Automatic data collection: On the availability of non-target dataavailability of non-target data

Despite the Hypothetico-Deductive method is applicable to some scientific research, where the creative process and the empirical testing go separately, I question that all scientific progress can be seen under this perspective.

The overcome of computers in all scientific fields has increased the amount of available data and has drastically changed the data acquisi-tion process. At the time when Karl Popper wrote “The logic of scientific discovery”, obtain-ing data to study certain phenomenon required a specific survey or experiment, aimed to obtain results for a particular topic. Remote sensing, computer simulations, data logs, among other, allow nowadays for the acquisition and storage of huge amounts of data. Sometimes, the data are stored just because there is the chance to do

so, and not for any particular experiment.

The data collection has become a human ob-session, and every possible variable of piece of information susceptible of being analysed is now logged and processed. There are terabytes of all sort of data stored in hard disks and servers waiting for a researcher to milk them, including Internet navigation, the number of vehicles that use a particular road, the budget of a country or the stocks market, among a neverending list of issues. Almost everything nowadays is quantifi-able, and this quantification is stored and often analysed.

How does this fact affect the scientific ap-proach? What is its effect in the progres of knowledge and in the scientific methodology?

We don’t need any more to design an experi-ment to collect the data, we can just download it from internet and transform it into graphical material to be interpreted.

The present work is a clear example of this situation: the Argo floats were originally de-signed to monitor the temperature and salin-ity of the upper global ocean, and to introduce the data in weather forecast models. However, it was soon realized though the float positions could give valuable information about the ocean

velocities if correctly processed. The studies here presented show the information extracted from the trajectory files of the Argo floats in or-der to obtain the ocean velocities, applied to two ocean regions: the equatorial Atlantic Ocean and the Tasman Leakage. Despite being true that the statistical study relates to the global dataset, it is also true that there is a lot of in-formation in the Argo trajectory data to be ex-plored and tested. There is a large amount of knowledge yet to be built.

This can be afforded in two ways. The Argo data can be used, on one hand, to test different previous theories about the ocean currents, pro-cessing the data in order to verify or falsify early hypothesis. On the other hand, the data may be plotted aimless, just to explore what the infor-mation stored in all these floats has to tell us.

We can plot a map of zonal velocity of an ocean region unknown to us, and observe the graphi-cal information, trying to comprehend what we see, on the basis of our previous knowledge. It is like carrying an experiment without a previous hypothesis, and asking ourselves what question could the data we are obtaining be the answer for.

We are not saying this is how science works,

mentioning the fact that nowadays we have the results of hundreds of thousands of experiments that have been aimless performed, and that the order of the steps of the scientific method pro-posed by Popper are somehow inverted.

Despite total ignorance will probably not be the case when approaching a new ocean region, or any dataset in general, it is true that we can, from a basic knowledge of a certain question, ex-plore a related dataset in order to extract more information susceptible for being be latter con-trasted with what others said before. This is the path to deepen in our knowledge, facing data against new perspectives, that should lead us to a better comprehension of phenomena, through the combination of intuition (which builds on previous knowledge) and the information ex-tracted from data.

There is another question related to the need of verifying or falsifying a hypothesis: many questions in science are not about true or false, but rather about accurateness in the descrip-tions. Descriptive oceanography would be a good example, since we are not necessarily say-ing weather the existence of a current is true or false but rather describing the current, its mass,

climate. So what method would apply in these cases?

These considerations about research and data analysis contrast with the hypothetico-deductive scientific method, in the sense that we do not always need a previous hypothesis to face a problem, and we can just say: “Let’s see what I can get from these data!”

Paul Feyerabend, in his book “Against the Method” (Feyerabend, 1975) does a dras-tic allegation in favour of an anarchist sci-ence, deeply contrasting with the hypothetico-deductive method. Feyerabend goes far be-yond a formal criticism of the adequateness of the hypothetico-deductive method, questioning also how rational criticism may lead to the loss of freedom, to a degeneration of the human essence. He presents the hypothetico-deductive method as the dehumanization of science, and quoting Kierkegaard, states: “Could it be possi-ble that my activity as an objective (rationally criticist) nature observer weakens my strength as human being?”

Feyerabend’s arguments also point to the fact that the scientific method does not respond for lots of the discoveries that have been made,

nor for many scientific approaches that brought knowledge beyond. Feyerabend does not de-fend pure inductivism in the terms Francis Ba-con proposed it in 1620, pointing to the role of experience beyond the contrast of previous hy-potheses, and makes relevant the role of observa-tion in the formulaobserva-tions of newer (possibly par-tial) hypotheses, that will complement the ac-tual knowledge once tested and verified (or not falsified).