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Scientific Data and Knowledge Management in Aerospace Engineering

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  • 1. Scientific Data and Knowledge Management in Aerospace Engineering ADVCOMP 2009 (October 13th 2009, Sliema) Andreas Schreiber, Jens Rühmkorf, Doreen Seider German Aerospace Center (DLR) – http://www.dlr.de/sc Folie 1 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 2. Outline Who we are What we do (among other things) How we do it What we want to do next Folie 2 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 3. Who we are DLR German Aerospace Center Research Institution Space Agency Project Management Agency Folie 3 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 4. Who we are 6200 employees across Hamburg  29 research institutes and  Neustrelitz Bremen   Trauen facilities at Berlin   13 sites. Braunschweig   Dortmund  Goettingen Offices in Brussels,  Koeln Paris and Washington.  Bonn Lampoldshausen  Stuttgart   Oberpfaffenhofen Weilheim  Folie 4 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 5. What we do (among other things) Simulation in Aerospace and Avionics Designing new space and aerospace vehicles require high-resolution numerical simulation steps conducted in complex workflows Involved disciplines: Aerodynamics – Structure – Heat – Flight mechanics – Radar & Infrared signature – Materials (physics/chemistry) – Combustion … Folie 5 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 6. How we do it Software Technology for Aerospace Simulations Numerical Codes For example, high-fidelity CFD codes Many codes available (free, commercial, proprietary) Two major CFD codes of DLR TAU TRACE Supporting Tools for Distributed Computing and Data Management Integrated Environments and Workflow Management Knowledge Management Folie 6 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 7. Distributed Computing and Data Management Large data sets are accumulated by simulations Data are the significant essence of simulations It is essential to make them available in a useful way  Tool handling those data Folie 7 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 8. Distributed Computing and Data Management DataFinder Storage Locations Logical View User Interface “Data Stores” Department Employee Simulation Geometry Grid Generation Flow Solution Visualisation Folie 8 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 9. Distributed Computing and Data Management DataFinder Running simulations Folie 9 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 10. Integrated Environments and Workflow Management Simulations are mostly conducted in complex workflows Workflow components mostly run on different hosts Single simulations mostly come from different disciplines  Environment for integrating the different simulations and handling the workflow execution and all related tasks Folie 10 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 11. Integrated Environments and Workflow Management Remote Component Environment (RCE) Integration environment with base software components Eclipse Rich Client Platform application Integrating diverse and specific applications (e.g. simulation codes) Folie 11 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 12. Integrated Environments and Workflow Management Provenance System The Provenance of some information is the history of its creation Provenance of computational workflows gives information about the origin of electronic data the compliance of the workflow that led to the data Folie 12 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 13. Knowledge Management Usage of numerical methods are standardised procedures Procedures are based of experience of knowledge of previous simulations Knowledge about strengths and weaknesses of certain simulation codes  Expert systems conserving and providing knowledge http://www.esa.int/esaMI/Rosetta Folie 13 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 14. Knowledge Management Expert System for Aerospace Engineers (XPS4CFD) 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 14 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 15. Conclusion Putting All Together… Expert feedback analysis System User generate workflow Shares knowledge Uses knowledge Data & trace Works with data Workflow Provenance user Management Store Search meta data action Select resources execute workflow trace Software tools workflow GRID execution Generates workflow description Executes workflows in Grids Computing resources Applications Records Provenance info Data Folie 15 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 16. What we want to do next Tighter integration of the expert system Expert feedback analysis System generate workflow Data & trace Workflow Provenance user Management action Store execute workflow trace workflow execution ... Folie 16 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 17. What we want to do next Integration of external data sources into the expert system Folie 17 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 18. What we want to do next Integration of Web 2.0 Technologies Web 2.0 technology have huge potential in research areas Each of us contains knowledge and information At the moment no way to use them in an easy way  Make them accessible for others Folie 18 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 19. What we want to do next Integration of Web 2.0 Technologies Publish, discuss, document, and share Results Input data Resources Problems Via Web 2.0 technologies Chats, Wikis, Blogs, Social Networks  Simplicity and Usability for Collaboration User participation Folie 19 ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009
  • 20. Questions? Folie 20 Doreen.Seider@dlr.de ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009