Asking "What datasets are available to me?" is sometimes the wrong question. A better way of going about the problem is asking something more specific like "How can I create a heat-map of U.S poverty?" The reason why the latter is better is that it not only focuses your attention on something do-able but it actually teaches you more about data analysis than just searching for datasets.
For example, to solve the question above you are going to be asking yourself the following followup questions:
1) Where do I get a map of the U.S?
2) How do I make a heat-map?
3) How do I feed in my own data into this heat map?
4) What colors do I use?
5) Can I do this real-time? Do I need a database? What language do I use?
6) Whats a FIPS code?
7) How do I find a poverty dataset with FIPS codes?
8) This poverty dataset doesn't have FIPS codes, but I can join it with this other dataset that does have FIPS codes.
Open datasets are hard to come by. It's potentially easier to find problems to solve by looking at the available datasets than seeking datasets for the problems you wish to solve.
When you want to create a new website do you start by looking at a bunch of clip art and images? Browsing through datasets such as the ones listed in this thread leaves me overwhelmed. I've never had any difficulty finding open datasets. If there is a dataset I need that doesn't exist or costs money, I find a way to create it from scratch.
Datasets aren't always quested for. Sometimes you want a specific dataset to solve a specific problem, and sometimes you'll take any dataset just to see what you can learn, or to make interesting infographics. Lists like this help the latter situation.
It may sometimes be the right question, it all depends on what the enquirer wants to with the data. This comment is just an exercise in answering a question that no one asked, I fail to see why it merited any upvotes.
It is just an example of an alternate viewpoint. My point is that sometimes you will have more success finding data for questions that interest you than looking at datasets that interest you and trying to come up with questions.
I likewise feel that this type of list of data sources fits a data collecting/hoarding mentality, rather than a problem solving one. It doesn't help me think of interesting things to do with the data.
Google or Amazon should offer to sponsor it and make the data accessible in their respective cloud computing platforms. There's tons of potential for data analysis / consultancy companies to work on this data and it's too big to process anywhere else.
I have a feeling this might be a bluff. This scare might just be politics as usual. It just doesn't make sense to cut this, especially if they're saving money.
Hackers & Founders SV is hosting a hackathon[1] in two weeks at the Hacker Dojo in Mountain View. It's going to be geared towards working with Factual's open data API.
Factual's[2] goal is to provide an API to connect all those available data sets, and they have a fairly impressive list of data sets available. Factual is very interested in hearing what datasets you want to work with, and they are willing to bust ass to get them available before the hackathon.
The software that they provide to go through the data is crappy, however (90's era).
I have an equally crappy but more useful to a computer scientist Common Lisp program that will pull out specific fields from the data set based on a list of field names. If you want that, I can dig it up for you.
Also, before you start parsing this, it's worthwhile to read the documentation to find out how the files are laid out, and what each field really means. These files are not relational databases, so if you're looking at it through those lenses, confusion will result. In particular, some things are already aggregated within the data set.
http://aws.amazon.com/publicdatasets/ which includes my former advisor's dataset (UF sparse matrix collection) which includes a matrix or two from my research.
I believe Steven Levitt used the Fatality Analysis Reporting System (FARS) from the national highway traffic safety administration (NHTSA) for his seatbelts vs carseats work:
Yelp has an API that returns business data in a given geographic area. You could probably get a list of zipcodes from wikipedia and then just loop through that.
We provide API access to more than 20 million articles (headlines, excerpts). People have done all sorts of interesting things with it - http://platform.newscred.com.
For example, to solve the question above you are going to be asking yourself the following followup questions:
1) Where do I get a map of the U.S?
2) How do I make a heat-map?
3) How do I feed in my own data into this heat map?
4) What colors do I use?
5) Can I do this real-time? Do I need a database? What language do I use?
6) Whats a FIPS code?
7) How do I find a poverty dataset with FIPS codes?
8) This poverty dataset doesn't have FIPS codes, but I can join it with this other dataset that does have FIPS codes.