David De Roure
What’s so different about
Arts and Humanities data?
ChristineBorgman
What  is  e-­‐Research?  
•  Research  in  every  domain  is  increasingly  data-­‐  and  
computa8onally-­‐intensive,  ca...
More people
Moremachines
Big Data and
Computation
Conventional
Computation
Social
Machines
Social
Networking
Cyberinfrastr...
Economic  and  Social  Research  Council  
Shaping  Society  
•  Digital  Social  Research  Program  
•  Social  Machines ...
F i r s t
BioEssays,,26(1):99–105,January2004
http://research.microsoft.com/en-us/collaboration/fourthparadigm/
INT. VERSE VERSE VERSE VERSEBRIDGEBRIDGE OUT.

The  Problem  
signal
understanding
Ich Fujinaga
Chris Lintott
Scientists
Talk
Forum
Image
Classification
data reduction
Citizen Scientists
The challenge is to foster the co-constituted socio-technical
system on the right i.e. a computationally-enabled sense-
ma...
data  
method  
  
Web as lens
Web as artefact
The  Observatory  Quarter  
http://www.w3.org/community/webobservatory/
The  “Virtual”  
Observatory  
Technicalandbusiness
interface
Interop
http://www.w3.org/community/webobservatory
Digital  Music  
Collec8ons  
Student-­‐sourced  
ground  truth  
Community  
SoOware  
Linked  Data  
Repositories  
Supe...
1.  From  signal  to  understanding  
2.  Working  with  mul8ple  sources  
of  incomplete  and  inconsistent  
data,  wit...
Nigel Shadbolt et al  
Some  Social  Machines  
1.  Digital  >  Digi8sed  
2.  Machines  are  users  too  
3.  Digital  brings  new  decay  but  also  opportunity  for  
...
david.deroure@oerc.ox.ac.uk  
www.oerc.ox.ac.uk/people/dder  
www.scilogs.com/eresearch  
@dder  
Thanks  to:  Chris8ne  B...
David De Roure - What's so different about Arts and Humanities data?
David De Roure - What's so different about Arts and Humanities data?
David De Roure - What's so different about Arts and Humanities data?
David De Roure - What's so different about Arts and Humanities data?
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David De Roure - What's so different about Arts and Humanities data?

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David De Roure - What's so different about Arts and Humanities data?

  1. 1. David De Roure What’s so different about Arts and Humanities data?
  2. 2. ChristineBorgman
  3. 3. What  is  e-­‐Research?   •  Research  in  every  domain  is  increasingly  data-­‐  and   computa8onally-­‐intensive,  carried  out  collabora8vely  over   distributed  infrastructures     •  e-­‐Research  is  the  con8nuous  technological  and   methodological  innova8on  in  digital  methods  to  achieve   new  research  outcomes  –  using  new  forms  of  data  and   emerging  infrastructural  capabili8es   •  The  Oxford  e-­‐Research  Center  is  a  digital  methods   incubator  hos8ng  40  postdoctoral  researchers  conduc8ng   early-­‐adopter  digital  research  across  all  disciplines  
  4. 4. More people Moremachines Big Data and Computation Conventional Computation Social Machines Social Networking Cyberinfrastructure e-infrastructure Science 2.0 Citizen Science e-Research David De Roure
  5. 5. Economic  and  Social  Research  Council   Shaping  Society   •  Digital  Social  Research  Program   •  Social  Machines   •  Web  Observatories   •  Responsible  Innova8on   •  Centre  for  Interna8onal  Social   Media  Analy8cs  
  6. 6. F i r s t BioEssays,,26(1):99–105,January2004 http://research.microsoft.com/en-us/collaboration/fourthparadigm/
  7. 7. INT. VERSE VERSE VERSE VERSEBRIDGEBRIDGE OUT.  The  Problem   signal understanding Ich Fujinaga
  8. 8. Chris Lintott Scientists Talk Forum Image Classification data reduction Citizen Scientists
  9. 9. The challenge is to foster the co-constituted socio-technical system on the right i.e. a computationally-enabled sense- making network of expertise, data, models and narratives. Big data elephant versus sense-making network? Iain Buchan  
  10. 10. data   method    
  11. 11. Web as lens Web as artefact The  Observatory  Quarter   http://www.w3.org/community/webobservatory/
  12. 12. The  “Virtual”   Observatory   Technicalandbusiness interface Interop http://www.w3.org/community/webobservatory
  13. 13. Digital  Music   Collec8ons   Student-­‐sourced   ground  truth   Community   SoOware   Linked  Data   Repositories   Supercomputer   23,000 hours of recorded music Music Information Retrieval Community SALAMI
  14. 14. 1.  From  signal  to  understanding   2.  Working  with  mul8ple  sources   of  incomplete  and  inconsistent   data,  with  new  born-­‐digital  data   3.  Innova8on  and  sharing  of  new   digital  methods   4.  Challenges  of  resource   discovery  and  publica8on  of   new  digital  artefacts   5.  Importance  of  provenance   6.  Challenges  of  cura8on   7.  Increasing  automa8on  (and   risks  therein)     Commonali8es   Differences   1.  Specific  content  types  and   their  rela8onship  to   physical  artefacts   2.  Curated  collec8ons,  and  an   “infinite  archive”  of   heterogeneous  content,   richly  interlinked   3.  Specialist  digital  methods   4.  Publica8ons  are  subjects   and  records  of  research   5.  Emphasis  on  mul8ple   interpreta8ons  and  cri8cal   thinking  
  15. 15. Nigel Shadbolt et al  
  16. 16. Some  Social  Machines  
  17. 17. 1.  Digital  >  Digi8sed   2.  Machines  are  users  too   3.  Digital  brings  new  decay  but  also  opportunity  for   automa8on…  and  community  engagement   4.  SoOware  is  part  of  the  problem  and  part  of  the   solu8on   5.  Disciplinary  boundaries  are  a  legacy  and   transcended  by  today’s  research  ques8ons   6.  Towards  Social  Machines  for  Digital  Cura8on?     Messages  
  18. 18. david.deroure@oerc.ox.ac.uk   www.oerc.ox.ac.uk/people/dder   www.scilogs.com/eresearch   @dder   Thanks  to:  Chris8ne  Borgman,  Ichiro  Fujinaga,  Stephen  Downie,  Chris  Lintog,   Iain  Buchan,  Nigel  Shadbolt  

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