1. Bottom-up, Top-Down, and other social and technological dynamics of e-Research Kathryn Eccles, Eric Meyer, Ralph Schroeder Oxford e-Social Science Project (OeSS) Oxford Internet Institute University of Oxford Presented at the UK All Hands Conference, Oxford, December 2009

2. Top-Down and Bottom-Up Two predominant ways of thinking about e-Research Both are misleading… –Top-down because It suggests supporting a ‘society’ of researchers (in fact, niches) It suggests supporting structure (in fact, provisional efforts only) –Bottom-up because It includes individual ‘garage’ efforts that are not sustained and/or cumulative It includes individual efforts that are not shared - technically, socially, or in terms of goals A definition of e-Research: distributed, shared digital tools or data for knowledge production

3. Beyond Top-Down and Bottom-Up Social movements around technological systems or artifactual cores The conditions for stabilizing these new technologies…(not necessarily technological superiority) –Coalitions –Compatibility –Task uncertainty Specific to e-Research is that these are distributed and shared, so commitment is an added condition Diffusion, ‘community’, sustainability are also necessary

4. Top-down and bottom-up again… The two may not be mutually exclusive, but one or other may depend on the outcome of certain conditions (community creation, resources, etc.) Resources, data, and tools have different conditions (as ideal types, even if they overlap)… –Resources (not part of knowledge production) depend mainly on maintenance and user support –Data depends on user contributions, standards, and competition with other data sets –Tools depend on user-friendliness or robustness, usefulness and critical mass

5. Some examples Swiss BioGrid: a set of tools and data without an ‘infrastructural’ home Swedish National Data Service: an infrastructure with a community of users in the making Genetic Association Identification Network: a shared data infrastructure with still-emerging standards Pynchon Wiki: a rapidly forming community with indefinite task finalization EGEE: a polymorphous large organization in organizational transition to another(s?) (EGI) VOSON: a popular social science tool in search of resources for robustness

6. Implications Adoption cannot be conceived of in individual terms for e-Research technologies Conditions for resources are different (also in underpinning natural science, social science and humanities) from tools and data A fourth category is the ‘accidental e-Researcher’ – example: Web 2.0 tools (though the same conditions as for tools, data and resources apply) The stabilization of socio-technical systems at different scales, functionality levels, and stages…

7. Oxford Internet Institute University of Oxford Ralph Schroeder Senior Research Fellow ralph.schroeder@oii.ox.ac.uk http://people.oii.ox.ac.uk/schroeder Kathryn Eccles Research Fellow kathryn.eccles@oii.ox.ac.uk http://www.oii.ox.ac.uk/people/faculty.cfm?id=138 Eric T. Meyer Research Fellow eric.meyer@oii.ox.ac.uk http://people.oii.ox.ac.uk/meyer Oxford e-Social Science Project