Alexandre Trilla, PhD - Data Scientist | home publications


-- Thoughts on data analysis, software development and innovation management. Comments are welcome

Post 67

Numerical computation platform for the technical university: values to decide on a proprietary or open-source software model


A discussion on the adequacy of a proprietary numerical computation platform like Matlab or a free open source alternative like Octave is an old story already. But I feel it would be inadequate to stick with rigid values only because of one's preference for a single particular software development model. To me, one is just as good as the other. And I opine with certain authority being a TA at the university who led the migration from Matlab to Scilab for the practise sessions of Discrete-Time Signal Processing (a graphical interface for simulating dynamic systems was required, therefore xcos was needed), which is part of the Master's degree programme in Telecommunications Engineering.

Needless to say, I have a preference for open-source software, but in an educational environment such as the university, choosing an open platform for teaching is more of an act of responsibility than it is of taste. Here are the reasons why I bothered remaking from scratch the whole lot of practise sessions (see my teaching materials) with Scilab:

  • It enables the students to fully reach to the detail of their implementations from all analysis perspectives. This is the essence of hacking in the end, which in turn was born at MIT, one of the most prestigious technology universities in the world.
  • It saves students (and the university) a deal of money as they are not forced to buy a proprietary software licence for conducting the lab experiments (the over-dimensioned commercial product is simply not necessary).
  • It does not entice the students to commit the illegal activity of software piracy through breaking the contract they are forced to accept with a proprietary software license.

With these arguments I don't mean that Matlab is a bad product at all in any sense! On the contrary, as long as people acquire it, I assume it must provide some differentiated solutions for specific needs. But in an university environment, where the gist of a technical class is teaching off-the-shelf methods to fledgling engineers, open-source software packages like Octave, Scilab or SciPy, offer high quality numerical computation platforms that are orders of magnitude more powerful than it is needed. What is more, I have used them myself for more serious computing tasks, and in my experience, strictly speaking, they are truly comparable to their proprietary counterparts.

Now, while this seems to be a reasonable an sound argument (IMHO), related companies seem to disagree and complain to the university to prevent the publication of such opinions and to remove the teaching materials that we instructors offer for free for the sake of education. If such complaints are not simply dismissed as the university is supposed to always protect the educational freedom, students are in threat of being tangled with the monopoly dictated by these companies (and shamefully accepted by the university). So this is what happened to Guillem Borrell with Mathworks and the Universidad Politecnica de Madrid. And since I share his indignation wrt this issue, I wanted to echo his open letter to Mathworks. I wonder if this company will also complain to Andrew Ng for the similar opinions he expressed in the materials he prepared for the Machine Learning class.

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