1. More speed, more data, more automation, more work? Alun Ashton

2. Thanks to organisers.

3. 1.75+ million man-hours 2,100 tons of steel 35,000 m 3 of concrete 33,000 m 2 of roofing Joint venture company between CCLRC (86%) and Wellcome Trust (14%) Electron Beam Energy3 GeV Circumference561.6 m Diameter of outer wall235 m Beam current300 mA(500 mA) Start March 2003: Users January 2007 Diamond Light Source

4. Beamlines

5. Computing at Diamond. Data Acquisition and Scientific Computing Controls IT support External groups

6. Scientific Computing Data Analysis Data Visualisation eScience Data Curation Data Acquisition Automation Simulation And Theory

7. Macromolecular Crystallography computing at Diamond Phase I (2007) 3 MX (0.5 – 2.5 Å optimised for 0.98Å) with double crystal monochromator, Kirkpatrick Baez horizontal and vertical focusing mirrors; Focal spot size ~ 94  m (h) x 17  m (v) (FWHM); estimated flux at 12.6 keV 3.5 x 10 12 ph/s; fully automated sample handler; cryo cooling; CCD detector. One station will have containment three facility for pathogenic samples Phase II Microfocus beam line Fixed wavelength side station (0.96 Å) (MR & ligand binding studies) Long wavelength side station for Sulphur anomalous (1.5 – 2.5 Å)

8. More speed

9. MX computing at diamond on the beamline On each of the 3 Beamlines 2 CPU server for Data Acquisition 2 CPU server for Data Analysis 20Tb (RAW) beamline storage 1 read and 1 write server (Approx 1 month data storage) 4 Beamline user workstations per beamline: 3 RedHat Linux, (2 with dual monitors) 1 windows XP 1 in hutch computer similar to tablet PC with touch screen. Networking is 1 GBit on beamline and 10 between MX beamlines and MX “near” beamline computers.

10. MX computing at diamond “near” the beamline 180 Tb (RAW) secondary MX storage (shared between 3 Phase 1 beamlines, approx 3 months data storage) Administered by 8 servers 24 dual dual (2x2) core CPU Cluster (50% infiniband fast interconnects Running Sun Grid Engine queuing system) Local user backup via USB and Firewire drives (small scale CD and DVD writing facilities available) CCLRC Atlas Data Store – Petabyte data storage Long term data storage and backup:

11. Near Beamline computing Crunchie the cluster

12. Where does everything fit? Synchrotro n Crystallization PIMS (Protein Production) Data Processing & Structure Solution Pipelines CollectionDB e-HTPX

13. More data

14. PiMS www.pims-lims.org Thanks to Chris Morris and PiMS developers

15. General Introduction

16. www.pims-lims.org Why is Data Modelling Important? ■A Data Model is a plan for building a database ■detailed enough to be used to create the physical structure ■simple enough to communicate to the end user the data structure ■The Unified Modelling Language (UML)

17. www.pims-lims.org Database ■Record keeping is an important aspect of most business today ■A stable and clean repository of data ■Constraints to enforce data integrity ■Open interface ■Allow users to access, search and retrieve data easily ■Multiple concurrent access ■Extensible ■New data added ■Maintainable ■Database provides maintenance tools, plus industry standards to ensure long-term compatibility ■Robust ■“industrial strength”

18. www.pims-lims.org Scientific goals ■Recording laboratory information ■A lot of data keeping ■10,000s of experiments ■1,000,000s of samples ■Data interchange and interoperation ■Collaboration in protein production ■Share data between stages and sites ■Data transfer to beamline or NMR ops ■Data mining and reporting ■Analysis ■Negative results can be mined to improve methods ■Scientific publications ■Data deposition ■All made feasible by data model ■… plus common understanding of it

19. www.pims-lims.org Acknowledgements ■PiMS developers ■Chris Morris (CCP4) ■Ed Daniel (Daresbury) ■Peter Troshin (MPSI) ■Bill Lin (CCP4) ■Jo van Niekerk (SSPF) ■Susy Griffiths (YSBL) ■Jon Diprose (OPPF) ■Marc Savitsky (OPPF) ■Anne Pajon (EBI) ■Crystallization developers ■Ian Berry (OPPF) ■Gael Seroul (EMBL- Grenoble) ■Diederick de Vries (NKI-Amsterdam) ■Sabrina Haquin (Paris) ■CCPN developers ■Wayne Boucher ■Rasmus Fogh ■Tim Stevens ■Wim Vranken

20. What does ‘PiMS’ mean for diamond and diamond users?

21. Synchrotron data

22. Image format

23. Images off the beamlines ADSC Q315 –ADSC image size – 20-80Mb –ADSC image rate - <>60Mb/second ImgCIF/CBF –30% size of ADSC uncompressed images NeXus

24. imgCIF/CBF ADSC header HEADER_BYTES= 512; DIM=2; BYTE_ORDER=little_endian; TYPE=unsigned_short; PIXEL_SIZE=0.1026; BIN=2x2; ADC=fast; DETECTOR_SN=922; DATE=Fri Sep 15 10:07:46 2006; TIME=1.00; DISTANCE=250.000; OSC_RANGE=1.000; PHI=0.000; OSC_START=0.000; TWOTHETA=0.000; AXIS=phi; WAVELENGTH=1.0000; BEAM_CENTER_X=10.000; BEAM_CENTER_Y=20.000; CREV=1; CCD=TH7899; BIN_TYPE=HW; ACC_TIME=1781; UNIF_PED=1500; IMAGE_PEDESTAL=40; SIZE1=3072; SIZE2=3072;

25. Synchrotron and Beamline Beam conditions: ring energy and current Beam size Attenuation If available, estimate of photon flux coming out of the collimator. Backstop type, size and position wrt sample Date and time Detector type and serial number Goniostat (manufacturer and model) Method of sample mounting (by hand, arcs/tongs or by robotics (type)) Temperature of sample Sample code (barcode ?) Text field to allow any special comments relevant to this experiment to be stored. eg If crystal has been annealed, and if so, what the conditions were. Has the crystal been cryocooled in a capillary etc

26. Record the mode the synchrotron is running in. Attenuation - this should be a calculated factor Photon flux + error. Maybe an intensity reading A record of an experiment number, this would give us the link back to everything else e.g. user etc. An image of the crystal, with the cross hairs marking the beam and beam size? Beam size at sample and beam size on detector.

27. NeXus All diamond data collection runs will produce NeXus files NeXus will serve as a longer term data storage format.

28. More automation

29. Joint collaboration between Daresbury SRD and Diamond. GDA sits ‘above’ EPICS which wich does the majority of low level/component/compound motion control. Generic Data Acquisition (GDA)

30. Design considerations A single software framework which can be applied to all beamlines Must be flexible \ adaptable – “plug and play” –must work with both EPICS and non-EPICS hardware –highly configurable system: different GUIs and hardware on different beamlines, but all work within the same overall architecture Similar look and feel across all beamlines –users can visit different beamlines without learning new software every time A single window to operate the beamline Framework defines more than just code: includes programming methodologies, coding conventions etc. Result is a system which is simpler and easier to maintain

31. Experiment automation automateD collectioN of datA – DNA –Automated strategy calculation using BEST –Multi crystal ranking and data collection –Automated autoindex with Mosflm –Automated integration with Mosflm –Quick Scaling results for data quality –Basic radiation damage consideration –Data reading and writing into beamline database –MiniKappa incorporation with STAC

32. DNA Acknowledgements –Cambridge -MRC –Diamond –EMBL Grenoble –EMBL Hamburg –ESRF –GlobalPhasing –Soleil –SRD Daresbury –Brookhaven –Users DNA 2.0…..

33. ISPyB Management of experimental data produced in protein crystallography Management of experiment related information (shipping of samples, beam time allocation, safety information…) Tracking your progress through the experimental process: –Retrieves information from DataCollection automatically –Stores both Beamline and Experimental information –Allows disparate groups to monitor projects –Communicates with other systems (Sample Changer, DNA, …) –Portable Interface (using PDA + wireless DataMatrix reader) to track Samples –User friendly web interface –Custom interface and access restricted based on privileges –Generates report

34. 23/11/2005 http://ispyb.esrf.fr ISPyB: Webservice or web based user interface … Webservices available for: Crystal details Shipment Diffraction and Screening plan Diffraction results

35. 23/11/2005 http://ispyb.esrf.fr Solange Delageniere Ricardo Leal Darren Spruce Dominique Porte & MIS Group Lilian Cardonne Matias Guijarro Olof Svensson Jose Gabadinho Collaboration to develop joint system ISPyB & associated BM14 eHTPX eHTPX members and associated collaborations Ludovic Launer Martin Walsh Hugo Caserotto Max Nanao Jean_Baptiste Reiser Hassan Belrhali Laurent Geoffroy (Maatel) David Stuart, Robert Esnouf Oxford, Colin Nave, Rob Allan, Martyn Winn, Daresbury, Kim Henrick EBI, Kevin Cowtan York, Martin Walsh Grenoble DEVELOPERS: Chris Mayo, Ian Berry (Oxford) Graeme Winter, Ronan Keegan, David Meredith (Daresbury) Joel Fillon (EBI), Paul Young (York), Ludovic Launer (Grenoble) Florent Cipriani Franck Felisaz Jean-Sebastien Aksoy Bernard Lavault Arnaud Clere Julien Huet S. Cusack

36. Where does everything fit? Synchrotro n Crystallization PIMS (Protein Production) Data Processing & Structure Solution Pipelines CollectionDB e-HTPX

37. Remote data collection Remote data monitoring –ISPyB Remote experiment monitoring –ISPyB Remote experiment control –GDA –VNC eInfrastructure!

38. 10 second pause

39. How do MX ‘legacy’ projects bespoke solutions fit into a bigger picture? More work!

40. e-Science Infrastructure for Diamond Light Source

41. Phase 1 Single Sign On Automatic cataloguing of data and metadata relating to a scientific experiment. Backup all Diamond’s data to the Atlas Data Centre for long term storage. Be able to view and retrieve your data. Works in conjunction with Diamonds current computing infrastructure. Backbone for further e-Science work

42. Single Sign On

43. GDA DDH StorageD Data / metadata Nexus File & Data DUO DUO Desk IKitten DLS ICAT SRB People DB Active Directory Diamond, CICT Modified by e-Science DataPortal Diamond Proposal Web pages Atlas Data Store

44. GDA DDH StorageD Data / metadata Nexus File & Data DUO DUO Desk IKitten DLS ICAT SRB People DB Active Directory Diamond, CICT Modified by e-Science DataPortal Diamond Proposal Web pages Atlas Data Store

45. SRB in practice

46. What Next? Work towards live collection of data on Beamlines. Gain operational experience. Have a consultation period with scientist to get feedback on the work and input into what metadata to collect. Work closer with science community to understand what metadata best describes the experiments. Add analytical framework.

47. What's really next? More work! Plenty of software to demonstrate

48. Acknowledgements