ENTRIES TAGGED "scala"

Four short links: 22 December 2010

Four short links: 22 December 2010

Etherpad, Scala, Journalism, and Mazes from Ruby

  1. ietherpad — continuation of the etherpad startup. Offers pro accounts, and promise an iPad app to come. (via Steve O’Grady on Twitter)
  2. Scala Collections Quickref — quick reference card for the Scala collections classes. (via Ian Kallen on Twitter)
  3. Raw Data and the Rise of Little BrotherTurns out, despite the great push for citizen journalism, citizens are not, on average, great at “journalism.” But they are excellent conduits for raw material — those documents, videos, or photos.
  4. Theseus 1.0 — impressive source maze builder in Ruby contributed to the public domain. (via Hacker News)
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Four short links: 25 May 2010

Four short links: 25 May 2010

European Economic Crisis, Scaling Guardian API, Cheerful Pessimism, and Science Mapping

  1. Lending Merry-Go-Round — these guys have been Australia’s sharpest satire for years, filling the role of the Daily Show. Here they ask some strong questions about the state of Europe’s economies … (via jdub on Twitter)
  2. What’s Powering the Guardian’s Content API — Scala and Solr/Lucene on EC2 is the short answer. The long answer reveals the details of their setup, including some of their indexing tricks that means Solr can index all their content in just an hour. (via Simon Willison)
  3. What I Learned About Engineering from the Panama Canal (Pete Warden) — I consider myself a cheerful pessimist. I’ve been through enough that I know how steep the odds of success are, but I’ve made a choice that even a hopeless fight in a good cause is worthwhile. What a lovely attitude!
  4. Mapping the Evolution of Scientific Fields (PLoSone) — clever use of data. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985-2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.
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