scientific software posts

Of software and Science. Reproducible science: what, why, and how

At MLOSS 15 we brainstormed on reproducible science, discussing why we care about software in computer science. Here is a summary blending notes from the discussions with my opinion.

“Without engineering, science is not more than philosophy”    —   the community

How do we enable better Science? Why do we do software ...

MLOSS 2015: wising up to building open-source machine learning

Note

The 2015 edition of the machine learning open source software (MLOSS) workshop was full of very mature discussions that I strive to report here.

I give links to the videos. Some machine-learning researchers have great thoughts about growing communities of coders, about code as a process and a deliverable ...

Software for reproducible science: let’s not have a misunderstanding

Note

tl;dr: Reproducibilty is a noble cause and scientific software a promising vessel. But excess of reproducibility can be at odds with the housekeeping required for good software engineering. Code that “just works” should not be taken for granted.

This post advocates for a progressive consolidation effort of scientific ...

Publishing scientific software matters

Christophe Pradal, Hans Peter Langtangen, and myself recently edited a version of the Journal of Computational Science on scientific software, in particular those written in Python. We wrote an editorial defending writing and publishing open source scientific software that I wish to summarize here. The full text preprint is openly ...

Personal views on scientific computing

My contributions to the scientific computing software ecosystem are motivated by my vision on computational science.

Scientific research relies more and more on computing. However, most of the researchers are not software engineers, and as computing is becoming ubiquitous, the limiting factor becomes more and more the human factor[G ...