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San Diego 2010

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Semantic Web San Diego

Linked data, Life Sciences and RDF Stores - Exploration and Tutorials by Jans Aasman, CEO Franz Inc San Diego Semantic web Jan 30, 2010 presentation

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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.    • • • • • • • • • •
  • 6.
  • 7.
  • 8.
  • 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)
  • 10.
  • 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")
  • 12.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.             
  • 20.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.                       
  • 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 
  • 39.
  • 42.
  • 44.
  • 45.
  • 46.
  • 47.
  • 48.
  • 49.
  • 52.
  • 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
  • 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.             
  • 61.                     
  • 63.                
  • 65.                  
  • 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 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
  • 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.           