From The R Backpages 2 by Joseph Rickert.
From the post:
Quandl contiues its mission to seek out and make available the worlds financial and econometric data. Recently added data sets include:
- ALFRED: 10,000 vintage economic datasets from the Federal Reserve's archival site.
- Commodity Futures Trading Commission: Over 8,000 datasets with commitment of traders information, for futures and options, both new and legacy formats.
- PsychSignal: Bullish/bearish sentiment index and volume ratios for 6,000+ stocks.
- Penn World Table 8.0: 5,000 datasets from the latest Penn World Table (version 8.0).
- US Treasury: Marketable debt statistics, including average maturity of issuance.
- FDIC: Banking statistics including assets, liabilities, failures and deposit insurance.
- Center for Applied Studies on Applied Economics: Brazilian agricultural price indexes.
- London Platinum and Palladium Market: Platinum and Palladium prices.
- Federal Reserve Bank of Philadelphia: Philly Fed's new GDP+ indicator.
- Swiss Exchange: EOD data for over 250 stocks.
- Stock Exchange of Thailand: 6 market indexes.
- Liv-ex: Fine wine price indexes.
- Beta Arbitrage: Minimum variance portfolios and beta portfolios.
- International Securities Exchange: ISE sentiment indexes for equities and ETFs.
- Renaissance Capital: Monthly US IPO statistics.
- Osaka University: Japanese equity volatility indexes.
- Nikkei: 15 daily indexes published by the Nikkei group.
- UK Office for Budget Responsibility: Economic indicator forecasts up to 2063.
- Federal Reserve Economic Data: Added 1000s of new indicators from FRED.
- Wall Street Journal: Over 100 commodity spot prices added.
- Bureau of Labor Statistics: In progress, currently over 180,000 datasets imported.
That’s a big jump since our last post when Quandl broke 5 million datasets! (April 30, 2013)
Any thoughts on how many of these datasets have semantic mapping data to facilitate their re-use and/or combination with other datasets?
Selling the mapping data might be a tough sell because the customer still has to make intelligent use of it.
Selling mapped data on the other hand, that is offering consolidation of specified data sets on a daily, weekly, monthly basis, that might be a different story.
Something to think about.
PS: Do remember that a documented mapping for any dataset at Quandl will work for that same dataset elsewhere. So you won’t be re-discovering the mapping every time a request comes in for that dataset.
Not a “…butts in seats…” approach but then you probably aren’t a prime contractor.