Further thoughts on eresearch services

I’ve been watching the eresearch services thread from the eresearch 2013 conference. I’m beginning to regret not having gone - it looks to have been more interesting than I expected, but that’s life.
A lot of people seem to be getting interested in eresearch services. I’ve already expressed my opinions about such things, but generally a heightened level of interest is probably a good thing.
However there seems to be a bit of conflation going on, so here’s my $0.02:

• eresearch is not the same as big data - big data refers to the handling of very big data sets and their analysis using inferential analyses, eresearch refers to the application of computational and numerical techniques to research data
• eresearch is not the same as digital humanities - digital humanities really refers to the move to using electronic resources in the humanities - this move may enable the application of eresearch techniques to humanities research
• astronomers, physicists, economists and many more have been using inferential analyses such as cluster analysis for many years - eresearch is not new, but its spread and penetration is
• the rise of cheap (cloud) computing and cheap storage are key drivers in the adoption of eresearch by allowing bigger datasets to be handled more easily and cheaply

In short, you can do perfectly good eresearch with an old laptop and an internet connection, you don’t need all the gee-whizzy stuff, all you need is a problem, the desire to solve it, and a little bit of programming knowledge.
Any eresearch service is going to be there to support such work, by faciliating access and providing advice and support to researchers, in fact it’s taking on the role of research support that belonged to computing services in the days before the commodification of computing and the rise of the internet when in the main computing meant time on a timesharing system to run some analytical software …

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