During the Watson-related madness earlier this year I wrote a script to put all of the Jeopardy! game data from J! Archive into a SQL database (they have no API so I parsed the very-broken HTML for each game). I never ended up doing anything with the data, but there’s been renewed interest around the house in this data so I took some time to make a word cloud of the Jeopardy! categories.

The format was a shortened pub trivia, with songs played after reading each question:

• 1 round of 4 questions with each question being worth either 1, 3, 5 or 7 points (you decide, you can only use each value once)
• 1 special picture round (2 points for each item correctly identified)
• 1 round of 4 questions with each question being worth 2, 4, 6 or 8 points (akin to the first round)
• 2 final questions on which you wager up to 10 points each (win or lose what you wager)

Without further ado, here are the questions:

Famous Nerds: Who wrote in a famous RFC, “be conservative in what you do, be liberal in what you accept from others”?

Databases: What does ACID stand for?

Networking: How many bytes are there in an Ethernet address?

Systems Programming: What is the only UNIX syscall that returns twice?

Data Structures: This colorful binary tree is self-balancing and contains no data in the tree’s leaf nodes – what is it?

Operating Systems: Which process typically has the PID of 1 on a UNIX system?

Computing History: Which of these technologies was not invented at XEROX PARC: Ethernet, The Mouse, The Windowing GUI, laser printer?

SciFi/Fantasy: Who is the Kwistaz Haderach?

Video Games: What item must you retrieve from the Dungeons Of Doom in Nethack?

Role Playing Games: What does THAC0 stand for?

And of course, we had a picture round: ID The Programming Language & ID Carrier/GDS By IATA Code (hey, we’re an airline software company, I have to have some airline trivia).

I won’t post the answers here but feel free to post your answers in the comments (and be aware there’s a few correct answers to some of these questions).

Also, if you’re a nerd looking for a job at a cool place to work, check out ITA’s current job offerings. Not to spam my readers but it really is fun to work at a place where you can host a nerd pub trivia and 10 teams join the fun.

When I’m not being a computer nerd I’m often studying music (I’ve even created website which helps me study), and in an effort to keep me and my friends making music I’ve started Iron Musician, where my friends and I must create at least a minute of music once week or owe $5 to the beer pool.

Take a listen to some of the entries and feel to free to provide some constructive criticism.

In what was a very productive session of procrastinating on doing my guitar homework I ended up making my own ear training site. So, if you’re in need of some ear training, please take a look at Minor Seventh.

I built the site on SoundManager 2 (which regrettably requires Adobe Flash, because JavaScript has no native way to play sound), jQuery and jQuery UI. I’ll work on an HTML 5 version once someone sends me a free iPad.

I’d love some feedback on the site if you end up using it. Upcoming features include:

• Listening mode, where pressing the interval buttons plays the interval
• Chord sound training
• The option to change the root note to a random note
• The option to play only the arpeggio, not the chord
• New samples
• Progression training (identify a set of chords by location in the key)

Big thanks to Jessica McKellar, Mike Fisher, Greg Price, Todd MacGarvey, Giles Hall, and the others who helped work out all the bugs. Would you like a new feature or a change? Post a comment here or send some feedback from the ‘Submit Feedback’ link on Minor Seventh!

My friends and I frequently get lost in Wikipedia. I’ll start out searching for something innocuous, like neutrino, and then suddenly I’m learning all about tanning addiction. This happens so often that my girlfriend suggested that it would be fascinating to plot the various trips through Wikipedia by datamining the Firefox history database, and since she is busy with her thesis I stole the idea and spent a few hours writing a Python script to visually display my Wikipedia wanderings.

Firefox 3 stores its history in a SQLite 3 database file in your profile directory; on OS X that database lives in ~/Library/Application Support/Firefox/Profiles/cn3x93q2.default, and the database file we’re interested in is places.sqlite.

The history database schema is described here, but the two tables we’re interested in are moz_places and moz_historyvisits. The first, moz_places, has the URL, title and other data related to the links we’ve visited. What it doesn’t have is information on the paths we have a traversed to get to the URLs in moz_places – that information is in moz_historyvisits. moz_historyvisists has internal references which let us find out where we’ve been (the column from_visit) and a reference to the moz_places table via the place_id column.

How I got from neutrino to tanning addiction.

A very talented data architect I know helped write (entirely wrote is maybe more accurate), this query:

SELECT
curr.id, curr.url, curr.title,
prev.id, prev.url, prev.title,
1, t.visit_date
FROM
moz_places curr, moz_places prev,
moz_historyvisits frm,
moz_historyvisits t
WHERE
t.place_id = curr.id AND
frm.place_id = prev.id AND
frm.id = t.from_visit AND
curr.url LIKE 'http://en.wikipedia.org/%' AND
prev.url NOT LIKE 'http://en.wikipedia.org/%'

This query returns all Wikipedia URLs that are the starting points of my journeys through Wikipedia by finding all of the Wikipedia links I’ve visited whose referrer is not Wikipedia itself. With a few changes to the last clauses we can find all the URLs whose referrers are Wikipedia links (ie, the waypoints in my travels through Wikipedia). Finally, by asking for a curr.url which is not part of Wikipedia but which has a prev.url that is Wikipedia, we know when we’ve left Wikipedia.

My script outputs graphs in Dot format and JSON. The JSON output is in a representation that is compatible with JIT, a web 2.0 AJAXy graphing library, the output of which you can see in the title graphic of this post.

I’ve put the script up on github and called it FoxyGraph (be kind; it was written in a few hours for a specific purpose and is probably full of bugs). I’ll be updating FoxyGraph later with more interesting visualizations of my Firefox history, but for now you can see the immense clickable web 2.0 hypertree of my Wikipedia wanderings.