Nascent

The editorial I mentioned in this post is here. It's subscriber-only, but here is a snippet:

When looking at the future of scientific computing... it is easy to focus on the vast data architectures necessary for projects such as the LSST or the Large Hadron Collider at CERN, the European particle-physics laboratory near Geneva. The truly amazing story, though, is of the distributed power that ends up not in exceptional places such as the focal plane of a giant telescope, but spread out across the world; the power that allows data to be acquired from microfluidic chemistry sets and genome sequencers in labs around the world at astonishing rates... The fact that everyday computing is getting exponentially cheaper promises to vastly increase data flows of all sorts and to revolutionize the practice of science...

As computing gets ever cheaper, quicker and more powerful, scientists would do well to remember that, by being a demanding and stimulating 'user community' that engages the interest of companies such as Microsoft, Google and Intel, they can influence the development of the field, to everybody's benefit.

A very interesting Nature issue on computing in science. However, it would been great to see your analysis of distributed computing/ peer-to-peer networks. There are some interesting new projects such as Lionshare exploring the potential uses of peer-to-peer networks for scientific collaboration, as well as bioinformatics P2P projects like Chinook. I have collected some related bookmarks in Connotea. Would you consider covering this in Nascent in the future?

I enjoyed the issue, but was disappointed that there was almost no discussion of the fact that most scientists have no idea how trustworthy their programs are. If experimentalists don't calibrate their equipment and check the purity of their samples, their work is rejected out of hand. In contrast, only a handful of computational scientists test their programs thoroughly, and never (in my experience) describe what tests they've done, or why those tests lead them to believe that the output from those programs is anything other than plausible noise. If journals and funding agencies don't start insisting that computational work meet the same quality standards as benchwork, a "computational thalidomide" seems inevitable.

In addition to high performance computing, the ability of powerful computers that can sit underneath your desk and do computations that require clusters today will also make a significant impact.

It is critical that computational science become more ingrained in undergraduate and graduate (perhaps even high school) for some of the advances that nature talks about. There is still resistance to computational science and the belief that it is the realm of theorists.

Thanks, Anna.

I didn't know about these P2P projects, but I'd be interested to learn more, and maybe other Nascent readers would too. If you (or someone) is interested in writing a short guest item on this, please send it to me (t DOT hannay AT nature DOT com) and I'll consider posting it. Thanks.

Hi Greg,

Thanks for your interesting comments. With Stephen Emmott's permission, and for the benefit of other readers, I'm copying here his response when you raised a similar question to us via email.

Thanks for this feedback

Software QA is clearly a significant challenge in science, as we point
out in terms of software engineering in our report. And indeed, this is
indeed a challenge in general for highly complex software systems such
as those any successful software company produces.

There are several points in the report where we refer to the need for
reliable, 'trustworthy' software systems which encompasses and underpins
software "QA", including mention of the need for better software design
and analysis tools, the challenges and benefits of 'managed platforms'
and in particular the sub-section you refer to on 'Correctness' which as
you will undoubtedly know summarises the need for and benefits of proofs
and verification of complex software systems - the foundations for
software QA.

Furthermore, you might recall that we make clear our report is a summary
and an opener to generate discussion such as that you have initiated, so
thanks a lot for getting the discussion on this particular issue going
-- really very much appreciated. It was never our intention to
comprehensively cover in detail every aspect of every technological and
scientific issue.

If you'd be interested in offering any suggestions for how to improve in
this area, I'd be delighted.