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Key Architecture Elements of a Great Observatory for Space Physics

This article explores the key architectural elements required for a successful observatory in space physics, including distributed data environments, grid services, virtual observatories, data mining, data archive standards, sensor webs, sensor development, scientific modeling, and advanced visualization. It discusses the challenges and solutions in managing the information explosion and understanding complex physical systems in the era of high data rate sensors and intelligent sensor networks.

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Key Architecture Elements of a Great Observatory for Space Physics

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  1. Key Architecture Elements of a Great Observatory for Space Physics Timothy E. Eastman and Kirk D. BorneQSS Group, Inc. & Space Physics Data Facility NASA Goddard Space Flight Center

  2. Distributed, on-line, multi-source/media/format Web-based, machine/application-accessible data archives Registries of products and services Front-end applications Brokers to connect archives to front ends Diverse metadata, emerging standards/ontologies High-order search capabilities Data mining, knowledge discovery tools [Projects: e-Science, cyberinfrastructure, collaboratories, VOs] [examples: NVO, VSO, CDAWeb, VSPO] Distributed Data Environment

  3. Data guidelines (format, archive process) Metadata (content, format, ontologies) Middleware and services (Web Services) Software and systems (marketplace, ISO) Systems architecture (Grids, e-Science) Interoperability

  4. Data & Data Systems as Central to Science • PROBLEMS • Information Explosion • Understanding Multiscale Physical Systems • Solving Complex Systems • New High Data Rate Sensors • Distributed, Intelligent Sensor Networks • SOLUTIONS • Distributed Data Environments • Grid Services • Virtual Observatories • Data Mining • Data Archive Standards • Sensor Web • Sensor Development • Scientific Modeling • Advanced Visualization

  5. Graphic Credit: NASA/GSFC: 2000 Survey of Distributed Spacecraft Technologies and Architectures for NASA’s Earth Science Enterprise in the 2010-2025 Timeframe Sensor WebsDistributed Sensor Systems

  6. Grid Services Communications Fabric Sensor Nodes Computing Nodes Information Storage Nodes • Predictive models, information fusion, data assimilation • Historical archives mined information, metadata Graphic courtesy of Steve Talabac, NASA GSFC

  7. Service Grids, Data Grids, Compute Grids

  8. Grid Frameworks KDDData Mining Knowledge Grid MetadataOntologies Semantic Grid Grid Services Sensor Data Computation

  9. Space Science Informatics as a key enabler of the Heliophysics Great Observatory program

  10. Services Grid (sensor, data, computation)[multi-note, dynamically adaptive grid systems;service oriented architecture (SOA), including Web Services] Semantic Grid[ontologies, metadata] Knowledge Grid[unified schema, data mining, ontology inference layer] Publishing of and access to data through web-enabled end-to-end systems with metadata, software and science results Towards a newSpace Science Informatics see Borne and Eastman, IN51A-05, Fri. 9;30am Key Architecture Elements

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