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Cyberinfrastructure for Environmental Observing Systems

Cyberinfrastructure for Environmental Observing Systems. Chaitan Baru Director, Science R&D San Diego Supercomputer Center. “CYBERINFRASTRUCTURE” What do we mean?. Technologies to bring remote resources together. e-science. Social aspect: bringing multidisciplinary groups together.

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Cyberinfrastructure for Environmental Observing Systems

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  1. Cyberinfrastructure for Environmental Observing Systems Chaitan Baru Director, Science R&D San Diego Supercomputer Center

  2. “CYBERINFRASTRUCTURE”What do we mean? • Technologies to bring remote resources together e-science Social aspect: bringing multidisciplinary groups together

  3. Environmental Observing Systems • A major area of emphasis for NSF, and other agencies (e.g. GEOSS) • LTER, www.lternet.org • NEON, www.neoninc.org • ORION, www.orionprogram.org • Waters Network • CUAHSI HIS, www.cuahsi.org/his • CLEANER, cleaner.ncsa.uiuc.edu • EarthScope, www.earthscope.org • And many other efforts…(NEES, www.neesinc.org), etc. • Number of established efforts at other federal and state agencies • USGS, EPA, DOE, …

  4. Example of a Cyberinfrastructure Project GEON: Geosciences Network(www.geongrid.org) • Funded by NSF IT Research program (~$11.5M) • Multi-institution collaboration between IT and Earth Science researchers • GEON Cyberinfrastructure provides: • Authenticated access to data and Web services • Registration of data sets and tools, with metadata • Search for data, tools, and services, using ontologies • Scientific workflow environment • Data and map integration capability • Scientific data visualization and GIS mapping

  5. Key Informatics Areas • Portals • Authenticated, role-based access to cyber resources: data, tools, models, model outputs, collaboration spaces, … • Data Integration • Search, discover and integrate data from heterogeneous information sources (“mediation” and “semantic integration”) • Modeling and simulation environments based on “scientific workflow” software • Users can “program” and steer computations at a higher level of programming abstraction • Share models (not only data), and support generation and sharing of provenance information • Geospatial information and Geographic Information Systems (GIS) • Spatial statistics, spatiotemporal data mining • Visualization of 2D, 2.5D, 3D, 4D data, and multidimensional information spaces

  6. GEON: International Component • India • Collaboration with University of Hyderabad • Profs. K.V. Subbarao & Arun Agarwal • Deploying a GEON Node at UofHyd and an India-based portal • Conducted GEON Cyberinfrastructure Workshop, Oct. 2005 • Recently announced as a Knowledge Networked R&D Center by Indo-US Science and Technology Forum • Will partner with institutions like NGRI, INCOIS, Wadia Institute of Himalayan Geology (WIHG), Birbal Sahni Institute of Paleo-Botany (BSIPB) • China • Collaboration with Chinese Academy of Sciences, Beijing • Dr. Yaolin Shi, Director, Chinese Geodynamics Lab, Dr. Baopin Yan, Dir, CNIC • GEON Cyberinfrastructure Workshop, July 20-23, 2006, Beijing. • Deploy GEON node & a Linux cluster for developing parallel geodynamics codes • Japan • Collaboration with AIST, Tokyo • Dr. Satoshi Sekiguchi • Initiating a GEOGrid in Japan. Inauguration in early October, 2006 • Will make various remote sensing data available via GEON.

  7. Analyze/ Interpret LiDAR Data Processing Meeting in August with USGS EROS Data Center to make continental-scale datasets open to NEON, GEON, and hazards user communities • Current implementation • 32 IBM P690 1.7GHz processors, 128GB, 8TB SAN • ~2TB point cloud data, ~6B rows in database • ~20TB orthophotos • Migrating to… • 16-way Linux cluster, 64-bit Intel processors to support… • Central warehouse and replicas for failover and load balancing, and • On-demand access & analysis of data Survey Process & Classify R. Haugerud, U.S.G.S D. Harding, NASA Point Cloud Interpolate/Grid Point Cloud x, y, zn, … Courtesy: Chris Crosby & Prof. Ramon Arrowsmith, Arizona State

  8. NEON Infrastructure Overview

  9. NEON Sensornet-level Cyberdashboard 1 1 2 2 3 3 4 4 16 15 14 20 11 12 11 10 17 13 16 10 18 16 14 13 17 12 18 20 19 15 19 9 9 8 8 7 7 6 6 5 5

  10. GridSphere Kepler, Custom portlets Portal Pub/Sub (Apache AXIS WS) Workflows Services Data Turbine, EmStar, Antelope, SRB, Surge,ESS2 Admin and Control Analysis and Visualization Data Management TinyDB, ESS2 Real-time Distributed Instrument Control Sensors Definition of standard interfaces Sensornet Software Stack Courtesy: Tony Fountain, Neil Cotofana, SDSC

  11. Sensor Sensor Sensor Sensor Portal Services Services RTD Instr. Ctl. RTD Instr. Ctl. RTD Instr. Ctl. RTD Instr. Ctl. *** *** *** *** Workflows Admin / Ctl. Admin / Ctl. MicroNet Node MicroNet Node MicroNet Node MicroNet Node Sensor Sensor Sensor Sensor Data Mgmt. Data Mgmt. Portal Server RTD Instr. Ctl. RTD Instr. Ctl. Workflows Well-endowed Node Well-endowed Node Services Analysis / Vis. Analysis / Vis. Server Services Data Mgmt. Data Replication / Archiving Server E.g. NEON Site SensorNet Logical Infrastructure User (BioPDA) User (web) … … Sensor MicroNet (e.g. Soil) … … … Sensor MicroNet (e.g. Climate) Courtesy: Tony Fountain, Neil Cotofana, SDSC

  12. Opportunities • Exploit national high-speed networking, e.g. Garuda, to ensure easy and efficient access to online (cyber) resources • Leverage GEON cyberinfrastructure in collaboration with UofHyd/UCSD • Keep in step with NEON cyberinfrastructure • Provide well-defined interfaces to metadata, data, and instruments • Create a true collaboration between scientists and computer scientists and IT researchers • Promote e-science • Engage the next generation of scientists • Lobby for NSF-India office (similar to NSF Beijing)

  13. Thanks!

  14. How do we combine data, knowledgeand information management with simulation and modeling? Applications: Medical informatics, Biosciences, Ecoinformatics,… Visualization How do we represent data, information and knowledge to the user? Data Mining, Simulation Modeling, Analysis, Data Fusion How do we detect trends and relationships in data? Knowledge-Based Integration Advanced Query Processing How do we obtain usableinformation from data? Grid Storage Filesystems, Database Systems How do we collect, accessand organize data? How do we configure computer architectures to optimally support data-oriented computing? High speed networking Networked Storage (SAN) sensornets instruments Storage hardware HPC Data, Informatics and Cyberinfrastructure integration

  15. NEON Visualization and Forecasting Facility NEON Data Replica Access to TeraGrid Visualization Displays (“Synthesis Center”) Internet 2 NEON Data Center Compute Cluster w/ disk Data from NEON District-level PoP’s Processing nodes Geographically Remote archival copy . . . . . . SAN Raw data, Derived products Archival Storage

  16. NEON Portal provides Authenticated access to NEON sensor data, metadata, and derived prodcuts; Web services; sensor command and control Access to NEON forecasts and models via scientific workflow environments Data and map integration capability Visualization and GIS mapping NEON “Cyberdashboard” (Portal)

  17. Portal Workflows Services Admin and Control Analysis and Visualization Data Management Real-time Distributed Instrument Control Sensors A Proposed Open Systems Sensor Network Software Stack Courtesy: Tony Fountain, Neil Cotofana, SDSC

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