An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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Conference talk at ISWC 2011 for the award winning outrageous ideas track, October 2011, Bonn, Germany

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An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

  1. 1. An  Integrated  Socio-­‐Technical   Crowdsourcing  Pla8orm  for   Accelera;ng  Returns  in  eScience   Karl  Aberer,  Alexey  Boyarsky,   Philippe  Cudré-­‐Maurox,  Gianluca   Demar-ni,  and  Oleg  Ruchayskiy  
  2. 2. Science   Yesterday   Today   GiIed  Individuals   Collabora;ve  Effort  
  3. 3. OPERA  Collabora;on  
  4. 4. Scien;st-­‐Computer  Symbiosis   •  A  single  scien;st  has  no  more  the  capacity  to   process  all  the  informa;on   – High  complexity  of  systems  and  workflows   – Various  fields  of  exper;se  involved   •  New  discoveries  will  emerge  from   community-­‐based  socio-­‐technical  systems  
  5. 5. Community-­‐based  Socio-­‐technical  Systems   •  Such  pla8orms  will  be  useful   – Locally  to  the  scien;st     – By  extrac;ng  knowledge  used  globally   •  They  will  enable  cross-­‐pollina;on   – All  ar;facts  need  to  be  interoperable   – Higher  order  logic  to  combine  them  
  6. 6. Science   Tomorrow   Collec;ve  Intelligence  
  7. 7. What  do  we  need?   •  Highly-­‐expressive  machine-­‐readable  formats   – Ontologies  of  unprecedented  quality   – Implicit  knowledge  available  in  the  head  of  the   experts   •  Understanding  concepts,  assump;ons,   phenomena,  abstrac;ons   •  Create  a  mental  map  of  a  research  field   •  Understand  analysis  methods  
  8. 8. A  Giant  Crowdsourcing   Conceptualiza;on  Machine  
  9. 9. Towards  Self-­‐Awareness   •  A  Scien;fic  infrastructure   – Complex  ontological  networks   – Capture  the  scien;fic  process   – Automate  rou;ne  opera;ons   – Share  scien;fic  ar;facts   •  Experts  will  train  the  system  with  their  daily   ac;vi;es  
  10. 10. An  “entropy-­‐reduc;on”  machine   •  Relate  en;;es   •  Provide  lineage  informa;on   •  Discriminate  conflic;ng  informa;on   •  Reason  and  infer  new  data  
  11. 11. The  Web:  a  Collec;ve  Intelligence  engine     •  Informa;on  systems  are  not  instruments   •  A  catalyst  for  the  scien;fic  progress   •  Reason  and  combine  scien;fic  ar;facts  at  very   large  scale   •  Individual  scien;st  will  not  be  able  to  fully   appreciate  models  and  methods  
  12. 12. Scien;fic  progress   Time   Now  

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