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STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
STI Summit 2011 - Mlr-sm
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  • 1. My  Seman)cs  of  “Train”   <owl:Thing  rdf:about="#LevisTrain">                  <rdf:type  rdf:resource="#Train"/>                  <rdfs:label>Levi’s  Train</rdfs:label>                  <madeOf  rdf:resource="#Plas&c"/>          </owl:Thing>  <owl:Thing  rdf:about="#LevisTrain">                  <rdf:type  rdf:resource="#Train"/>                  <rdfs:label>Levi’s  Train</rdfs:label>                  <madeOf  rdf:resource="#Wood"/>          </owl:Thing>  
  • 2. A  Usage-­‐dependent  Life  Cycle   Request  to  put   • toy  train   away  the  “train”   • toy  train   • made  of  plas)c   • SELECT  *  WHERE  ?t   • made  of  wood      a:madeOf  a:Plas)c   • SELECT  *  WHERE  ?t   b:madeOf  b:Wood   Nego)ate   Enter  the  room   understanding   USAGE  
  • 3. Yet  another…   OTK   …   The   NeOn   Maintenance   METHONTOLOGY   Black  Box  DILIGENT  Make  it  less  a  methodology  but  support  the   people  to  get  their  “Things”  done!  
  • 4. Who  is  hurt  by  that?  •  rather  small/simple  ontologies   –  min.  effort  for  OE   –  “under-­‐engineered”  •  unknown  user  requirements  
  • 5. Hey  “LOD  people”,  do  you  think  that   ontology  engineering  maaers?   Usage-­‐based  ontology  engineering  
  • 6. Survey  covering  approx.   25%  of  all  cloud  datasets  •  size  •  complexity  •  engineering  methodology  •  …    Publishers  of  75%  of  the  dataset  do  not  feel   99%   responsible  for  their  data?   Survey  ran  in  October  2010  
  • 7. Concrete  Example  of  Usage-­‐based   Approach  digging  in  log  files  
  • 8. Usage?   Request  to  put   away  the  “train”  • SELECT  *  WHERE  ?t      a:madeOf  a:Plas)c   Yes*!  But  beyond?  • SELECT  *  WHERE  ?t   b:madeOf  b:Wood   USAGE   •  What  about  the  future  of  SPARQL   endpoints  on  the  WoD?   *  W.r.t.  an  architecture  proposed  by  a  famous  “Web-­‐Extremist”  
  • 9. You  should  have  a  query  endpoint!   Effort Distribution between Publisher and Consumer •  You  get  Pays-As-You-Go something   valuable   Consumer generates/ data mines linksen the data publisher,t   data integration effort is out  of  i the publisher which  helps  mer and third parties. !"# Effort $%&()) *(+( Distribution ,-+&.(+"/-lisher s data as RDFyou  to  play   011/+ your  role  erms from common vocabularies s and publishes mappings Publisher provides links Links as hintsties on  the   p WoD!   pointing at y g your datamappings to the Web 567)"83&98 011/+ 23"4 5(+: 011/+ Christian Bizer: Pay-as-you-go Data Integration (21/9/2010)sumer ;/-86<&98o the rest 011/+ ta mining techniques for
  • 10. Usage  Analysis  •  queries   •  paaerns   •  triples   •  primi)ves   visualize  heat   maps   zoom  in  and  see   details  
  • 11. Some  Results  (DBpedia  Analysis)   •  ns:Band  ns:instrument  ?x   inconsistent   •  ns:Band  ns:genre  ?y   data   •  ns:Band  ns:associatedBand  ?z   •  ns:Band  ns:knownFor  ?x   •  ns:Band  ns:na)onality  ?y   missing  facts  Complete  analysis  can  be  found  at  hap://page.mi.fu-­‐berlin.de/mluczak/pub/visual-­‐analysis-­‐of-­‐web-­‐of-­‐data-­‐usage-­‐dbpedia33/
  • 12. Some  Thoughts   about  Benefit    •  usage  analysis  helps   to  acquire  new   knowledge   –  links  between  data     helps  to  increase  •  lightweight  approach   the  quality  of  data  on   helps  to  bootstrap   the  Web   linked  data   –  external  schema   It  is  not  necessary  to  automate  everything  if  the  result  has   enough  (business)  value  in  a  problem  domain  anyway.    
  • 13. make  it  less  a  methodology   •  LOD  vocabularies  are  specific  ontologies   •  and  need  specific  life  cycle  our  data   provide  (query)  access  to  y support   T •  endpoint  and  pcan  your  to  mon  the  WoD   usage  analysis   lay   help  role   aintain  them   a •  (and  the  mplicitly  necessary  to  automate   it  is  not  i data)   k •  things  ahat  enable  automa)on   publisher   this  is   t  benefit  for  the  dataset   e   and  the  Web  of  data  as  a  whole   A Hey  “LOD  people”,  do  you  think  that   w dataset  maintenance  maaers?   a y  Markus  Luczak-­‐Rösch  (luczak@inf.fu-­‐berlin.de)  Freie  Universität  Berlin,  Networked  Informa)on  Systems  (www.ag-­‐nbi.de)  
  • 14. Actual  Addi)on  •  “15.500.000  people  in  Germany  are  not  willing   to  use  the  internet”   –  emphasis  on  the  ESWC  discussion:  bridging  the   gap  (directly  or  indirectly)  between  these  people   and  the  internet/Web  has  a  high  poten)al  to   influence  societal  transforma)on  (they  are  not   going  to  use  a  browser  or  an  iPhone  and  they  do   not  care  for  seman)cs)   Source:  ARD-­‐Morgenmagazin,  08-­‐07-­‐2011  

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