12
An Integrated SocioTechnical Crowdsourcing Pla8orm for Accelera;ng Returns in eScience Karl Aberer, Alexey Boyarsky, Philippe CudréMaurox, Gianluca Demar-ni, and Oleg Ruchayskiy

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

Embed Size (px)

DESCRIPTION

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

Citation preview

Page 1: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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  

Page 2: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

Science  

Yesterday   Today  

GiIed  Individuals   Collabora;ve  Effort  

Page 3: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

OPERA  Collabora;on  

Page 4: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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  

Page 5: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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  

Page 6: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

Science  

Tomorrow  

Collec;ve  Intelligence  

Page 7: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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  

Page 8: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

A  Giant  Crowdsourcing  Conceptualiza;on  Machine  

Page 9: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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  

Page 10: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

An  “entropy-­‐reduc;on”  machine  

•  Relate  en;;es  •  Provide  lineage  informa;on  •  Discriminate  conflic;ng  informa;on  •  Reason  and  infer  new  data  

Page 11: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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  

Page 12: An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

Scien;fic  progress  

Time  

Now