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Michael L. Brodie, Mark Greaves, Rudi Studer
                                                                                       STI Fellows

© Copyright 2011   STI - INTERNATIONAL www.sti2.org
Michael L. Brodie, Mark Greaves, Rudi Studer
                                                                                       STI Fellows

© Copyright 2011   STI - INTERNATIONAL www.sti2.org
www.sti2.org   7/2011 -Summit
Problems - Solutions


 •  Problem PULL

 •  Solution PUSH




www.sti2.org            7/2011 -Summit
Tipping Points
Technology        Time                   Value                Tipping Point


Databases         ‘80s (RDBMSs)          Data                 Beat other
                                         management           DBMSs
Client-Server     ‘90s (servers)         Cost, flexibility    Beat M/F
Services          20th C (economics);    Module-object-       simplicity
                  90s (Biz), 00s(IT)
                                         service
Web               80-90s; 90s+           Universal            Mosaic
                                         Information access
                                         and sharing
Cloud             80’s; 2004+            Compression:         Big players savings:
                                         hardware; labor      Amazon

Semantic Tech     50’s; 70-80’s; 90’s+   Higher order +       AI Winter; now
                                         productivity         what?
Semantic Web      2001 (Sci Am);         Connectivity: people 10 years; now
                  2005 (LOD)+            & machines           what?
   www.sti2.org                                                             7/2011 -Summit
Semantic Web Value & Tipping Point


 •  Deliver value
 •  Dirty details of a specific application (domain)
 •  Dieter’s Examples
               –    Documents
               –    Data
               –    Mobile
               –    Social
               –    Sensors
               –    Energy grids
               –    Etc.


www.sti2.org                                           7/2011 -Summit
Big Data


 •  Problem: Scale
 •  Solutions
               –  Data-driven methods (supplant scientific method?)
               –  Multi-disciplinary (will the semantic web be in the mix?)

 •  Data Integration Solution
               –    Search / discover candidates
               –    ETL: get candidate data elements in required form
               –    Entity resolution
               –    Computation


 •  Critical / Central Challenge
               –  Meaningfully
www.sti2.org                                                                  7/2011 -Summit
Thank you for being here!



www.sti2.org                               7/2011 -Summit

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STI Summit 2011 - Conclusion

  • 1. Michael L. Brodie, Mark Greaves, Rudi Studer STI Fellows © Copyright 2011 STI - INTERNATIONAL www.sti2.org
  • 2. Michael L. Brodie, Mark Greaves, Rudi Studer STI Fellows © Copyright 2011 STI - INTERNATIONAL www.sti2.org
  • 3. www.sti2.org 7/2011 -Summit
  • 4. Problems - Solutions •  Problem PULL •  Solution PUSH www.sti2.org 7/2011 -Summit
  • 5. Tipping Points Technology Time Value Tipping Point Databases ‘80s (RDBMSs) Data Beat other management DBMSs Client-Server ‘90s (servers) Cost, flexibility Beat M/F Services 20th C (economics); Module-object- simplicity 90s (Biz), 00s(IT) service Web 80-90s; 90s+ Universal Mosaic Information access and sharing Cloud 80’s; 2004+ Compression: Big players savings: hardware; labor Amazon Semantic Tech 50’s; 70-80’s; 90’s+ Higher order + AI Winter; now productivity what? Semantic Web 2001 (Sci Am); Connectivity: people 10 years; now 2005 (LOD)+ & machines what? www.sti2.org 7/2011 -Summit
  • 6. Semantic Web Value & Tipping Point •  Deliver value •  Dirty details of a specific application (domain) •  Dieter’s Examples –  Documents –  Data –  Mobile –  Social –  Sensors –  Energy grids –  Etc. www.sti2.org 7/2011 -Summit
  • 7. Big Data •  Problem: Scale •  Solutions –  Data-driven methods (supplant scientific method?) –  Multi-disciplinary (will the semantic web be in the mix?) •  Data Integration Solution –  Search / discover candidates –  ETL: get candidate data elements in required form –  Entity resolution –  Computation •  Critical / Central Challenge –  Meaningfully www.sti2.org 7/2011 -Summit
  • 8. Thank you for being here! www.sti2.org 7/2011 -Summit