E-Research for Education

Social and cultural aspects of e-research, grid and/or cyberinfrastructure become increasingly an attractive research topic for social scientists and cultural anthropologists. It is not surprising why. Interesting and important research themes can be found almost on the surface of e-research phenomenon. As an example, at least two research questions are represented in the following titles of the papers presented at e-research conferences this year:

• M. Daw, R. Procter, Y. Lin, T. Hewitt, W. Jie, A. Voss, K. Baird, A. Turner, M. Birkin K. Miller, W. Dutton, M. Jirotka, R. Schroeder, G. de la Flor, P. Edwards, R. Allan, X. Yang, R. Crouchley (2007) Developing an e-Infrastructure for Social Science. Paper presented at the Third international conference on e-social science, Ann Arbor, MI, US. URL

Question 1: Is there a limit for productive collaboration?

• J. Dalziel, C. Nguyen, R. Warouw (2007) Macquarie University: ASK-OSS, DRAMA and RAMS: eResearch support from MELCOE. Paper presented at the E-Research Australasia 2007. Brisbane. URL

Question 2: Is there a limit for effective(?) technical communication?

1. The difference in numbers of co-authors of presentations in e-research and educational conferences is astonishing. Is this difference a reflection of collaborative nature of e-research or a reflection of governmental funding policies? Is there a limit for productive collaborative work? From my longitudinal observations, the numbers of co-authors in e-social science conferences have been growing almost exponentially over the last four years. Does this mean that Moore’s law apply not only to computer power but also to collaboration in e-research? Social scientists probably could check Metcalfe’s law’s validity in such collaborations. A different aspect of this phenomenon is academic authorship. It is not new that writing and authorship are not necessarily two related aspects in scientific disciplines, while this is a big transformation in social sciences and humanities.

2. The number of new acronyms in e-research has been growing exponentially too. Information system designers have been always creating and using them generously. But before it was possible to read (and understand) research papers and policy documents (at least titles) without looking to a glossary. Is this still an effective way for communicating complex technical ideas? How to remember all this ever growing and ephemeral ontology of e-research definitions?

Finale: Technology vs. sociology

The cultural, social, political and organisational are all tightly interwoven with technological and in many different configurations. An interesting reading about how such techological configurations shaped by and shaping the sociology of e-research might evolve is the following paper:

• Edwards, P. N., Jackson, S. J., Bowker, G. C., & Knobel, C. P. (2007). Understanding infrastructures: Dynamics, tensions, and design. Report of a workshop on “History & theory of infrastructure: Lessons for new scientific cyberinfrastructures". National Science Foundation. URL

“When you are designing a cyberinfrastructure, there are several things going on simultaneously. You are trying to deploy the latest computing infrastructure to:

• Permit distributed collaborative work;
• Engineer changes in the organization of scientific work (e.g. altering reward structures for database work, or encouraging early sharing of results);
• Enable interdisciplinarity in a way which will get scientists from disparate communities working together.

This work is principally social and organizational. Yet in general designers are not trained to recognize these dimensions of their work practice – hence the horrific image of throwing new products over the wall to their designated community. <…> Cyberinfrastructure will not be built from the center with a single design philosophy. Instead, it will be built from the ground up, and in modular units. <…> It’s simply unrealistic to talk about designing cyberinfrastructure. Rather, each project produces a set of modules which ideally interoperate to create a larger whole” (p. 33)

Technology drives sociology. Sociology drives technology. The dialectical nature of change, life and science.