Keynote talk by Rufus Pollock at Open Data Holyrood, December 10 2013.
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Today I was at Innovate UK to speak in the panel on “Big Open Data”. This was a chance to expand on the ideas I presented at the OECD Foresight Forum on Big Data in November and also to connect with our recent post on Open Data and My Data.
Slides from my talk today introducing the first Open Economics International Workshop organized by the Open Knowledge Foundation Working Group on Open Economics.
Mary Meeker of KPCB put out a nice piece in October entitled “USA inc” on how much financial trouble the US is in:
Summary: here is an increasing amount of open data but friction in (re-)using it is still far too high. We can reduce friction via e.g. packaging data better (cf software where packaging and automated publishing and download are a core part of the ecosystem). Open Data Protocols is an initiative producing simple protocols and formats for working with data RFC-style. Included is a concrete data packages proposal which emphasizes simplicity in the form of flat files, CSV, JSON and the minimal info to make this useful (like column types!).
Interesting October 2012 working paper from the ECB: BANK RATINGS WHAT DETERMINES THEIR QUALITY? by Harald Hau, Sam Langfield and David Marques-Ibanez. Here’s the abstract (emphasis added):
This paper examines the quality of credit ratings assigned to banks in Europe and the United States by the three largest rating agencies over the past two decades. We interpret credit ratings as relative assessments of creditworthiness, and define a new ordinal metric of rating error based on banks’ expected default frequencies. Our results suggest that rating agencies assign more positive ratings to large banks and to those institutions more likely to provide the rating agency with additional securities rating business (as indicated by private structured credit origination activity). These competitive distortions are economically significant and help perpetuate the existence of ‘too-big-to-fail’ banks. We also show that, overall, differential risk weights recommended by the Basel accords for investment grade banks bear no significant relationship to empirical default probabilities.
While we thought it before (see the excellent material in the Levin report on the crisis), it’s always good to have intuition and anecdote borne out by proper data.
Research and notes on Node.JS libraries. This is ongoing and gets updated from time to time!
S3 / Google storage libraries
- Does not support GS – https://github.com/LearnBoost/knox/pull/68
Command line tools
- jsdom (jquery support!)
Today I had the opportunity to talk at REFORM’s event Future is Open: Open Government and Data Transparency in a session on Data-driven services: Open data and public service reform. Here are the slides.