The Whisky Fringe Tasting Tracker generated a couple of hundred datapoints over the course of two days (after Neil gave it a crack on the Sunday, and a few of us had played with it on the Saturday). The data we have available is pretty simple, and associates opinions about whiskies against the times that those opinions were recorded.

This lets us look at a couple of things from the off:

• What was the sampling rate like over the course of the day? Did it get quicker near the end when time was constrained, did we start off quickly and wind down early?
• Did our sentiment towards the drams being tasted change over the course of the afternoon?

I charted some of the data using our company Scott Logic’s Visiblox charting component in a pretty rough-and-ready fashion. By way of a quick summary:

• A PHP file generates a JSON object containing the various metrics
• A custom Silverlight control hosting a Visiblox chart is coded to expose some ScriptableMember methods that directly manipulate the axes and data-series of the hosted chart, allowing Javascript on the HTML page hosting the Silverlight control to programmatically add data and configure axes
• Note that this isn’t the way the Visiblox component’s intended to be used – I did it in this way as a fun experiment, to be written up in a subsequent post

For now here’s some static images:

Sampling rate

First off we see the aggregate sampling rate. Each bar represents the total number of drams sampled (across all people using the system) in a given 15 minute time period. While the event started at 2pm, we didn’t actually get started on sampling until about 2.20pm (with the rest of the time spent actually getting into the venue and waiting for a few stragglers). Further, the tables started getting cleared at 5.45pm so there’s a corresponding lack of data there.

• Around 4pm there’s a sharp drop-off as everyone camped out at their chosen ‘half-time orange’ stand – these are the rarer whiskies of which you can try one. We also seemed to use the subsequent wee while taking a breather.
• Once the half-time orange period had ended things pick up substantially, possibly as people realised that time was no longer on our side.
• There was another minor panic right near the end of the day as the time when stands packed up approached, though it’s clear that by about 5.30 everyone was pretty much done.

Likes and dislikes

Here we’re charting the same data as above, but split out into those drams that were marked as ‘liked’ vs those marked as disliked. Dislikes are given a negative score to push them below the axis. It seems like there was a period about 45 minutes after the half-time orange where we were more critical of what we were trying, perhaps as a result of having recalibrated as a result of really liking the half-time whiskies. However, it’s a little difficult to tell (and in fairness, we don’t have enough data points with so few people using the system).

Sentiment

Sentiment’s a tricky thing to gauge. My initial attempt subtracts the number of whiskies marked as ‘disliked’ from the number marked as ‘liked’ in each 15 minute bucket, giving a net number of liked whiskies in the period. This is then divided by the total number of whiskies sampled during that 15 minute window, giving a normalised value between 0 and 1:

• Values close to 0 suggest that more whiskies were disliked than liked in the period (that is to say that sentiment was negative overall). Zero values also occur when no tasting took place (such as the 4pm half-time orange lull).
• Values close to 1 suggest that more whiskies were liked than disliked in the period (or that sentiment was positive overall).

With some of the buckets having so few samplings within them (for example, the 5.30ish bucket has only three samplings), the measure is very sensitive to noise but it’s an interesting diversion nonetheless.

Each year the Royal Mile Whiskies Whisky Fringe showcases the wares of the whisky industry in the picturesque settings of Mansfield Traquair. For £20, you have four hours in which to wander round 30 or so stands sampling any of the ~250 whiskies and ~30 rums on offer.

Upon entry you get three things – a printed programme booklet, a biro and a tasting glass. I’ve tended in the past to try to take notes in the booklet, but it requires an unusual manoeuvre of trying to hold the tasting glass and booklet in one hand while scrawling (with less success the later in the day you are) with the other.

So on Thursday night I threw together a quick mobile-friendly website for myself and a few friends to use to track which whiskies we taste on the day and which we particularly like or dislike.

The interface is as simple as possible to allow one-handed operation on a phone – phone in one hand, sampling glass in the other. The list of whiskies is presented without much fanfare with a alphabetical jump-list at the top for navigation. Users can say that they either liked, disliked or simply tasted a given whisky which is recorded in a MySql database along with a timestamp such that we can piece together the events of the day after the fact.

It remains to be seen whether it’ll hold up for the day (having effectively had to teach myself PHP in the space of a night for this one, it’s probably not the most robust implementation I’ve ever been involved in)…

After the BBC announced that they were going to enter into a timeshare of sorts for the live TV rights to Formula 1 from 2012 onwards there’s been a fairly vocal crowd on Twitter, Facebook, the BBC message boards and petition sites making their views known. And those views are, understandably, almost universally negative. At time of writing, the ‘Keep F1 Coverage On The BBC For All Races From 2012‘ petition on PetitionBuzz has over 28,000 signatures and nearly 20,000 Facebook likes.

Since I’d intended this to be a technical blog, I figured that there wasn’t much better a way of starting off than hammering out some code over a single malt to track the progress of the petition as a chart:

A cron job running every 15 minutes first scrapes the petition site for the number of signatories, which is stored in a MySQL database against a timestamp. The above graph is then refreshed and saved to disk, such that it’s always in line with the latest data but not forever being generated on-the-fly. The graph is generated using the jpGraph library (the free version) with the actual incantations effectively copied-and-pasted from a sample on the website – I was going for quick and dirty with this one, and good Lord is it that.