Month: June 2008

My brother Andy is doing some pretty cool stuff this summer.  He heads off this week to Siberia, to do research on climate change in the Arctic.  Here’s the web site for the project he’s working on, and here’s a piece from Science News.

A friend of mine asked me what I thought of this article in Wired, which argues that the existence of extremely large data sets is fundamentally changing our approach to data. The thesis is roughly that we no longer need to worry about constructing models or distinguishing between correlation and causation: with the ability to gather and mine ultralarge data sets, we can just measure correlations and be done with it.

This article is certainly entertaining, but fundamentally it’s deeply silly. There’s a nugget of truth in it, which is that large data sets allow people to do data mining – that is, searching for patterns and correlations in data without really knowing what they’re looking for. That’s an approach to data that used to be very rare and is now very common, and it certainly is changing some areas of science. But it’s certainly not the case this somehow replaces the idea of a model or blurs the distinction between correlation and causation. On the contrary, the reason that this sort of thing has been important to science is that it’s a great tool for constructing and refining models, which can then be tested in the usual way.

Two of the specific cases the article cites are actually examples of precisely this process. As I understand it, Google’s search algorithm started in more or less the way it’s described in the article, but over time they refined it by means of a process of old-fashioned model-building. Google doesn’t rank pages by simply counting the number of incoming links; that’s one ingredient in a complicated algorithm (most of which is secret, of course) that is continually refined based on tests performed on the data. Craig Venter’s an even better example: sure, his approach is based on gathering and mining large data sets, but the reason scientists care about those data sets is precisely so that they can use them to construct old-fashioned models and testable hypotheses.

The case of fundamental particle physics, which is also discussed in the article, is quite different. In fact, it’s totally unclear what it has to do with anything else in the article. Fundamental particle physics has arguably been stuck for a couple of decades now because of a lack of data, not an excess of data. There’s not even the remotest connection between the woes of particle physics and the phenomenon of mining large data sets.

Here’s another way to think about the whole business. The distinction between correlation and causation was always a distinction in principle, not a mere practicality. It’s not affected by the quality and quantity of the data.

You can see the slides for all of the talks at the workshop I was just at in Paris,  including the three talks I gave. (As I said in my last post, this was a pretty specialized workshop, so you probably don’t want to unless you’re a researcher who works on the microwave background.)

According to the International Astronomical Union, Pluto is still not a planet, but it is a Plutoid.  If I recall correctly, at the time the original naming decision was made, there was a proposal to call the class of Pluto-like objects “Plutons,” but that was rejected, in part because “Pluton” is already the name of Pluto in various languages, including French.  I guess “Plutoid” solves that problem.

I don’t much care about Pluto no longer being considered a planet, but I do think that the IAU made a poor choice of naming conventions.  According to the new system, Pluto and similar objects are not planets, but they are “dwarf planets.”  That’s right: a dwarf planet is not a planet.  That’s a needlessly confusing naming convention, especially since it’s inconsistent with the terminology in the rest of astronomy: dwarf stars are stars, and dwarf galaxies are galaxies.

That’s old news now, of course: the new wrinkle, namely the introduction of the term “Plutoid,” neither solves nor worsens that problem.

Even though it’s all in the past, here are a couple of observations about the Pluto-classification flap:

1. Obviously, no interesting scientific questions hinge on whether we choose to classify Pluto as a planet.  I recall a news article at the time of the Great Naming Controversy saying that the future of NASA’s New Horizons probe was in doubt because of the reclassification of Pluto as a non-planet.  That’s an obviously ridiculous notion: As Abraham Lincoln could tell you, the nature of a thing doesn’t change because of what we call it.

2.  The justification for the Great Renaming was to have a precise physical definition of the word “planet.”  Mike Brown has argued against the need for such a definition: Why not just consider the word “planet” to mean the nine bodies that it has traditionally meant?  By way of analogy, the word “continent” refers to a conventional set of seven land masses.  We don’t really need to justify why it’s that list of seven (Why aren’t Europe and Asia considered as one? Why not include Greenland?).   Often, science needs precise, objective definitions in order to proceed.  But it’s not clear that in this case anyone was being hampered by the arbitrary nine-body definition of the word “planet.”  What, exactly, was the problem that the IAU solved?