Earlier quoted context omitted.
I am often told that I should keep my nose out of other science domain's business because they know more than I do. I've only heard such statements coming out of a few fields: math education, labor economics, climate science and psychometrics of race/gender. You should ignore such statements; they are nothing more than an attempt to bully you into accepting received wisdom from activists with a PhD. As an actual scie…
As another scientist I have to strongly second this . Some things might take real work on your part to understand though. Even within different fields of mathematics there are difficulties in understanding (complaint about this: http://www.math.rutgers.edu/~zeilberg/Opinion104.html ).
Keeping computers from ending science's reproducibility
61–63 of 63 posts
Re: Keeping computers from ending science's reproducibility
#62Reminds me of an interesting Wired article from 2008: "The End of Theory: The Data Deluge Makes the Scientific Method Obsolete" http://www.wired.com/science/discoveries/magazine/16-07/pb_t...
A fun article, but Peter Norvig of Google has said he feels like it severely misunderstands his work.
Re: Keeping computers from ending science's reproducibility
#63Earlier quoted context omitted.
"My group does this with every paper." Any links?
Sure. We started doing this last summer, and this is the first paper accepted for publication that uses the method. http://autonomy.cs.sfu.ca/doc/wawerla_icra10.pdf and here's a draft of our paper on the methodology, with rationale. Long paper: http://autonomy.cs.sfu.ca/doc/wawerla_submitted_2009.pdf Original short workshop paper: http://autonomy.cs.sfu.ca/doc/wawerla_rss09_workshop.pdf For context, here's the lab's…
From your draft paper,
"A few months ago, a graduate student in another country called me (Vaughan) to ask for the source code of one of my multi-robot simulation experiments. The student had an idea for a modification that she thought would improve the system’s performance ... we were able to offer the requesting student some code that may or may not be that used in the paper. This was better than nothing, but not good enough, and we suspect this is quite typical in our community."
Fwiw I've had a similair experience.
A few years ago I was reading Daphne Koller's "Using learning for approximation in stochastic processes" and it was a very elegant and powerful idea, but it didn't seem to me at the time that there was enough detail in the paper to implement the algorithm and I wrote to Dr Koller and asked if she had source code available. She replied that her student had departed a decade ago and the code was effectively lost.
Dr Koller was very helpful and clarified some doubts I had and in the end I managed to re implement the algorithm and so a happ ending after all but if code was archived and made public for every paper, it would have really helped.
Awesome that you guys are adopting this methodology.