I'm real glad to see this on the HN frontpage and I'm kind of surprised that I didn't submit it at some point...I joined the beta just to contribute some material/upvotes so it could be approved. I honestly don't use it that much on a day to day basis, but having had used it, and occasionally answering questions...it does fill a real niche that regular Stack Overflow doesn't.
If you were to ask me before, I'd think that the StackOverflow would be good enough because many, many data problems are programming related (how to parse one format, database optimization, etc)...but there are issues specific to data, such as denormalization...not how or necessarily when to do it at the database schema, but why...or rather, given a set of data (such as from the gov't) in which normalization was obviously not done...what is the most sensical compromise that you should do in organizing the data?
Anyway, hope more people get into it...I've worked in data for awhile and now, having to think about it, it's definitely a big enough field with enough questions to justify a vibrant SE board.
As somebody who has spent lots of time trying to find free (for academic use) data in natural language processing, I really hope this becomes quite popular.
It doesn't seem to be overly busy, but some of the questions caught my attention, and I was pleased to learn that the answers are actually friendly and helpful.
There's a lot of open data available, depending on what you are looking for. If I had time, I could probably spend it on this SE and earn points, count coup, or whatever. Instead I'm working with a couple of user groups helping local programmers analysts learn how to dig into it. We have a few specific data sets that we use for different types of analysis, demographic, mapping and financial.
As someone who upvoted but didn't comment: I'd like the site to get exposure so it will be more useful, but I don't have anything specific to say about it.
If you were to ask me before, I'd think that the StackOverflow would be good enough because many, many data problems are programming related (how to parse one format, database optimization, etc)...but there are issues specific to data, such as denormalization...not how or necessarily when to do it at the database schema, but why...or rather, given a set of data (such as from the gov't) in which normalization was obviously not done...what is the most sensical compromise that you should do in organizing the data?
Anyway, hope more people get into it...I've worked in data for awhile and now, having to think about it, it's definitely a big enough field with enough questions to justify a vibrant SE board.