STI Summit 2011 - Conclusion

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<ul><li> 1. Michael L. Brodie, Mark Greaves, Rudi Studer STI Fellows Copyright 2011 STI - INTERNATIONAL www.sti2.org </li> <li> 2. Michael L. Brodie, Mark Greaves, Rudi Studer STI Fellows Copyright 2011 STI - INTERNATIONAL www.sti2.org </li> <li> 3. www.sti2.org 7/2011 -Summit </li> <li> 4. Problems - Solutions Problem PULL Solution PUSHwww.sti2.org 7/2011 -Summit </li> <li> 5. Tipping PointsTechnology Time Value Tipping PointDatabases 80s (RDBMSs) Data Beat other management DBMSsClient-Server 90s (servers) Cost, flexibility Beat M/FServices 20th C (economics); Module-object- simplicity 90s (Biz), 00s(IT) serviceWeb 80-90s; 90s+ Universal Mosaic Information access and sharingCloud 80s; 2004+ Compression: Big players savings: hardware; labor AmazonSemantic Tech 50s; 70-80s; 90s+ Higher order + AI Winter; now productivity what?Semantic Web 2001 (Sci Am); Connectivity: people 10 years; now 2005 (LOD)+ &amp; machines what? www.sti2.org 7/2011 -Summit </li> <li> 6. Semantic Web Value &amp; Tipping Point Deliver value Dirty details of a specific application (domain) Dieters Examples Documents Data Mobile Social Sensors Energy grids Etc.www.sti2.org 7/2011 -Summit </li> <li> 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 Meaningfullywww.sti2.org 7/2011 -Summit </li> <li> 8. Thank you for being here!www.sti2.org 7/2011 -Summit </li> </ul>