The Open Science Data Cloud is a hosted, managed, distributed facility that allows scientists to manage and archive medium and large datasets, provide computational resources to analyze the data, and share the data with colleagues and the public. It currently consists of 6 racks, 212 nodes, 1568 cores and 0.9 PB of storage across 4 locations with 10G networks. Projects using the Open Science Data Cloud include Bionimbus for hosting genomics data and Matsu 2 for providing flood data to disaster response teams. The goal is to build it out over the next 10 years into a small data center for science that can preserve data like libraries and museums preserve collections.

1. Open Science Data Cloud April 13, 2011 Robert Grossman Open Cloud Consortium University of ChicagoOpen Data Group

2. Open Science Data Cloud Astronomical data Biological data (Bionimbus) NSF-PIRE OSDC Data Challenge Earth science data (& disaster relief)

3. Who are we?

5. Manages cloud computing infrastructure to support scientific research: Open Science Data Cloud.

6. Manages cloud computing testbeds: Open Cloud Testbed.

7. Develop reference implementations, benchmarks and standards.www.opencloudconsortium.org

8. OCC Members Companies: Cisco, Citrix, Yahoo!, … Universities: University of Chicago, Northwestern Univ., Johns Hopkins, Calit2, ORNL, University of Illinois at Chicago, … Federal agencies: NASA International Partners: AIST (Japan) Other: National Lambda Rail Beginning to add international partnersin 2011. 5

10. 10G networks

11. 450+ nodes

12. 3000 cores

13. 2 PB

14. Build a data center for science

15. 6-10 locations

16. 100G networks

18. Variety of analysis Scientist with laptop Wide Open Science Data Cloud Med High energy physics, astronomy Low Data Size Medium to Large Small Very Large Dedicated infrastructure No infrastructure General infrastructure

19. Persistent data Large data clouds Med databases HPC Small Cycles Large & spec. clusters Small to medium clusters Single workstations

20. What is the Open Science Data Cloud?

21. Hosted, managed, distributed facility to: Manage & archive your medium and large datasets Provide computational resources to analyze it Provide networking to share it with your colleagues and the public.

22. Long Time Goal Build a (small) data center for science.

23. And preserve your data the same way that libraries preserve books & museums preserve art.

25. Operate infrastructure at the scale of a small data center

26. Interoperate with public clouds

27. Open, interoperable architecture

28. Experiment at scale

30. Project 1. Bionimbus www.bionimbus.org

31. Case Study: Public Datasets in Bionimbus

32. What Could You Do With 1 PB of Genomics Data? The NIH in the U.S. currently makes available for download approximately 2PB of data. Bionimbus today consists of 6 racks, 212 nodes, 1568 cores and 0.9 PB of storage. We plan to add approximately 1 PB of genomics and other data from the biological sciences to Bionimbus in 2011.

33. Case Study: ModENCODE Bionimbus is used to process the modENCODE data from the White lab (over 1000 experiments). BionimbusVMs were used for some of the integrative analysis. Bionimbus is used as a backup for the modENCODE DCC

34. Project Matsu 2: An Elastic Cloud For Disaster Response Daniel Mandl - NASA/GSFC, Lead 20

36. River gauges displayed as small circles

37. Detailed measurements are available on the display by clicking on the river gauge stations.Zambezi basin consisting of upper, middle and lower catchments 21

38. Project 3: OSDC PIRE Project

40. Cloud middleware for data intensive computing

41. Wide area clouds

42. Training and education workshops

43. Data intensive computing using the OSDC

44. Cloud computing for scientific computing

45. Outreach

47. Beijing Institute of Genomics (BIG)

48. Edinburgh University

49. Korea Institute of Science & Technology

50. San Paulo State University

51. Universidade Federal Fluminense, Brasil

54. Wide area clouds

55. Continuous learning

57. Send one of your graduate students to hands-on Workshops, such as Introduction to Data Intensive Computing

58. Submit your most impressive dataset to the OSDC Data Challenge

60. Towards a Long Term, Sustainable Model Capital Exp about $1M/year Operating Exp about $1M/year Moore Foundation providing $1M/year for 2011 and 2012 to support the Cap Exp.

61. Who do you most trust to manage your data for 100 years? Companies may not be here tomorrow. Government agencies have a role, but not always easy to use. Think of a not for profit with that mission.

62. Buy A Container and Join the OCC Use 2/3 of the container for your own purposes. Provide 1/3 of the container to the OCC for a share replica space.

63. To Get Involved Join the Open Cloud Consortium: www.opencloudconsortium.org

64. Questions?