Dr Jack Cranshaw (Argonne National Laboratory (US))
TAGs are event-level metadata allowing a quick search for interesting events for further analysis, based on selection criteria defined by the user. They are stored in a file-based format as well as in relational databases. The overall TAG system architecture encompasses a range of interconnected services that provide functionality for the required use cases such as event level selection, display, extraction and skimming. Skimming can be used to produce any of the pre-TAG data products by pure copy or any post-TAG data products if these can be made from a pre-TAG data product. The implemented use cases for the skimming service scale from a physicist wishing to select a handful of interesting events for an analysis specific study to the creation of physics working group samples on the ATLAS production system. This paper will focus on the workflow aspects involved in creating pre and post TAG data products from a TAG selection using the Grid in the context of the overall TAG system architecture. The emphasis will be on the range of demands that the implemented use cases place on these workflows and on the infrastructure. The tradeoffs of various workflow strategies will be discussed including scalability issues and other concerns that occur when integrating with data management and production systems.
Collaboration Atlas (Atlas)
Donnchadha Quilty (University College Dublin School of Physics (UCD)) Dr Jack Cranshaw (Argonne National Laboratory (US)) Dr Julius Hrivnac (Universite de Paris-Sud 11 (FR)) Marcin Nowak (Brookhaven National Laboratory (US)) Mark Slater (Birmingham University) Qizhi Zhang (Argonne National Laboratory (US)) Thomas Doherty (Department of Physics and Astronomy-University of Glasgow)