Quandl: find and use numerical data on the internet
Quandl.com is a platform for numerical data that currently offers 6 million free and open time series datasets. Conceptually, Quandl aspires to do for quantitative data what Wikipedia did for qualitative information: create one location where quantitative data is easily available, immediately usable and completely open.
Open Economics and Quandl thus share a number of core values and objectives. In fact, at Quandl we are working to build part of the “transparent foundation” that is central to the Open Economics mission.
Quandl was invented to alleviate a problem that almost every econometrician knows well: finding, validating, formatting and cleaning data is a tedious and time consuming prerequisite to econometric analysis. We’re gradually reducing the magnitude of this problem by bringing all open time series datasets to one place, one source at a time.
To do this, we’ve built a sort of “universal data parser” which has thus far parsed about 6.4 million datasets. We’ve asked nothing of any data publisher. As long as they spit out data somehow (Excel, text file, blog post, xml, api, etc) the “Q-bot” can slurp it up.
The result is www.quandl.com, a sort of “search engine” for time series data. The idea with Quandl is that you can find data fast. And more importantly, once you find it, it is ready to use. This is because Quandl’s bot returns data in a totally standard format. Which means we can then translate to any format a user wants.
Quandl is rich in financial, economic and sociological time series data. The data is easy to find. It is transparent to source. It can be easily merged with each other. It can be visualized and shared. It is all open. It is all free. There’s much more about our vision on the about page.
Everyday Quandl’s coverage increases thanks to contributions made by Quandl users. We aspire to get to a point where publishers instinctively choose to put their data on Quandl. This has already started to happen because Quandl offers a solid, highly usable and totally open platform for time series data. We will work to perpetuate this trend and thus do our small part to advance the open data movement.