Speaker
Description
We present an overview of Data Processing and Data Quality (DQ) Monitoring for the ATLAS Tile Hadronic
Calorimeter. Calibration runs are monitored from a data quality perspective and used as a cross-check for physics
runs. Data quality in physics runs is monitored extensively and continuously. Any problems are reported and
immediately investigated. The DQ efficiency achieved was 99.6% in 2012 and 100% in 2015, after the detector maintenance in 2013-2014.
Changes to detector status or calibrations are entered into the conditions database during a brief
calibration loop between when a run ends and bulk processing begins. Bulk processed data is reviewed and certified
for the ATLAS Good Run List if no problem is detected. Experts maintain the tools used by DQ shifters and the
calibration teams during normal operation, and prepare new conditions for data reprocessing and MC production
campaigns. Conditions data are stored in 3 databases: Online DB, Offline DB for data and a special DB for Monte
Carlo. Database updates can be performed through a custom-made web interface.
| Primary Keyword (Mandatory) | Monitoring |
|---|---|
| Secondary Keyword (Optional) | Data processing workflows and frameworks/pipelines |
| Tertiary Keyword (Optional) | Reconstruction |
