TopQuadrant
© Copyright 2001-2003, TopQuadrant Inc.
The information in this presentation is proprietary to TopQuadrant and should not be duplicated, used or disclosed without permission.
Semantic Technologyin Government
Dean Allemang
TopQuadrant Inc.
© Copyright 2001-2003 TopQuadrant Inc., “Semantic Technologies for the Digital Shuttle”, slide 2
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Semantic Web – quick intro
W3C Ratified standards in 2004
RDF, RDFS, OWL
Standard for describing data, rather than documents
RDF merges data
RDFS and OWL process merged data
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Plain web page – addresses, no maps
No link to mapsYou have to map it
yourself
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Automatic link to maps
One link per mapCan’t make comparisons
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Map all button!
Map all! Now you can compare
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What about combinations from multiple sites?
?
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Semantic Web defines infrastructure for merging
Piggybank allows infofrom multiple
sites to be mergedand placed on a
Google mape.g.,
Red=red lineBlue=blue line
Magenta=Organic Supermakets
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Government Interest in Semantic Web
Data Integration multiple databases siloed systems Sensor fusion
Knowledge Management How do I know what I know? . . . when what I know is stored so many places?
Modularity of Models Enterprise Architecture Integrated system roadmap
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Data Integration
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Data Integration: Target Validation of the Future ?
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NEXIOM
Nasa Exploration Initiatives Ontology Model ExplorationSystems Mission Directorate Back to the Moon, on to Mars!
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Multiple sources of mission planning
Risk models materials process computation organizational . . . All need to be brought together!
CCCI (Command, Control, Communications, Intelligence) During mission execution Connect to DARPA practices (DODAF)
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Modular Enterprise Architecture
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F EA RM O
F - Federal
EA - Enterprise Architecture
O - Ontology
RM - Reference Model
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US Federal e-gov initiative
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Federal Enterprise Architecture – Reference Model
What is a “Reference Model”?
A basic model for something (system, architecture, whatever)
When someone builds their own (system, architecture, whatever) they extend the reference model
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Knowledge Management: NASA Digital Shuttle
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Why integration?NASA - An Illustrative Imagined Scenario
12. The launch occurred.
NASA Knowledge sources EO
1. An equipment anomaly delays the
Space Shuttle launch
2. An engineer searches databases for similar problems
3. With incomplete answers, he consults
other engineers about the faulty
equipment
4. Searches were made for the
supplier and where it was used elsewhere
on the Shuttle
5. The equipment was installed over 20 years ago and all of
the required information could
not be found.
6. The people that would know had
retired and had to be located
SDSKSC PRACA
7. Retirees were brought back to work
on the problem
8. On their advice, more document searches were
conducted.
9. Key documents were found in the
archives of a building
10. Important information was
communicated to relevant parties
11. A solution was decided
JSC PRACA GFE PRACA JEEVES MRCS CVAS CV
Disclaimer
This scenario is fictitious and is not based on any actual occurrences on the Space Shuttle. It is inspired by the movie entitled “The Space Cowboys”.
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The Digital Shuttle Project Vision
Move away from 2-D drawings to 3-D models
Implement a comprehensive knowledge representation for engineering data structure
Integrate commercial KM, engineering data management systems and engineering tools
CAD shape
Process
Part structure
Additional representations
metadata semanticsKnowledge Model
(EngrObj)
“The models (we want) have semantics, and can be analyzed for conformance to specs and self-adjusted when parameters are changed. All using a very high-level user interface that is comfortable for practitioners. CAD doesn't provide modeling semantics - just shapes. CAD is also difficult to use - typically, designs are entered by CAD operators, creating a potential interstice where knowledge can be dropped“ [Sidney Bailin]
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Future Scenario – Leaking valve is discovered on STS-nnn
NASA Knowledge sources
EOSDSKSC PRACA JSC PRACA GFE PRACA JEEVES MRCS CVAS CVano
Shuttle Knowledge Hub
Shuttle Knowledge AdvisorProfilesSpace
Shuttle Ontology
1. Leaking valve delays Shuttle
launch
2. Engineer asks the Knowledge
Advisor about the valve that is
leaking – has it happened before?
System reports previous incidents.
3. Engineer asks who supplied the valve, relevant
Engineering Orders (EOs) and Drawing
numbers also where the valves
are used
4. Engineer determines what needs to be done
to replace the valves
5. New EOs are raised and the
problem is fixed
6. Shuttle mission is ready for launch
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Tower of Babel
Well-known problem in large organizations – lots of people talking, but they don’t understand one another
First bright idea – bring in a Thesaurus or Controlled Vocabulary to help them out.
Another bright idea: Bring in an Object model to help them
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The tower grows higher …
But who resolves the differences between the mediators?
COVE
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Example – NASA Taxonomy and HORM
NASA Taxonomy Project at JPL – comprehensive enterprise taxonomy of Missions, Competencies, Industries, etc.
HORM – Ontology model of Risks, Threats, Mission Features
NASA Taxonomy Project at JPL – uses language of Thesaurus – broader, narrower, synonym, etc.
HORM – Ontology uses Classes, instances, Properties
A complex translation is needed – right?
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OWL to the rescue
BroaderNarrowerTermUseUse For…Mars
Climate Orbiter
ClasssubClassOftypePropertysubPropert
y…MCO
A few connections in the schema ….
… and OWL can integrate the rest of the information!
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Reusing thesauri in COVE
Now any thesaurus, object model, semantic model, etc. can be used as they were all in a single place
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NASA taxonomy in COVE
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Federated queries
Once the information is unified, a single query can work on the combined information space: