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Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
Linked Data at the BBC
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Linked Data at the BBC

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Short talk during the What linked data does, what linked data needs (http://www.meetup.com/Web-Of-Data/events/155068962/) meetup

Short talk during the What linked data does, what linked data needs (http://www.meetup.com/Web-Of-Data/events/155068962/) meetup

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  • 1. Linked  data  at  the  BBC   Sofia  Angeletou     Data  Architect   Linked  Data  Pla3orm   Core  Engineering  
  • 2. overview   •  what  is  the  BBC  doing  with  Linked  Data •  what  have  we  learnt   •  what  are  our  main  challenges      
  • 3. Linked  Data  Pla3orm   •  “To  organise  the  BBC's  online  content  around   the  things  that  ma5er  to  our  audience”   •  Link,  reuse  content  and  expose  it  in  novel  and     interesAng  ways   •  Available  to  many  online  products    
  • 4. what  does  that  mean?   •  A  lot  of  data   •  Defining  the  scope  and  the  data  model  very   well  and  clearly   •  Enabling  tools  and  services,  self  provisioning  
  • 5. TRIPLESTORE   CLIENT  APIs   CLIENT  APIs   DOMAIN  APIs   LDP  CORE   LDP  WRITER   key  components   SHARED  LIBRARIES  
  • 6. data   •  creaAve  works  (content)   •  things  (reference  data)   •  ontologies   –  content   –  things   –  management  and  ownership  
  • 7. services   •  live  sites   –  /sport   –  /educaAon   –   news  pilot   •  coming  soon   –  music  news   –  radio    
  • 8. lessons  learnt   Adding  complexity    while  not  directly  adding   value  to  the  proposiAon  is  not  a  good  idea   •  “Nice  to  have”,  “cool  thing  to  do”  are  not   compelling  reasons  when  dealing  with  a   producAon,  24/7  live  pla3orm  
  • 9. lessons  learnt   •  Trying  to  be  a  good  LOD  ciAzen  should  be   done  carefully   •  Examples   –  more  than  1M  unused  FOAF  triples   –  Geonames  ontology  very  large  and  difficult  to   delete.   •  Very  hard  to  manage  unused  models  when   serving  many  clients.  
  • 10. lessons  learnt   •  CauAously  use  restricAons   –  blank  nodes   –  funcAonal  properAes   –  disjointness   –  domains  and  ranges  (cause  inference,  they  are  not   for  type  checking)  
  • 11. main  challenges     •  decommissioning  legacy   •  shared  ownership  of  common  topics   •  culture   –  tagging  with  a  purpose   –  what  is  your  proposiAon  (why  you  want  to  do  it)  
  • 12. main  principles   •  what  is  the  audience  proposiAon?   –  only  build  what  delivers  the  funcAonality  and  extend   iteraAvely   –  only  add  data  that  add  business  value   •  clear  ownership     –  content,  concepts,  ontologies   –  management  and  permissions   •  bo^om  up  approach   –  first  test,  then  generalise   –  controlled  pilot  builds  
  • 13. Thank  you   sofia.angeletou@bbc.co.uk  

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