1. The Earth System Grid: A Visualisation Solution
Gary Strand

2. Introduction

3. Acknowledgments ESG Development Team PI’s Veronika Nefedova (ANL)
Ann Chervenak (ISI/USC)
Carl Kesselman (ISI/USC)
David Bernholdt (ORNL)
Kasidit Chanchio (ORNL)
Line Pouchard (ORNL)
Alex Sim (LBNL)
Arie Shoshani (LBNL)
Bob Drach (LLNL)
Dave Brown (NCAR)
Gary Strand (NCAR)
Jose Garcia (NCAR)
Luca Cinquini (NCAR)
Peter Fox (NCAR)
PI’s
Ian Foster (ANL)
Don Middleton (NCAR)
Dean Williams (LLNL)

4. Current Practices Scientist (or others) wants a visualisation
Visualisation person gets appropriate data after verifying with data manager as to the name, location, total size, etc.
Data moved to “local” machine that has visualisation tools
Visualization created on “local” machine
Hopefully, someone remembers to archive the visualisation

5. Simple Vis Example

6. Problems in the process
What if the data cannot be found (e.g. we have 1.2 million files, 73 TB of data), or the data manager is unavailable?
What if there isn’t enough disk space or sufficient other resources?
What if a better visualisation tool is located elsewhere?
What if the visualisation should be shared?
What if the visualisation is lost?
ESG is part of the answers to these questions

7. What is ESG? ANL: Computational grids, & grid-based applications
LBNL: Climate storage
facility
LLNL: Model diagnostics
& inter-comparison
USC/ISI: Computational grids,
& grid-based applications
NCAR: Climate change
predication and scenarios
LANL: Next generation
coupled models & computing
ORNL: Climate storage &
computational resources

8. ESG Architecture LBNL ANL NCAR LLNL ORNL ISI
HPSS
High Performance
Storage System
disk
ANL
CAS
Community Authorization Services
NCAR
SRM
Storage Resource
Management
gridFTP
Striped
server
gridFTP
server
openDAPg
server
Tomcat servlet engine
MyProxy
server
LLNL
disk
MCS client
MyProxy client
CAS client
RLS client
SRM
Storage Resource
Management
Note the many services needed to build such a Grid.
gridFTP
server
GRAM
gatekeeper
gridFTP
server
ORNL
gridFTP
SRM
Storage Resource
Management
ISI
gridFTP
gridFTP
server
SRM
Storage Resource
Management
MCS
Metadata Cataloguing Services
SOAP
HPSS
High Performance
Storage System
RLS
Replica Location Services
RMI
MSS
Mass Storage System
disk
disk

9. Solutions Metadata catalogue service (MCS)
What happens when data cannot be found, or the data manager is unavailable?
Metadata catalogue service (MCS)
Replica location service (RLS)

10. MCS and RLS and Metadata Services
EXTRACTION
DISPLAY
BROWSING
QUERY
ESG CLIENTS API
& USER INTERFACES
Data &
Metadata
Catalog
Dublin Core
Database
COARDS
mirror
XML Files
COMMENTS
METADATA HOLDINGS
ANNOTATION
VALIDATION
METADATA ACCESS
(update, insert, delete, query)
SERVICE TRANSLATION
LIBRARY
CORE METADATA SERVICES
AGGREGATION
DISCOVERY
METADATA & DATA
REGISTRATION
PUBLISHING
HIGH LEVEL METADATA SERVICES
SEARCH & DISCOVERY
ADMINISTRATION
BROWSING & DISPLAY
ANALYSIS & VISUALIZATION

11. Solutions (contd.) Hierarchical Resource Manager (HRM)
What if there isn’t enough disk space or sufficient other resources?
Hierarchical Resource Manager (HRM)

12. HRM

13. Solutions (contd.) Distributed visualization
What What if a better visualization tool is located elsewhere?
Distributed visualization

14. CDAT Example of an ESG Script Access
The next-generation language, Python, is used to access the Earth System Grid (ESG) at LLNL
Import cdms, vcs
db = cdms.open(“ldap://localhost:389/database=demo,ou=PCMDI,o=LLNL,c=US”)
f = db.open( “ncep_reanalysis_mo”)
ds = f(‘ts’)
x=vcs.init( )
x.plot(ds)

15. CDAT: Example of an ESG GUI Client Access

16. Solutions (contd.) What if the visualization should be shared?
Access Grid plus Visualisation Tool

17. Collaborative Environments
Science Portals + AccessGrid:
University of Michigan (Knoop, Hardin)
Vegetation & Ecosystem Mapping Program (VEMAP)
NCAR/SCD VETS/KEG
Argonne National Labs

18. Conclusions
Visualisation can require as many services and resources as the initial computation
Many sites do not offer sufficient resources for the visualisations earth sciences require
ESG provides, and will provide, the tools that enable visualisation on a grander scale

19. Conclusions (contd.)
ESG tools enable better data access, better data knowledge, and the processes of collaboration for the needs of investigating, visualising, and learning