OpenSource advocates have long maintained that by having more eyes looking at the code, they are able to develop better software than traditional closed source methods. While this story isn’t a slam-dunk for OpenSource vs. closed source, it certainly shows that there are benefits to sharing data.

A more chilling thought is how many more advances in medical science may be lurking out there if only scientists were encouraged to share? As some commentators point out, the “madness” of the patent system strongly encourages researches to keep their data secret. This begs the question, are patents hindering progress in some areas of science rather than helping it?

It’s no secret that predicting the weather is hard and even the experts frequently get it wrong, but I seem to be noticing that when they get it wrong, they always tend to error on the optimistic side. For example, if the 5 day forecast predicts 20C, it actually ends up being 15C. Being off by a few degrees is understandable but if it truely was a science, then it should be wrong the other way approximately the same amount of times. So when they predict 20C, half the time we should get 25C but it never seems to work that way.

I know very little about forecasting but from what I understand, all forecasters use computer models. Usually they run a few different models then set the forecast based on the consensus. If my theory is correct, my data will show that on average the forecast is always too optimistic and that will prove that the computer models are wrong.

If that turns out to be the case then it raises some other questions.

First of all, the weather modelers should already know this. They have access to all the forecast data and can easily compare the predictions with the actual temperatures and then adjust their models accordingly to make them more accurate. Why haven’t they done that?

A wrong forecast may not seem like a big deal but does it have other implications? Do the same people that wrote the software which makes short term forecasts also write the climate models that predict global warming?

It’s going to take some time to gather enough information to be meaningful (at least a  year), and maybe I’m wrong? Once I’ve gathered enough data to make some pretty graphs I’ll post a link to a site where everyone can take a look at the results.

Though neither invention could be called an open standard, it’s a classic example of how more liberal rules for usage lead to wider adoption and technological dominance.

It’s a pattern that has repeated itself throughout history and continues to impact technology today. Companies would do well to heed the lessons of the past.

Since I’m an IT professional I often explore various technologies and work on projects which are quite complex and interesting. Along the way you learn a lot of small details which are often quickly forgotten which is quite frustrating the next time you have to do something similar. Mainly these things are not recorded because there is no simple mechanism to do this nor any easy way of storing this information. And so I’m hoping I can capture some of these details here on this web site so I’ll have a sort of personal knowledge base.