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
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2. Outline
Who we are
What we do (among other things)
How we do it
What we want to do next
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3. Who we are
DLR
German Aerospace Center
Research Institution
Space Agency
Project Management Agency
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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 
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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 …
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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
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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
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8. Distributed Computing and Data Management
DataFinder
Storage
Locations
Logical View User Interface “Data Stores”
Department
Employee
Simulation
Geometry
Grid Generation
Flow Solution
Visualisation
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9. Distributed Computing and Data Management
DataFinder
Running simulations
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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
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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)
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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
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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
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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
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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
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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
...
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17. What we want to do next
Integration of external data sources into the expert system
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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
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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
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20. Questions?
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Doreen.Seider@dlr.de ADVCOMP 2009 > Doreen Seider > Scientific Data and Knowledge Management in Aerospace Engineering > 13.10.2009