1. Quality Control B. von Haller 8th June 2015 CERN

2. CWG9 in a nutshell ▶ Started in May 2013 along with O 2 ▶ Group working on ▶ the Data Quality Monitoring ▶ the Quality Assurance ▶ the Visualization  Quality Control (QC) ▶ For Run 2 and Run 3 B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 1

3. CWG9 Members ▶ Renu Bala ▶ Francesca Bellini ▶ Jakob Blomer ▶ Daniele de Gruttola ▶ Mihaela Gheata ▶ Lukasz Graczykowski ▶ Malgorzata Janik ▶ Andreas Morsch ▶ Jeremi Niedziela ▶ Jacek Otwinowski ▶ Ankita Sharma ▶ Maciej Szymanski ▶ Barthélémy Von Haller B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 2

4. Definitions of DQM and QA Data Quality Monitoring & Quality Assurance B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 3 ▶ Feedback on the quality of data ▶ Online (DQM) ▶ Make sure to record high quality data ▶ Identify and solve problem(s) early ▶ Offline (QA) ▶ Make sure to analyze high quality data ▶ Identify high quality runs ▶ Involves ▶ [Online gathering of data] ▶ Analysis by user-defined algorithm ▶ Production of monitoring objects such as histograms ▶ Assessment of the quality of the data based on the objects ▶ Storage of monitoring data ▶ Visualization (+ human assessment of quality)

5. B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 CWG9 Tasks Group focusing on the data Quality Assurance, online and offline, and the visualization of its results as well as of the visualization of the data itself ▶ Run 3 ▶ Study how to monitor data efficiently and in plenty without interfering with the data taking ▶ Discuss QA output and results, incremental QA and procedures to formalize if the results are acceptable or not ▶ Determine the needs, and design the software, to access, visualize the results ▶ Define and develop the software to visualize data, raw and reconstructed ▶ Technical Design Report and prototyping 4 Dataflow Monitoring Object Generation Automatic Quality Assessment Automatic Quality Assessment Storage Visualization

6. B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 QC Servers Possibility to use EPNs or dedicated machines EPNs Synchronous Asynchronous TF Building Data Reduction 1 Detector Reco. Final reconstruction Calibration 2 QC objects Time Frame QC TF QC Compressed TF QC Event QC Compressed TF QC Event QC AOD QC CTF QC Calibration 1 Event Extraction FLPs RAW QC ~1% RAW, Sub-TF QC Repo QC objects + quality Trending Correlation Automatic Checks Mergers Legend O2 Dataflow step QC Task QC objects (e.g. histo) Physics data transport QC Infrastructure QC objects + quality Specific Web App Generic Web Application Specific Web App Specific Web Applications Web Server & REST API ALICE Experiment Extra QC tasks Advanced QC Local Aggregation Extra QC tasks Auxiliary monitoring CTP LHC DCS TF, CTF, AOD ALICE Detectors 5 Time Slicing Data Reduction 0 Calibration 0 RAW QC Sub-TF QC

7. Current and future tasks ▶ Run 3 ▶ QC prototyping ▶ Merging (naive and complex approaches) ▶ Web ROOT gui ▶ Basic functionalities to integrate with first prototype of an FLP (see next slide for details) B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 6

8. EPNs B. von Haller | FLP proto - QC | 03.06.2015 QC Servers Possibility to use EPNs or dedicated machines Synchronous Asynchronous TF Building Data Reduction 1 Detector Reco. Final reconstruction Calibration 2 QC objects Time Frame QC TF QC Compressed TF QC Event QC Compressed TF QC Event QC AOD QC CTF QC Calibration 1 Event Extraction FLPs Time Slicing Data Reduction 0 RAW QC Calibration 0 ~1% RAW, Sub-TF QC Repo QC objects + quality Trending Correlation Automatic Checks Mergers Legend O2 Dataflow step QC Task QC objects (e.g. histo) Physics data transport QC Infrastructure QC objects + quality Specific Web App Generic Web Application Specific Web App Specific Web Applications Web Server & REST API ALICE Experiment RAW QC Sub-TF QC Extra QC tasks Advanced QC Local Aggregation Extra QC tasks Auxiliary monitoring CTP LHC DCS ITS Half layer 7

9. FLPs B. von Haller | FLP proto - QC | 03.06.2015 QC Servers Possibility to use EPNs or dedicated machines ~1% RAW, Sub-TF QC Repo QC objects + quality Automatic Checks Legend O2 Dataflow step QC Task QC objects (e.g. histo) Physics data transport QC Infrastructure QC objects + quality Specific Web App Web Server & REST API ALICE Experiment Extra QC tasks Advanced QC 8 QC functionality for FLP prototype : Get raw data or STF samples locally or from another machine. Process the data, produce histos and send them to central QC infrastructure Check the quality of the histograms Store histos and quality in a repository Display the histos and their quality Time Slicing Data Reduction 0 RAW QC Calibration 0 RAW QC Sub-TF QC Local Aggregation ITS Half layer

10. Current and future tasks ▶ Run 3 (continued) ▶ Actual implementation – 5 areas ▶ Mergers ▶ General Framework and API ▶ Repository ▶ Automatic checkers, correlation, trending ▶ Clients ▶ Event Display - Visualization ▶ Evolve Run 1 and Run 2 ED for Run 3 ▶ Time Frames and Run 3 events as input ▶ Geometry ▶ Total Event Display ▶ Data converters : ESD -> xml/json ; Run3-ESD -> xml/json ▶ Geometry converter : AliRoot -> 3d Studio max B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 9

11. O 2 and detectors schedule B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 10 201520162017201820192020 Today 6/15 ITS half-layer test 1/17 TPC read-out test 4/17 ITS surface test 9/18 TPC RCUs installation CR1 1/19 Data taking Cosmics with core detectors 7/19 TPC pre-commissioning on surface 7/19 TPC commissioning in cavern 1/20 End of commissioning 6/20 O2 system v1 - 1 CRU, 1 FLP, basic data processing, control, logging, QC, monitoring 1/17 O2 system v2 - 1 detector (e.g. ITS) full read-out capability 4/18 10% Data processing and storage HW installation 9/18 90% Data processing and storage HW installation 11/19 Full system ready 2/20 Detectors milestones O2 milestones

12. CWG9 schedule ▶ Q1 2017 ▶ FLP prototype, basic QC: data sampling, general api and framework, some checkers, repository, basic client ▶ Q1 2018 ▶ Mergers (work already started) ▶ Clients (including generic) ▶ Automatic checkers, correlation, trending ▶ Q1 2019 ▶ Fully ready for cosmics ▶ Event Display ▶ Still to be exactly defined, should be ready Q1 2018 ▶ Waiting for data format ▶ Work already started on converter and geometry extraction B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 11

13. Conclusion ▶ CWG9 gathers all QC stakeholders ▶ Requirements and architecture available ▶ Next main milestone is Q1 2017 ▶ Prototyping has started ▶ We are looking for motivated and competent developers to work on the QC framework or on prototyping specific parts B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 12

14. B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 13

15. Past work ▶ Run 2 ▶ Event Display ▶ Run 2 preparation ▶ Run 3 ▶ System Requirements Specifications (SRS) ▶ Delivered ▶ TDR ▶ Architecture and design of the Data Quality Control and Event Display ▶ Defined milestones and required manpower B. von Haller | CWG9 DQM-QA-Visualization | 08.06.2014 14