1. e-Science: The view from the social sciences Jenny Fry and Ralph Schroeder Oxford Internet Institute Oxford e-Social Science Project

2. 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

3. Mapping current social science approaches to e- science (with illustrative concerns) Practical/usability (How appropriation can be enhanced through refining understanding of practice, user representations, and human computer interaction) Attempted neutrality/value free (Measuring dimensions of distributed communication and collaboration) Advocacy/steering and aligning structures (Fostering institutional, economic and legal structures that enable distributed communication and collaboration. Promoting a particular type of open and accessible e-science) Critique/reflexive or prospective (Social implications of e-science; ability to deliver on claims; policy)

4. 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 e- science based on disciplinary analysis Others?…

5. Social and technical organization of e- Sciences: 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?

6. To add to David and Spence’s classification of e-science Discipline (based on PIs parent discipline) Applied statistics Computer science Psychology Engineering Geography Environmental science Humanities computing Application area Quantitative social science Social anthropology Health Transport Business Tools 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 Intra-institutional Inter-institutional Academic/commercial research laboratory Value-addedness (claims) 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 Technical Infrastructure Interfaces Software (including bespoke) Middleware Portals Ontologies Wireless networking/GPS Tracking devices

7. 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

8. 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?