenges.
A. Maier (CERN) A. Soroko (Oxford University) C.L. Tan (Birmingham University) D. Adams (BNL) G.N. Patrick (RAL) J. Martyniak (Imperial College London) J. Moscicki (CERN) K. Harrison (Cambridge University) P. Charpentier (CERN) P. Mato (CERN) R. Jones (Lancaster University) U. Egede (IMPERIAL COLLEGE LONDON)