Research Cyberinfrastructure: Research Cyberinfrastructure: Virtual Organizations, Data and Virtual Organizations, Data and Visualization Visualization Chaitan Baru Chaitan Baru San Diego Supercomputer Center San Diego Supercomputer Center UC San Diego UC San Diego
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Research Cyberinfrastructure: Virtual Organizations, Data and Visualization Chaitan Baru San Diego Supercomputer Center UC San Diego.
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Research Cyberinfrastructure: Research Cyberinfrastructure: Virtual Organizations, Data and Virtual Organizations, Data and
VisualizationVisualization
Chaitan BaruChaitan BaruSan Diego Supercomputer CenterSan Diego Supercomputer Center
UC San DiegoUC San Diego
OutlineOutline
Virtual Organizations and Data SharingVirtual Organizations and Data Sharing
PortalsPortals
Visualization and CyberdashboardsVisualization and Cyberdashboards
Collaboration, and the Socio-technical Collaboration, and the Socio-technical InfrastructureInfrastructure
Some VO ProjectsSome VO Projects
BIRN, BIRN, www.nbirn.net (NIH) www.nbirn.net (NIH) – Biomedical Informatics Research Network– VO for sharing neuroscience imaging data
NEES, www.nees.org, NEES, www.nees.org, it.nees.org (NSF)it.nees.org (NSF)– Network for Earthquake Engineering Simulations– VO for sharing earthquake engineering experiment and simulation data
GEON, www.geongrid.org (NSF) GEON, www.geongrid.org (NSF) – Geosciences Network– VO to facilitate integration of earth sciences data
TEAM, www.teamnetwork.org, (Moore/Conservation TEAM, www.teamnetwork.org, (Moore/Conservation International) International) – Tropical Ecology, Assessment and Monitoring– VO for sharing field ecology data from wildland sites in the tropics
More VO Projects…More VO Projects…
GLEON, www.gleon.org (Moore, NSF)GLEON, www.gleon.org (Moore, NSF)– Global Lake Ecology Observation Network– VO for sharing lake ecological data
TDAR, www.tdar.org (NSF) TDAR, www.tdar.org (NSF) – The Digital Archaeological Record– Sharing of data from different digs
MOCA, moca.anthropogeny.org (Mathers, UCSD)MOCA, moca.anthropogeny.org (Mathers, UCSD)– Museum of Comparative Anthropogeny– Creation of a phenomic information resource for investigating the origin of humans
Many others…in high energy physics, astronomy, Many others…in high energy physics, astronomy, climate/atmospheric research, hydrology, ecology, climate/atmospheric research, hydrology, ecology, biomedicine, emergency response, …biomedicine, emergency response, …
Cyberinfrastructure at the speed of Cyberinfrastructure at the speed of researchresearch
In some cases, “do what it takes” to keep upIn some cases, “do what it takes” to keep up– Take shortcuts– Leverage infrastructure from other CI projects and off-the-shelf
products– Difficult because
• Can be stressful on software developers who take pride in creating their own
• Software engineers may think PI is changing course too many times
In other cases, “don’t get too far ahead” of the usersIn other cases, “don’t get too far ahead” of the users– User community may see no apparent benefit to the
infrastructure being developed• And, therefore, become frustrated and may stop using the system
entirely
““Community data” and the nature Community data” and the nature of data sharingof data sharing
Physics:Physics:– Petabytes of data from the same detector, shared by a global research
community. Common physics model.
Astronomy:Astronomy:– Petabytes of digital data from the same telescopes, shared by a global research
community. Common astrophysics model.
Biomedicine:Biomedicine:– 100’s terabyte to several petabytes of digital imaging data about the same
human organ (e.g. brain) from different individuals. Common organ model.
Earth Science (e.g. geophysics):Earth Science (e.g. geophysics):– 10’s-100’s Terabytes of seismic sensor data and tomographic image data,
shared by a global research and hazards response and policy community. Common Earth model.
““Community data” and the nature Community data” and the nature of data sharingof data sharing
Ecology:Ecology:– 10’s of terabytes of sensor and field ecology data. There may be
common models at local and regional scale. What is the common model at continental and global scale?
ArchaeologyArchaeology– Megabytes to terabytes of data from archaeological digs. What is the
common model? The data may be the model.
Social SciencesSocial Sciences– Sharing data from surveys of small populations
– Share data or share models? What is the metadata for models? Is there a way to “normalize” the data, e.g. basic steps such as creating grids from non-gridded data
Portal-based Science EnvironmentsPortal-based Science Environments Support for resource sharing and collaborationsSupport for resource sharing and collaborations
GEON PortalGEON Portal
GEON Portal and Cyberinfrastructure provide:GEON Portal and Cyberinfrastructure provide:– Authenticated access to data and Web services– Registration of data sets, tools, and services with metadata– Search for data, tools, and services, using ontologies– Scientific workflow environment and access to HPC– Data and map integration capability– Scientific data visualization and GIS mapping
Software: E.g. OpenEarth Framework Software: E.g. OpenEarth Framework Interactive Visualization of 3D/4D earth science data Interactive Visualization of 3D/4D earth science data
–Derived 3D volumetric model–Multiple isosurfaces, with different transparencies–Slices through the volume–Variable gridding: data typically has lower resolution at greater depths
–2D surface data: Satellite imagery, street maps, geologic maps, terrain surface, fault lines, and other derived features etc.
–Bore hole or well data
“For a given region (i.e. lat/long extent, plus depth), return a 3D structural model with accompanying physical parameters of density, seismic velocities, geochemistry, and geologic ages, using a cell size of 10km”
Facility: E.g. SDSC / Calit2 Facility: E.g. SDSC / Calit2 Synthesis CenterSynthesis Center
Conceived as a collaboration space “to do” scienceConceived as a collaboration space “to do” science– Bring together …
• High-performance computing
• Large-scale data storage
• In-person collaboration
• Technical professionals to move projects forward
Face-to-face collaborationsFace-to-face collaborations– Are important, even in a “flat world” where distance is
disappearing…
Synthesis Center FacilitySynthesis Center Facility
Large meeting spaceLarge meeting space
Multiple display Multiple display devicesdevices
Private conference Private conference room with high room with high resolution projection resolution projection systemsystem
A variety of usesA variety of uses
Viz-oriented workshopsViz-oriented workshops– GEON Visualization workshop– Workshop on Visualization of Large
Biomolecular Complexes– Tsunami Recon Data Workshop– GEON Workshop on Constructing, Editing,
and Visualizing Integrated models of Earth Structure
– GEON Digital Acquisition Workshop: From hand-held computers to ground-based LIDAR
Classes / Hands-onClasses / Hands-on– UCSD Digital Photo Class– GEON Summer Institute– NBCR Summer Institute– GEON Portal Usability Workshop– NEES IT Managers’ Retreat
MeetingsMeetings– SEEK All-Hands Meeting– NEON CI Planning Workshop– The NEURON Simulation Environment– Metagenomics 2006– BIRN All-Hands Meeting– Information Theory and Applications
Workshop– ORION Coastal/Global RFP meeting– Geoinformatics 2007– Governor’s Broadband Taskforce Meeting– Moore Foundation Annual Marine
Microbiology Investigator Symposium
Site VisitsSite Visits– NEESit NSF Site Visit– LOOKING NSF Review Meeting– Calit2 UCOP Review– NEON NSF Conceptual Design Review
Staffing and FundingStaffing and Funding
StaffingStaffing– Technical Support Staff– Research Staff: Visualization, Data Integration,
Analysis, Data Mining– Coordination
FundingFunding– “Project-based” funding: Staff funded by research