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DIRC DATA QUALITY DOCUMENTATION

Each subsystem (subdetectors, trigger, PID, Breco and physics) has one expert in the Data Quality Group (DGQ). Its main goal is to assess the quality of the data taken in IR2, either processed or reprocessed(*) in OPR (Online PRocessing).

(*)If the conditions for a given period have improved -- for instance, the first days of running after a shutdown period are processed again once the SVT local alignment and several constants (Bhabha and dE/dx) are computed from the new data -- or if some bugs are found in the release used for the initial processing, a set of runs can be reprocessed.
Reprocessed runs must be checked as carefully as newly processed runs as the new processing can completely screw up data which are initially good (bad release, problems in some DB etc.).

The DQG meets weekly, currently every Thursday at 10.30 am (SLAC time). The meeting is announced in the Data Quality Hypernews to which all DIRC DQG experts must subscribe. This hypernews is used to let the experts know the successive task assigned to the DQG, to report the results of the checks and to exchange information when problems are detected.
Runs are checked on a weekly basis. At least two days before the meeting, the Run Quality Manager (RQM) sends on the hypernews the list of runs whose quality needs to be checked. Such lists are archived in the Stripcharts web page.

How does the data quality check work?

Among the various outputs of the OPR processing (PC or ER) of a run, there is a root file (used to be an hbook file until the 18 series) which contains the monitoring histograms of all subsystems. This root file is automatically processed by a set of ROOT macros which produce a postscript file used by DQG experts to assess the quality of the run.
The DIRC plots cover about a dozen of pages. DIRC specific histograms are defined, filled and processed in the DrcOprMon package.

Obviously, one has no time to check the whole set of plots for each run: there can be several hundred of runs to be checked in the weekly list! Therefore, an automatic monitoring has been setup to decrease dramatically the number of runs whose quality requires a detailled check. The DIRC part of this code was originally written by Malcolm John in a standalone DIRC package. Early 2004, it was moved inside the official RqmRootTreeTools package by Nicolas Arnaud with the help of Xavier Giroux. Several functionnalities were added since then.

Each subsystem defines a list of quantities important for their part of the monitoring. For each processed run, they are computed from the root OPR file and their run-by-run evolution is monitored via stripcharts. For each significant stripchart, a nominal range is defined in the code. If one stripchart goes outside its nominal range, an automated message is generated. All warning messages associated to the same run are gathered together and included in an e-mail which is sent to the relevant expert once the whole list of runs has gone through the automated checks.
Runs which do not fire this monitoring, done via the RqmRootTreeTools package are certainly good. Those which generate some warnings may need to be checked manually by looking at the detailled plots on the postscript files. As all stripcharts are not as important, it is on the expert's judgement (based on his/her experience) to know whether a given run has to be checked or not.

I (Nicolas) am not aware of any run flagged bad by the DIRC which wasn't obviously bad at first look. Of course, this statement does not mean that DIRC QA checks do not require full seriousness and care from the expert. It rather aims at avoiding that a new expert gets worried if it receives quite a lot of warnings the first week. Most (if not all) of these runs are certainly good for physics: just check them to verify that!
Generally speaking, it is better to keep the nominal ranges of the stripchart variables tight. This may lead to several false alarms but should avoid ANY false dismissal.

Once you have reviewed the quality of all the runs, you must summarize your checks by replying to the hypernews sent to the RQM. Even if you have nothing special to report, it is better to go (or to connect to) the DQG meeting to listen to the data taking and processing status and to exchange information with other subsystems. For instance, a problem with the DIRC is likely to decrease the performances of the PID selectors.

Monte Carlo release validations

In addition to the run quality monitoring, the DQG is required to validate the releases which are used to produce Monte-Carlo data -- if you didn't realize this yet, you'll soon understand that BaBar is also a generator of software releases...
For this purpose, MC samples of several decays (from a few kEvents to a few tens of kEvents per mode) are generated and processed in the new release. OPR postscript files are generated and checked to assess the quality of the code. Contrary to the data monitoring, no automated check can be setup for this job: the DIRC histograms do depend on the decay mode! Therefore, the only way to validate a release is to compare the QA plots one by one with those produced in the last validated release for the same SP mode.

As this job is quite time-consuming and can interfere with the weekly checks of runs quality, the Validation Board has been setup end of 2005 to make sure that the DQG wouldn't het overloaded by various tasks ongoing on parallel. For more information on it, see the physics and DQ talks of the December 2005 Collaboration Meeting.


This page is maintained by Nicolas Arnaud
Last significant update: December 15 2005