Open data is, basically, the idea that certain data should be freely available to everyone to use as they wish, without restrictions from copyright, patents or other mechanisms of control. A piece of data is open if anyone is free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and/or share-alike.
Sir Tim Berners-Lee, the inventor of the World Wide Web talks about open data in this TED talk:
“Opening up data is fundamentally about more efficient use of resources and improving service delivery for citizens. The effects of that are far reaching: innovation, transparency, accountability, better governance and economic growth.”
The idea would be: if you make your datasets open to the public, more researchers would have the opportunity to play with it and see what gives; potentially expanding knowledge. This can be particularly helpful for those operating on limited resources of their own: a lot of researchers using open data come from the global South/open data is being very successfully used by research informing policymakers in developed countries; see, for example, Ghana’s open data initiative or the Open Data Research network.
Now, Sir Berners-Lee makes another interesting distinction:
As for the explanation, Livingston has got a quite provocative-one:
“One reason for their higher scores might be education – college graduates outscore high school or less by nearly 8 points out of 32. It may be that nonbelievers, Jews, and Mormons are more likely to have finished college. […]
But another reason that these groups scored higher may be their position as religious minorities. Jews and Mormons have to explain to the flock how their ideas are different from those of the majority. Atheists and agnostics too, in their questioning and even rejecting, have probably devoted more thought to religion, or more accurately, religions. On the questions about Shiva and Nirvana, they leave even the Jews and Mormons far behind.
For Protestants and Catholics, by contrast, learning detailed information about their religion is not as crucial. Just as White people in the US rarely ask what it means to be White, Christians need not worry about their differences from the mainstream. They are the mainstream.”
Today, for instance, i want to talk about the “voodoo poll”, so called because it’s about as scientific as voodoo (and presumably because for the serious researcher seeing it reported as a serious poll in the media feels like a stab in the heart from a distance).
A “voodoo poll”, or open access poll, is one where a non-probability sample of participants self-select into participation.
In human language: sampling is the use of a subset of the population to represent the whole population. In probability sampling (random sampling), we have ways of calculating the probability of getting any particular sample, and therefore we can rigorously infer from the sample to the general population.In non-probability sampling, we do not; and therefore we need to use them with care.
As I’m writing this post right now, we’ve been knowing for sure for several hours: with 55% of “no” votes, Scotland is staying in the UK. On a quick look at my Twitter feed, I’m getting a mixed bag of relief, celebration, introspection, ‘what next’ concern and that rant from Trainspotting (nsfw).
The one comment that caught my eye, however, came from Sussex Uni fellow Ben Stanley.
A rogue poll might have had far-reaching consequences for the British constitution. This is a good argument for stats education.