1. Elder Matias on behalf of CLS Beamline Control and Data Acquisition

2. Challenges We Face? Fiscal Reality (flat-line budgets) Increasing Number of Beamlines More sophisticated/demanding beamline More complex experiments Obsolescence Human Factors Reliability and Availability Stronger Focus on Scientific Results (Papers, HQI, benefit to society)

3. Where we need to go More effectively leveraging what we are doing across our beamlines Making the facility more accessible across the entire experiment life cycle Driving I&C Innovation into the beamlines in a strategic way Exploiting emerging technology Human Factors

4. Where We Are? Mixed Environment: All beamlines are EPICS Based Most beamlines have QT based (IDA, IDEV, etc.) User Centric GUI (Aquaman) ScienceStudio based Remote Control

6. Human Factors Continue to move from device based to task based GUIs Increased layers of abstraction Priority has been tailoring GUI applications to specific beamlines, we now need to look at a common look and feel across the facility

7. Scan Lib Tradition Architect Insert a Scanning Library Slide here.

8. ScienceStudio & ANISE Dylan Maxwell, Dong Liu, Dioni Medrano and partners Developed through in collaboration with partners at CLS, Western, IBM, LNLS, and ALS. Uses: –REST & MQ. –HPC –Steams

9. Aquaman David Chevrier, Mark Boots, Daren Hunter Integrate Experiment & Visualisation Platform Qt based

10. User Experiment Lifecycle

11. Overview of User Cases

12. High-level Data Model Terminology Facility = CLS Laboratory = Beamline Instrument = Endstation Project = Proposal

13. Sequence

14. Software Stack Network and Directory Services Machine Protection Modbus IOC Services Gateway ServicesArea Detector Drivers (Detector, IOC Control EPICS Connect Qt EPICS Qt Devices EPICS PyQt EDM CA Connect AM - Scan CSS BEAST SS Meta Data Store Data Man PyEDM CDMA MPlot AM - Technique SS Portal AM - GUIBL GUI

15. µTCA Conventional technology is VME (320 MB/s) or Compact PCI (528 MB/s) Working with Instrumentation Technology on µTCA (5 GB/s) beamline data acquisition solution

16. Where we need to go More effectively leveraging what we are doing across our beamlines Making the facility more accessible across the entire experiment life cycle Driving I&C Innovation into the beamlines in a strategic way Exploiting emerging technology Human Factors