Batch processing:

Analysis tools must be capable of running both interactively and in batch mode. Scripts derived from an interactive session should be able to be passed to a batch job to reproduce the interactive analysis on a larger sample of events.Plots and other graphical output that are displayed on a terminal screen when running interactively should be saved for later examination when running in batch mode.

Sharing data structures among users:

At user option, data (and command) structures of various types should be capable of being made available to others, wiht some granularity on how widely the permission is granted (for example world-wide access, experiment-wide access, or physics group-wide access). This access should be granted to files of special types of data preserved in an analysis job, to selected samples of standard format data, to analysis macros and selection criteria, and to definitions of graphical output produced by an analysis job.

Shared dynamic access by several clients:

For online use, data structures (such as histograms) used for display purposes should be capable of being dynamically updated by other running processes. The data structures should be able to be shared among several jobs all having simultaneous read access to the data structure, thus allowing the plots to be viewed by several different users.

Parallel processing (using distinct data streams):

The analysis system must be capable of processing large numbers of events efficiently. If a single processor is not capable of providing the required throughput, the system should support simple parallel processing where different servers analyse separate event streams, with the results bring automaticaly combined before presentation.