I was doing some fiddling around with Google Fusion Tables. If you have not tried them, they are worth checking out. Basically, the way it works is this. You can create "tables" within Google Documents. A table is different than a spreadsheet. Tables can then be "merged" or related like you relate tables in a relational database. As fusion tables sits right now, it does not look you can configure join properties, like you can in a SQL query.
A good place to start is watching this video tutorial.
The video walks you through the basics. Although, I could not get the merge tables part to work. So, I just put together my own data, tried that, which worked. (This is the tutorial page for Google Fusion Tables.)
This is my end product.
To create that, I merged (or "fused") this table of (A) US State populations for 2009 with (B) this table of the geographic area polygons of each state for plotting on a map.
This is a visualization of the table I created (i.e. you can embed the result of what you create within a web page or share a link to your tables or merged tables):
This shows the power of creating data, making it available as "data" and not an HTML page, PDF, or a sloppily created Excel file. Anyone can create data files using Excel, basically all you do is "save as CSV". What is a little harder is understanding how to create a CSV file which is easy for a computer to work with.
This also shows the power of linked data. The semantic web. Properly modeled XBRL-based financial information contributes to the semantic web of linkable data.
In my example, I simply took an Excel spreadsheet which had population data, linked that population data to another data set which provides the polygon which can be used to visualize the state on a map such as Google Maps, linked the two data sets together via the postal code or ID which both data sets had; and then my population data can be visualized on a map rather than just as a list.
Of course, visualizing information on a map is not something which is new. What is new is the ease with which you can do it. And all this will get easier, and easier, and easier. Plus as more and more data sets are available the utility of all this will become more clear.
This is linked XBRL-based information. It is rather rudimentary, but if you look close and use your imagination a bit, you can see what is going on. You can see taxonomy information organized by "company" but you can also view the information by "component" (i.e. the balance sheet of each company). I hope to have some better examples of this where you don't need to use your imagination as much.