Knowledge management on the desktop

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Survey of Semantic Desktops, short paper presented at EKAW2012.

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  • Hello, My name is Laura and I'm here to tell you about linking semantic desktop data to the web of data I'll start by describing a bit the reasons behind it, and a bit of background
  • Knowledge management on the desktop

    1. 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. 2. [Old] Challenges & MotivationsDigital Enterprise Research Institute www.deri.ie  Information overload Nelson (70s)  Data silos / application formats  Trusted information Nelson (70s)  Associative trails Bush (40s) – Engelbart (60s) 2
    3. 3. memexDigital Enterprise Research Institute www.deri.ie  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” 3
    4. 4. NLS and XanaduDigital Enterprise Research Institute www.deri.ie  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.” 4
    5. 5. Modern Semantic DesktopsDigital Enterprise Research Institute www.deri.ie 5
    6. 6. Modern Semantic DesktopsDigital Enterprise Research Institute www.deri.ie 6
    7. 7. Differences and SimilaritiesDigital Enterprise Research Institute www.deri.ie  Architecture  Data representation  Evaluation 7
    8. 8. ArchitectureDigital Enterprise Research Institute www.deri.ie  Layered – modular – service oriented  Layers (fuzzy)  Data layer  Service layer  Presentation / Application layer 8
    9. 9. Data layerDigital Enterprise Research Institute www.deri.ie  Data-centric  Functions  Unlock desktop data from application repositories  Transform data from application specific formats 9
    10. 10. Data representationDigital Enterprise Research Institute www.deri.ie All systems define a data model comprehensive small/generic modular monolithic 10
    11. 11. ServicesDigital Enterprise Research Institute www.deri.ie  Storage  Extraction  Integration  Annotation  Query  Inference  ... 11
    12. 12. ServicesDigital Enterprise Research Institute www.deri.ie  Storage  Extraction  Integration  Annotation  Query  Inference  ... 12
    13. 13. ServicesDigital Enterprise Research Institute www.deri.ie  Storage  Extraction  Integration  Annotation  Query  Inference  ... 13
    14. 14. ServicesDigital Enterprise Research Institute www.deri.ie  Storage  Extraction  Integration  Annotation  Query  Inference  ... 14
    15. 15. ServicesDigital Enterprise Research Institute www.deri.ie  Storage  Extraction  Integration  Annotation  Query  Inference  ... 15
    16. 16. ServicesDigital Enterprise Research Institute www.deri.ie  Storage  Extraction  Integration  Annotation  Query  Inference  ... 16
    17. 17. Blackboard patternDigital Enterprise Research Institute www.deri.ie Data storage Storage service Desktop services 17
    18. 18. ApplicationsDigital Enterprise Research Institute www.deri.ie  Categories of systems  Enhance existing applications with semantic features  Replace existing applications with new semantic ones  Flexible visualizations  Resource browser 18
    19. 19. EvaluationsDigital Enterprise Research Institute www.deri.ie  Evaluation of PIM tools is difficult Kelly 2006  Simple ontologies prefered  Customisation rare Sauermann 2009  Semantic applications are better Franz 2008, 2009 19
    20. 20. ConclusionDigital Enterprise Research Institute www.deri.ie  Similar  Motivations  Goals  Architectures  Outcomes  Adoption  Future of the systems 20

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