Understanding Data-Intensive Science

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Understanding Data-Intensive Science

• Sabina Leonelli
• Egenis
• Department of Sociology and Philosophy
• s.leonelli_at_exeter.ac.uk

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Context The Rise of Data-Intensive Science and
the Difficulties in Making Sense of It

• New ways to produce, store and disseminate data
  are affecting how scientists work, think and
  collaborate a qualitative shift to
  data-intensive science
• Despite heated debates on the significance and
  impact of big data and data management tools
  (e.g. internet databases), no clear
  characterization of data-intensive science ---
  difficult given the distinctive methods, objects,
  materials, aims and technologies characterizing
  each of fields involved.
• Further, no systematic study of how this approach
  affects existing philosophical views on
  scientific epistemology, as expressed within
  contemporary philosophy of science and underlying
  science policy

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Towards a Philosophy ofData-Intensive Science

• Aim systematically analyze whether and how the
  epistemology of science is changing in the
  digital age, through an empirical, comparative
  study of data-intensive practices and their
  results across different scientific areas and
  time periods
• Method philosophy of science based on empirical
  studies of science (philosophy of science in
  practice)
• Historical and sociological research on
  scientific practices
• Collaborations with natural scientists (e.g.
  plant scientists, bioinformaticians and system
  biologists)

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Specific Topics

• Unsustainability of internet databases for
  biomedical data in the long term need for new
  funding support mechanisms
• Huge impact of databases and classification
  systems on how data are interpreted and re-used
  not yet fully recognised by biologists
• Shifts in division of labour in scientific
  research role of computer scientists and
  database curators?
• Key role of model organism communities, e.g.
  Arabidopsis thaliana, in driving future research
  in biology as well as how biologists think of
  organisms

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Activities and Results

• Publications in science journals and in
  philosophy, history and social studies of
  science monograph in progress.
• Forthcoming special issues on the characteristics
  of data-intensive biology, large-scale scientific
  research, and translational research.
• Science policy
• Consultations with funding bodies (e.g. BBSRC and
  NSF)
• Consultations with United Nations and EU on
  impact of digital technologies on science and
  society (Global Young Academy)