GNU Astronomy Utilities manual

1.2 Science and its tools

History of science indicates that there are always inevitably unseen faults, hidden assumptions, simplifications and approximations in all our theoretical models, data acquisition and analysis techniques. It is precisely these that will ultimately allow future generations to advance the existing experimental and theoretical knowledge through their new solutions and corrections.

In the past, scientists would gather data and process them individually to achieve an analysis thus having a much more intricate knowledge of the data and analysis. The theoretical models also required little (if any) simulations to compare with the data. Today both methods are becoming increasingly more dependent on pre-written software. Scientists are dissociating themselves from the intricacies of reducing raw observational data in experimentation or from bringing the theoretical models to life in simulations. These ‘intricacies’ are precisely those unseen faults, hidden assumptions, simplifications and approximations that define scientific progress.

Unfortunately, most persons who have recourse to a computer for statistical analysis of data are not much interested either in computer programming or in statistical method, being primarily concerned with their own proper business. Hence the common use of library programs and various statistical packages. ... It’s time that was changed.

Anscombe’s quartet ¹ demonstrates how four data sets with widely different shapes (when plotted) give nearly identical output from standard regression techniques. Anscombe argues that “Good statistical analysis is not a purely routine matter, and generally calls for more than one pass through the computer”. Anscombe’s quartet can be generalized to say that users of a software cannot claim to understand how it works only based on the experience they have gained by frequently using it. This kind of subjective experience is prone to very serious mis-understandings about what it really does behind the scenes and can be misleading. This attitude is further encouraged through non-free software². This approach to scientific software only helps in producing dogmas and an “obscurantist faith in the expert’s special skill, and in his personal knowledge and authority”³.

It is obviously impractical for any one human being to gain the intricate knowledge explained above for every step of an analysis. On the other hand, scientific data can be very large and numerous, for example images produced by telescopes in astronomy. This requires very efficient algorithms. To make things worse, natural scientists have generally not been trained in the advanced software techniques, paradigms and architecture that is taught in computer science or engineering courses and thus used in most software. The GNU Astronomy Utilities are an effort to tackle this issue. GNU Astronomy Utilities are built on the basis of the GNU general public license (GPL), giving the users complete “freedom” over them, see Your rights. We further add the requirement (on the authors of Gnuastro) that an astronomer, who is not necessarily trained in computer science or engineering, will need minimal requirements and preparations to understand and modify any step if they feel the need to do so, see Why C programming language? and Design philosophy.

Imagine if Galileo did not have the technical knowledge to build a telescope. Astronomical objects could not be seen with the Dutch military design of the telescope. In the beginning of his “The Sidereal Messenger” (1610) he cautions the readers on this issue and instructs them on how to build a suitable instrument. Before he actually saw the moons of Jupiter, the mountains on the Moon or the crescent of Venus, he was an anti-Copernican and was “evasive” to Kepler⁴. Science is not independent of its tools.

Bjarne Stroustrup (creator of the C++ language) says: “Without understanding software, you are reduced to believing in magic”. Ken Thomson (the designer or the Unix operating system) says “I abhor a system designed for the ‘user’ if that word is a coded pejorative meaning ‘stupid and unsophisticated’.” Certainly no scientist (user of a scientific software) would want to be considered as such. Roughly 5 years before special relativity and about two decades before quantum mechanics fundamentally changed Physics, Kelvin is quoted as saying⁵:

There is nothing new to be discovered in physics now. All that remains is more and more precise measurement.

If scientists are considered to be more than mere “puzzle solvers”⁶, they cannot just passively sit back and wait for others to build the tools that form the basis of all their interpretations and working paradigms. Today there is a wealth of raw telescope images ready (mostly for free) at the finger tips of anyone who is interested with a fast enough internet connection to download them. The only thing lacking is new ways to analyze them and dig out the treasure that is lying hidden in them to existing methods and techniques.

New data that we insist on analyzing in terms of old ideas (that is, old models which are not questioned) cannot lead us out of the old ideas. However many data we record and analyze, we may just keep repeating the same old errors, missing the same crucially important things that the experiment was competent to find.

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GNU Astronomy Utilities manual, November 2015.