Event Indexing Systems for Efficient Selection and Analysis of HERA Data

Title: Event Indexing Systems for Efficient Selection and Analysis of HERA Data

Abstract: The design and implementation of two software systems to improve the efficiency of offline analysis of event data taken with the ZEUS Detector at the HERA electron-proton collider at DESY are presented. Two different approaches were made, one using a set of event directories and the other using a tag database based on a commercial object-oriented database management system. These are described and compared. Both systems provide quick direct access to individual collision events in a sequential data store of several terabytes, and they both significantly improve the event analysis efficiency. In particular, the tag database provides a very flexible selection mechanism and can dramatically reduce the computing time needed to extract small subsamples from the total event sample. Gains as large as a factor of 20 have been obtained.

Main Research Question: How can the efficiency of offline analysis of event data taken with the ZEUS Detector at the HERA electron-proton collider at DESY be improved?

Methodology: Two software systems were developed to improve the efficiency of offline analysis of event data. One approach used a set of event directories, and the other used a tag database based on a commercial object-oriented database management system.

Results: Both systems provided quick direct access to individual collision events and significantly improved event analysis efficiency. The tag database, in particular, offered a very flexible selection mechanism and could reduce computing time needed for extracting small subsamples from the total event sample by as much as a factor of 20.

Implications: These systems have demonstrated that it is possible to overcome the limitations of traditional data storage and management methods in large HEP experiments. The tag database approach has shown promise in providing efficient and flexible access to event data, which can lead to more efficient and accurate analysis of experimental data.

Link to Article: https://arxiv.org/abs/0104008v1 Authors: arXiv ID: 0104008v1