Survey of Semantic Desktops, short paper presented at EKAW2012.

1. Digital Enterprise Research Institute deri.ie
Knowledge management
on the desktop
Laura Drǎgan, Stefan Decker
© Copyright 2009 Digital Enterprise Research Institute. All rights reserved.

2. [Old] Challenges & Motivations
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 Information overload
Nelson (70s)
 Data silos / application formats
 Trusted information
Nelson (70s)
 Associative trails
Bush (40s) – Engelbart (60s)
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3. memex
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 Vannevar Bush - “As we may think” - 1945!
“... a device in which an individual stores all his books,
records and communications, and which is
mechanized so that it may be consulted with
exceeding speed and flexibility”
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4. NLS and Xanadu
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 Doug Engelbart & Ted Nelson
 1960s and 1970s
“better concept structures can be developed –
structures that when mapped into a human’s mental
structure will significantly improve his capability to
comprehend and to find solutions within his complex
problem situations.”
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5. Modern Semantic Desktops
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6. Modern Semantic Desktops
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7. Differences and Similarities
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 Architecture
 Data representation
 Evaluation
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8. Architecture
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 Layered – modular – service oriented
 Layers (fuzzy)
 Data layer
 Service layer
 Presentation / Application layer
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9. Data layer
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 Data-centric
 Functions
 Unlock desktop data from application repositories
 Transform data from application specific formats
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10. Data representation
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All systems define a data model
comprehensive small/generic
modular monolithic
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11. Services
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 Storage
 Extraction
 Integration
 Annotation
 Query
 Inference
 ...
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12. Services
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 Storage
 Extraction
 Integration
 Annotation
 Query
 Inference
 ...
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13. Services
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 Storage
 Extraction
 Integration
 Annotation
 Query
 Inference
 ...
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14. Services
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 Storage
 Extraction
 Integration
 Annotation
 Query
 Inference
 ...
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15. Services
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 Storage
 Extraction
 Integration
 Annotation
 Query
 Inference
 ...
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16. Services
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 Storage
 Extraction
 Integration
 Annotation
 Query
 Inference
 ...
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17. Blackboard pattern
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Data storage
Storage service
Desktop services
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18. Applications
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 Categories of systems
 Enhance existing applications with semantic features
 Replace existing applications with new semantic ones
 Flexible visualizations
 Resource browser
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19. Evaluations
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 Evaluation of PIM tools is difficult
Kelly 2006
 Simple ontologies prefered
 Customisation rare
Sauermann 2009
 Semantic applications are better
Franz 2008, 2009
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20. Conclusion
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 Similar
 Motivations
 Goals
 Architectures
 Outcomes
 Adoption
 Future of the systems
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