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Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
Scientific Data and Knowledge Management in Aerospace Engineering
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Scientific Data and Knowledge Management in Aerospace Engineering

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Korea e-Science AHM 2008 (September 8th 2008, Daejeon)

Korea e-Science AHM 2008 (September 8th 2008, Daejeon)

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  • 1. Scientific Data and Knowledge Management in Aerospace Engineering Korea e-Science AHM 2008 (September 8th 2008, Daejeon) Andreas Schreiber <Andreas.Schreiber@dlr.de> German Aerospace Center (DLR), Cologne http://www.dlr.de/sc Folie 1 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 2. Outline German Aerospace Center (DLR) Introduction Excurse: DLR CFD Codes Grid Computing: D-Grid and AeroGrid Software Tools: DataFinder, RCE, and XPS4CFD Conclusion Folie 2 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 3. The DLR German Aerospace Research Center Space Agency of the Federal Republic of Germany Folie 3 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 4. Sites and employees 5,700 employees working Hamburg in 28 research institutes and Bremen- Neustrelitz facilities Trauen Berlin- Braunschweig at 13 sites. Göttingen Offices in Brussels, Paris and Washington. Köln Bonn Lampoldshausen Stuttgart Oberpfaffenhofen Weilheim Folie 4 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 5. Introduction Simulation in Aerospace and Avionics Designing new space and aerospace vehicles require high-resolution numerical simulation steps conducted in complex workflows The complete simulation of all flow phenomena throughout the entire flight envelope including the multidisciplinary simulation of all involved disciplines The multidisciplinary optimization of the overall aircraft design as well as the design of major parts, such as the turbine engines Involved disciplines: Aerodynamics – Structure – Heat – Flight mechanics – Radar & Infrared signature – Materials (physics/chemistry) – Combustion … Folie 5 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 6. Software Technology for Aerospace Simulations Numerical Codes and Supporting Tools Highly sophisticated and optimized numerical simulation codes For example, high-fidelity CFD codes Many codes available (free, commercial, proprietary) To major CFD codes of DLR TAU TRACE Simulation infrastructure and supporting tools Grid environments Data and workflows management tools Integrated Integrated Knowledge management ( documentation!) environments environments Preprocessing, post processing, visualization Folie 6 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 7. DLR CFD Codes Folie 7 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 8. DLR TAU Code Finite Volume CFD Solver Reynolds-averaged Navier-Stokes (RANS) code Steady and unsteady flow, hybrid grids State-of-the-Art turbulence models Adaptation module for local refinement Chimera method Completely parallelized (MPI) Used in European industry (Airbus, EADS) Contact: DLR Institute of Aerodynamics and Flow Technology http://www.dlr.de/as/case Folie 8 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 9. DLR TRACE Code Turbo machinery CFD TRACE: Turbo machinery Research Aerodynamics Computational Environment unsteady Reynolds-averaged Navier-Stokes (URANS) code Steady and unsteady flow (finite volumes) Hybrid multi block method Completely parallelized (MPI) Used in European industry (Siemens, MTU Aero Engines, Rolls Royce) Contact: DLR Institute of Propulsion Technology http://www.dlr.de/at Folie 9 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 10. Simulation Infrastructure Grid Computing in Germany – D-Grid Folie 10 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 11. German D-Grid Initiative Grid Infrastructure for e-Science Objectives Building a Grid Infrastructure for science and business in Germany Combine existing German grid activities Integration of middleware components developed in Community Grids Three components of the infrastructure Networks and associated tools Software layer for connecting tools and services Scientific information and knowledge Important aspects Continuing sustainable production grid infrastructure after the end of the funding period Integration of additional grid communities (2./3. generation) Business models for grid services Folie 11 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 12. D-Grid Projects Community Grid Projects User Services (Portals) PartnerGrid BauVOGrid Astro-Grid HEP-Grid MediGrid AeroGrid Business Services, SLAs, SOA Integration, Virtualization TextGrid WISENT C3-Grid In-Grid ●●● Knowledge Management Grid Middleware und Grid Services Integration Project Folie 13 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 13. General D-Grid Architecture User/Application Application development GAT API GridSphere and Plug-In user access Nutzer Scheduling Workflow Management higher Grid Monitoring Functions Datenmanagement LCG/gLite UNICORE Accounting Billing Base User/VO-Mngt services Globus Security Network- distributed distributed Data/ infrastructure data archives compute Software Resources Folie 14 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 14. Specifics of the D-Grid Architecture D-Grid supports three middleware and two data access protocols. Combines requirements of all communities. Goal: Support of all middleware systems by all resource providers Folie 15 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 15. D-Grid Infrastructure (2007) Folie 16 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 16. AeroGrid Project Folie 17 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 17. AeroGrid Project Data Grid-based cooperation between industry, research centres, and universities in aerospace engineering Runtime: April 1, 2007 – March 30, 2010 Website: http://www.aero-grid.de Folie 18 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 18. AeroGrid Use Cases and Project Goals Usage scenarios Use of computing resources via the AeroGrid Collaboration in designing engine components Co-operative further development of TRACE code Project goals Allow cooperation in research and development projects Use of up-to-date program versions, data, and compute resources across all locations Detailed documentation of history of a computational process that leads to a certain result (“Provenance”) Folie 21 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 19. Service-Provider A Service-Provider A WebDAV/ WebDAV/ Resources Resources AFS/SRB/ AFS/SRB/ Cooperation in AeroGrid GridFTP/… GridFTP/… UNICORE6 UNICORE6 Data/ Tools User User GridSphere GridSphere Meta data Data Data Server Server Code Code Management Management Developer Developer Tool Client Client Workflow Workflow Service* Service* CPU Resources Grid Interfaces Web Web Service-Provider B Service-Provider B Portal Portal Simulation Simulation Resources WebDAV/ WebDAV/ Resources User User AFS/SRB/ AFS/SRB/ GridFTP/… GridFTP/… UNICORE6 UNICORE6 Data/ Tools Workflow Workflow GridSphere GridSphere Meta data Client* Client* Server Server Workflow Workflow Service* Service* * Workflow service and client are not part of the project. CPU Resources They will be added for later user communities. ... Folie 22 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 20. Provenance Origin and Authenticity of Results Provenance of computational processes Recorded documentation of processes as they take place With this documentation, we can determine: the origin of electronic data and the compliance of the process that led to the data Definition of provenance The Provenance of some information is the history of its creation Related Terms “Data Lineage” is another word for Provenance Provenance is NOT “Logging” Folie 23 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 21. Provenance Example Queries Given some data item, what was the simulation case? Given some parameter, in what simulation(s) has it been used? What data has been recorded in a simulation with a specific parameter? What simulations have been run using a given model (aircraft design)? Given two/more simulations with the same setup, what is the result and the difference in provenance? What have been the initial conditions for this simulation? What were the termination criteria? How often has the workflow been executed? What specific algorithm/version has been used in computations? What were the hosts participating in the simulation run? Folie 24 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 22. Provenance Benefits for Aerospace Applications Clean documentation of distributed simulation workflows Ability to analyze and reason over all conducted computations Understanding of computations and their results Tool based support for analyses Allows checking for requirements Compliance to legal and business regulations Proof and reproducibility of results Folie 25 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 23. Example Provenance Information in Simulations Process d2 control File-Server m1 i0 c-4 c4 c1 c-1 d1 c2 c-2 c3 c-3 Pre- i1 Parameter i2 Simulation i4 Visualization Processing variation i3 Relationen: Interactions: - r0: i0 causes i1 Configuration State - r1: i1 causes i2 of the Actors - r2: i2 causes i3 Process flow - r3: i2 causes i4 Monitoring - r4: i3 causes i2 - r5: i2 causes m1 Data management - r6: i2 causes d1 - r7: i0 causes d2 Folie 27 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 24. AeroGrid User Interfaces Portal Web-basaed access Devlopment based on GridSphere Client applications Automation of recurring tasks Integration in existing working environments Folie 28 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 25. Data Management Client Software DataFinder Folie 29 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 26. DataFinder Short Overview DataFinder Efficient management of scientific and technical data Focus on huge data sets Development of the DataFinder by DLR Available as Open-Source-Software Primary functionality Structuring of data through assignment of meta information and self- defined data models Complex search mechanism to find data Flexible usage of heterogeneous storage resources Integration in the working environment Folie 30 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 27. DataFinder Uses Large-scale simulations aerodynamics material science climate … Measured data wind-tunnel experiments earth observations traffic data … Folie 31 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 28. DataFinder Overview Basic Concept Client-Server solution Based on open and stable standards, such as XML and WebDAV Extensive use of standard software components (open source / commercial), limited own development at client side Folie 32 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 29. DataFinder Mass Data Storage using “Data Stores“ Storage Logical View User Client Locations “Data Stores” External Medias Folie 34 (CD, DVD,…) Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 30. Data Structure Mapping of Organizational Data Structures Object Object (file) (collection) Relation File 1 Project Mega Code Ultra User Eddie Simulation I Key Value Project Mega Code Ultra User Eddie Key Value File 2 Project Mega Code Ultra User Eddie Project A Simulation II Key Value Project Mega Project Mega Code Ultra Code Ultra User Eddie User Eddie Key Value Key Value Experiment User Project Mega Project B Project Mega Project Code User Key Mega Ultra Eddie Value Code Ultra Code Ultra User Eddie User Eddie Key Value Key Value Attributes Project C Project Code User Key Mega Ultra Eddie Value (meta data) Folie 36 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 31. DataFinder in AeroGrid Turbine Simulation Folie 38 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 32. Turbine Simulation Data Model Simulation steps (example): 1. splitCGNS Preparing data for TRACE 2. TRACE (CFD solver) Main computation 3. fillCGNS Conflating results 4. Post Processing Data reduction and visualization Automation with customized DataFinder Folie 39 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 33. Turbine Simulation: Graphical User Interface Folie 40 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 34. Turbine Simulation: Customized GUI Extensions 1 2 1. Create new simulation 2. Start a simulation 3. Query status 3 4. Cancel simulation 5. Project overview 4 5 Customization based on user requirements! Folie 41 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 35. Turbine Simulation Starting External Applications 1. CGNS Infos / ADFview / CGNS Plot 2. TRACE GUI 3. Gnuplot 1 2 Integration with 3 other tools! Folie 42 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 36. Integration Platform and Workflow Management Reconfigurable Computing Environment (RCE) Folie 43 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 37. Beyond DataFinder… Use cases for “lightweight” tools like DataFinder Simple recurring tasks Easy and fast customization (but “static” workflows!) Instant access to distributed storage resources Easy installation Additional complexity requires more sophisticated systems Dynamic (large) workflows Complex configurable user interface Use of existing services Folie 44 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 38. Reconfigurable Computing Environment (RCE) The RCE general purpose integration platform Used to manage collaborative engineering processes Provision of commonly used software components Data management, graphical user interface, distributed computing, workflow component Concentration on the application specific software components Developed as a service oriented software framework Using OSGi as service platform (for Java) Eclipse for graphical user interface Folie 45 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 39. RCE Architecture Macro Notification Config. Ext. Code Application Server SOAP Communication RMI Application Privilege Wrapper Broker Data Application GUI … … … Reconfigurable Computing Environment OSGi/Eclipse Equinox Java Virtual Machine Folie 46 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 40. RCE DB Server Distributed System Communication SOAP Applic. Server RMI Privilege Broker Data Application … RCE GUI OSGi/Eclipse Equinox Java Virtual Machine Communication SOAP Applic. Server RMI Privilege Broker Data GUI … Ext. Code RCE Communication SOAP Applic. Server Simulation OSGi/Eclipse Equinox RMI Privilege Wrapper Broker Data Java Virtual Machine … RCE OSGi/Eclipse Equinox Java Virtual Machine Simulation Desktop Folie 51 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 41. GUI Example Shipbuilding Industry Folie 52 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 42. Use Cases at DLR RCE as integration platform IMENS (Multi disciplinary design of space re-entry vehicles) Simulation of hot structures RCE-based environment for coupled, distributed simulation in Grids CEF (Concurrent Engineering Facility) Collaborative early design of space vehicles Mission planning Experts for all disciplines in one room RCE-based software infrastructure Reuse of existing Excel-spreadsheets XPS4CFD (Expert System for CFD) Folie 54 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 43. Integration with Microsoft Excel If you cannot avoid Excel: Solution 1: Use Excel, integrate interfaces to computational resources into Excel Solution 2: Integrate Excel into execution environment and workflow system RCE-Excel-Integration Excel user interface integrated Excel is nice! into RCE/Eclipse It's ugly to use, but nice. Excel files stored in RCE data And in the end all data management Sharing data with other RCE ends in Excel. Hans Rosling components Folie 55 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 44. Folie 56 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 45. Folie 57 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 46. Expert System for Aerospace Engineers XPS4CFD Folie 58 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 47. XPS4CFD (1) Expert System for Aerospace Engineers Assistance of users of DLRs CFD-software TAU Provide best-practices and guidelines, depending on specific problems and facts Rule-based system using JBoss Drools as the rule engine Eclipse Rich Client Platform application, based on RCE Folie 60 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 48. XPS4CFD (2) Expert System for Aerospace Engineers Combined with a Lucene search engine for finding relevant documents Easily maintainable and extensible by experts, not programmers Forms and graphical editors for adding, changing and deleting rules, workflows and documents Generators for automatic creation of the fact model and UI elements like interview-components Folie 61 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 49. Choosing and Planning a Scenario Folie 62 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 50. Guiding Users Through a TAU Workflow (1) Folie 63 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 51. Guiding Users Through a TAU Workflow (2) Folie 64 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 52. Guiding Users Through a TAU Workflow (3) Folie 65 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 53. Creating Rules Folie 66 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 54. Creating Forms Folie 67 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 55. Creating Workflows Folie 68 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 56. Expert System Additional Use Cases (related to space/aerospace) Health monitoring Monitoring health status of astronauts and pilots Managing knowledge about irregular health parameters Send alarms Astronaut assistance Assist astronauts in standard procedures and problem situations Configurable for all subsystems of space crafts Folie 69 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 57. Conclusion Putting All Together… Expert Expert feedback analysis User System System Shares Knowledge Uses Knowledge generate workflow Works with data Data & Data & Search meta data Workflow trace Provenance Workflow user Select resources Management Management action Store execute workflow Software tools trace Generate workflow description workflow execution Executes workflows in Grids Record Provenance info Folie 70 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008
  • 58. Questions? Folie 71 Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008

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