Oxford e-Social Science Project
e-Science: The view from the
social sciences
Jenny Fry and Ralph Schroeder
Oxford Internet Institute
How can social science best support
research with novel technologies?
• Non-technological barriers to e-science e.g.
– Trust in distributed collaboration, data provenance,
access and ownership of data, confidentiality and
privacy in social data, social protocols around
technical standards and interoperability.
• Dual complexity: diversity of domain-specific
disciplinary expertise required in developing
solutions on one hand, and heterogeneity of
research practices being supported by e-science
on the other
Mapping current social science approaches to escience (with illustrative concerns)
Practical/usability
Attempted
neutrality/value free
(How appropriation can be enhanced
through refining understanding of
practice, user representations, and
human computer interaction)
(Measuring dimensions of distributed
communication and collaboration)
Advocacy/steering and
aligning structures
Critique/reflexive or
prospective
(Fostering institutional, economic and
legal structures that enable distributed
communication and collaboration.
Promoting a particular type of open
and accessible e-science)
(Social implications of e-science;
ability to deliver on claims; policy)
Examples of some earlier approaches
• Advocacy (steering and aligning
structures)…
– David and Spence’s project-based typology
• Critique (reflexive/prospective)…
– Wouters and Beaulieu computation-centric escience based on disciplinary analysis
• Others?…
Social and technical organization of eSciences: dimensions and factors
• Differences in degrees of interdependency
and uncertainty across disciplines, as
applied to…
…is technology development a driver?
…what is the balance between computer
science and disciplines being enhanced?
…disciplinary organization?
…how closely or loosely coupled are
collaborations?
To add to David and Spence’s classification of e-science
Discipline (based on
PIs parent discipline)
Application area
Tools
Quantitative social science
Social anthropology
Health
Transport
Business
Grid-enabled social
databases
Video based technologies
Multimodal digital records
(text/audio/visual)
Interfaces for collaborative
research
Modelling and simulation
Data sharing and integration
Collaborative
arrangement
Value-addedness
(claims)
Technical
Infrastructure
Intra-institutional
Inter-institutional
Academic/commercial
research laboratory
Virtual communities
Support centres/training
Stimulating uptake
Harmonizing practice
Support for social studies of
technology
Collaborative storytelling
New forms of digital record
Evidence-based policy
Mixed-method approaches
Interfaces
Software (including
bespoke)
Middleware
Portals
Ontologies
Wireless networking/GPS
Tracking devices
Applied statistics
Computer science
Psychology
Engineering
Geography
Environmental science
Humanities computing
Different levels of issue based analysis
• Issues at the macro- or policy level
• Issues at the systems and networks level
• Specific issues which apply to particular
scientific domains or cut across domains
• Issues pertaining to specific projects or
cases
• Individual or isolable issues within projects
Summary
• Non-technological challenges to appropriation
• Mapping current social approaches to e-(social)
science
• Variation in mutual dependences and technical
uncertainty across disciplines
• Different levels of analysis
• Can analyses of levels, typologies and social
science be brought to bear on one another?