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San Diego 2010

The document appears to include data entries regarding individuals and their attributes, as well as relationships between them, likely formatted for a database. It mentions individuals such as Steve, Jans, and Craig, detailing their occupations and personal details, while also referencing locations with geographical coordinates. The structure suggests an organized data system for managing information about people and their connections.

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     
               
   •  •  •    •  •  • 
                         
   • • • • • • • • • •
 createTripleStore(“seminar.db" ) addTriple (Person1 first-name Steve) addTriple (Person1 isa Organizer) addTriple (Person1 age 52) addTriple (Person2 first-name Jans) addTriple (Person2 isa Psychologist) addTriple (Person2 age 50) addTriple (Person3 first-name Craig) addTriple (Person3 isa SalesPerson) addTriple (Person3 age 32) addTriple (Person1 colleague-of Person2) addTriple (Person1 colleague-of Person3) addTriple (Person1 likes Pizza)
  addTriple ( Person3 neighbor-of Person1) addTriple ( Person3 neighbor-of Person2) addTriple ( Person3 !o:lives-in !o:Place1111) addTriple ( Place1111 !o:name !"Moraga") addTriple ( Place1111 !o:latitude !"37.12223") addTriple ( Place1111 !o:longitude !"-122.4325")
 
            
  
  
                      
 
  S1 type stream-segment  S1 upstream S2  S1 upstream S3  S1 left-drainage D1  S1 right-drainage D2  S1 longitude1 12.1  S1 latitude1 -121.2  S1 longitude2 12.12  S1 latitude2 -121.3 

 

   
  
GSK Competitive Analysis: > 50 % of new products come from buying up small innovative pharma research companies  > 2000 need to be tracked for competitive analysis  We tracked in one system New management New investors New whitepapers New products mentioned that are of interested to GSK New customers New partners

                     
               
 DB1 DB2 DB1000 Integrated Schemas, Data Integration CUSTOMER CARE INVENTORY CTR 1. Semantified Schema’s 2. Product and customer ontologies 3. Customer -> DB links MARKETING ANALYSIS 4. Product -> DB links 5. Customer/product aggregations
            
            

                    

               

                 

          Tech reasons      Business   Considerations  
                                       
                   
                   
                  
  LUBM(8000) Total query time 1200 1000 800 Seco n d s 600 Series1 400 200 0 AllegroGraph 3.2 Other Total
LUBM(8000) queries 800 700 600 Seconds 500 AllegroGraph 3.2 400 300 Other 200 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Query Num ber
LUBM(8000) with long queries zeroed 1 0.8 Seconds 0.6 AllegroGraph 3.2 0.4 Other 0.2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Queries
 LUBM(8000) Total Time 200000 150000 Total Query Time Seconds 100000 Type Materializations 50000 Loading and Indexing 0 Other / Static AllegroGraph AllegroGraph 3.2 3.2 Federated
    Find all meetings that happened in November within 5 miles of Berkeley that was attended by the most important person in Jans’ friends and friends of friends. (select (?x) (ego-group person:jans knows ?group 2) SNA (actor-centrality-members ?group knows ?x ?num) SNA (q ?event fr:actor ?x) DB Lookup (qs ?event rdf:type fr:Meeting) RDFS (interval-during ?event “2008-11-01” “2008-11-06”) Temporal (geo-box-around geoname:Berkeley ?event 5 miles) Spatial !)
                       
                
                   ’  
          

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San Diego 2010

  • 1.
         
  • 2.
                  
  • 3.
       •  •  •    •  •  • 
  • 4.
                             
  • 5.
       • • • • • • • • • •
  • 9.
     createTripleStore(“seminar.db" ) addTriple (Person1 first-name Steve) addTriple (Person1 isa Organizer) addTriple (Person1 age 52) addTriple (Person2 first-name Jans) addTriple (Person2 isa Psychologist) addTriple (Person2 age 50) addTriple (Person3 first-name Craig) addTriple (Person3 isa SalesPerson) addTriple (Person3 age 32) addTriple (Person1 colleague-of Person2) addTriple (Person1 colleague-of Person3) addTriple (Person1 likes Pizza)
  • 11.
      addTriple ( Person3 neighbor-of Person1) addTriple ( Person3 neighbor-of Person2) addTriple ( Person3 !o:lives-in !o:Place1111) addTriple ( Place1111 !o:name !"Moraga") addTriple ( Place1111 !o:latitude !"37.12223") addTriple ( Place1111 !o:longitude !"-122.4325")
  • 13.
  • 19.
                
  • 21.
  • 22.
  • 36.
                          
  • 37.
  • 38.
      S1 type stream-segment  S1 upstream S2  S1 upstream S3  S1 left-drainage D1  S1 right-drainage D2  S1 longitude1 12.1  S1 latitude1 -121.2  S1 longitude2 12.12  S1 latitude2 -121.3 
  • 40.
  • 41.
  • 43.
  • 50.
  • 51.
  • 53.
    GSK Competitive Analysis: >50 % of new products come from buying up small innovative pharma research companies  > 2000 need to be tracked for competitive analysis  We tracked in one system New management New investors New whitepapers New products mentioned that are of interested to GSK New customers New partners
  • 54.
  • 55.
                         
  • 56.
                   
  • 57.
     DB1 DB2 DB1000 Integrated Schemas, Data Integration CUSTOMER CARE INVENTORY CTR 1. Semantified Schema’s 2. Product and customer ontologies 3. Customer -> DB links MARKETING ANALYSIS 4. Product -> DB links 5. Customer/product aggregations
  • 58.
                
  • 59.
                
  • 60.
  • 61.
                        
  • 62.
  • 63.
                   
  • 64.
  • 65.
                     
  • 66.
  • 67.
              Tech reasons      Business   Considerations  
  • 68.
                                           
  • 69.
                       
  • 70.
                       
  • 71.
                      
  • 72.
      LUBM(8000) Total query time 1200 1000 800 Seco n d s 600 Series1 400 200 0 AllegroGraph 3.2 Other Total
  • 73.
    LUBM(8000) queries 800 700 600 Seconds 500 AllegroGraph 3.2 400 300 Other 200 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Query Num ber
  • 74.
    LUBM(8000) with longqueries zeroed 1 0.8 Seconds 0.6 AllegroGraph 3.2 0.4 Other 0.2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Queries
  • 75.
     LUBM(8000) Total Time 200000 150000 Total Query Time Seconds 100000 Type Materializations 50000 Loading and Indexing 0 Other / Static AllegroGraph AllegroGraph 3.2 3.2 Federated
  • 76.
        Find all meetings that happened in November within 5 miles of Berkeley that was attended by the most important person in Jans’ friends and friends of friends. (select (?x) (ego-group person:jans knows ?group 2) SNA (actor-centrality-members ?group knows ?x ?num) SNA (q ?event fr:actor ?x) DB Lookup (qs ?event rdf:type fr:Meeting) RDFS (interval-during ?event “2008-11-01” “2008-11-06”) Temporal (geo-box-around geoname:Berkeley ?event 5 miles) Spatial !)
  • 77.
                           
  • 78.
                    
  • 79.
                       ’  
  • 80.
              