Ross Shannon

Currently Listening to:

Barenaked Ladies — It’s All Been Done

A literature review is a standard part of any postgraduate’s endeavours, and usually makes up the majority of your first year or two. A good review sets up the landscape that you’re going to work within, saving you from duplicating effort and allowing you to identify the key players in your field. You don’t necessarily have to reel off a big document summarising your reading, but if you do it’s a fine head start on the first chunk of your thesis.

I had started my lit review last year, but it’s easy to fall into the trap of merely printing and filing papers without having read them. Then, in December at our second annual SRG-fest Joe gave an inspiring talk about structuring a literature review intelligently. Among his suggestions were to choose a handful of key conferences in your area and read every paper published in their proceedings for the last few years. For me, these conferences are places like InfoVis, ICAC, Pervasive and CHI.

Secondly he suggested building up a “mindmap” of the research areas that you’re actively engaging in. This has proven to be a very worthy excercise.

My (intimidating!) PhD mindmap

When drawn up like this my research interests seem both nicely structured but also worryingly broad. And I left out the stuff I’ll likely need to understand but currently have no interest in, like semantics, embedded systems and parallelism. My reading has been branching out a bit recently too; since I’ve started tracking my bookmarks on del.icio.us I discovered that I’m actually more interested in things like sociology and psychology than I thought.

If you imagine all the possible research that could be done in our field as a pie chart, the area I’m going to explore will end up being a thin sliver in that chart. Aaron always said that his job as my supervisor was to keep me anchored in that segment and not wander too far outside of it. Looks like he’s got his work cut out for him.

So it was around this day last year that I joined up with the rest of the SRG to start on the merry road to this thing we call a PhD. It’s been a great year; in many ways, it was the fifth year of college that I so desired when my four years were up last September. I’ve bashed out two papers, done some travelling, worked with Intel briefly, and become ensconced with a terrific band of smart, interesting people. And a few goons.

It took a lot of prodding and empty promises, but our two new arrivals this year mark the culmination of Marko’s plan to get all the old gang together into postgraduate studies.

My research area is pretty well defined, and can be summed up as “The visualisation of autonomic systems.” As part of our year one requirements we all had to write up our hypotheses and plan for the future, which I feel is pretty solid, though doubtless will change drastically. Autonomics as a field is fairly young, the term having only been coined by IBM in 1990s and still being ill-defined. So there’s plenty of stuff that could be done.

My biggest weakness at the moment is that I have struggled somewhat into getting into the mode of paper reading. As I was trying to explain to Aaron earlier this week, it has taken me a long time to attune to the paper-reading process. So used am I to getting the latest techniques daily through weblogs in four paragraph bursts, that facing into a ten page — possibly very boring — academic paper has been a challenge, and the main thing I aim to fix in the next few months.

You better learn it fast; you better learn it young,
'Cause, "someday" never comes.

Currently Listening to:

Kate Bush — Cloudbusting

As part of the new structured PhD program in operation in CSI, we all have to give a talk on something relevant to our research.

I chose/it was suggested to me to present “fisheye” visualizations, a technique described by George Furnas in his seminal paper “Generalised Fisheye Views”, and the 20 years on review paper, “A Fisheye Follow-up: Further Reflections on Focus + Context”. This is a really interesting data filtering approach (and not a visual technique as the name might imply).

The talk seems to have gone down well, which is nice, as I have some workshop talks coming up later this month. Creating this presentation, the first I’ve given since I left IBM last September, has proven to be very good practise for preparing a talk, and then — erk! — fielding questions. My slides are linked below.

Talk: Information Visualization
Using View & Data Distortion

And here are some of the things I learned from my presentation:

1. Never, ever try and say “specificity” out loud in front of other people. That is all.

Currently Listening to:

The Strokes — Trying Your Luck

So, I got my first paper finished and submitted in time to a workshop at AVI 2006 entitled “Context in Advanced Interfaces.” Worked all the way up to 15 minutes before the deadline (which I’m told is “decent buffer”). An arduous but rewarding experience, and I couldn’t have done it without the help of our terrific support structures in the SRG, namely our academics and postdocs. As Lorcan put it so nicely, “Welcome to the anti-rat race dude.”

Update 2006/04/08: Got ‘er in.

Currently Listening to:

Arcade Fire — Neighbourhood #1 (Tunnels)

No, not the as-yet-unknown-quantity that is the paper I’m trying to put together for AVI 2006. I just got word from one of the editors at O’Reilly that the book I contributed to, PHP Hacks, has been published and is in shops. I should be getting my ‘author copy’ in the post over the next few days. Huzzah!

At this early stage in my PhD, it would be instructive to look ahead and take a wild, naïve guess as to what kind of deliverable simulation I may end up producing at the end. If only to look back and laugh later on.

First of all; the challenge, as I understand it at this time:

To model an autonomic system, specifically one inside an automotive machine, most likely a car. A modern car will have a wide array of sensors and actuators, and the system designer needs to be able to see how they are performing, in real time.

At the moment I’m envisioning a car, modelled in 3D, driving out onto a classic Tufte-ian grid.

A car that I’ll never be able to model.

The best guess at the moment on what kind of 3D I’m going to use would be some modification of the “Source” engine, which powered Half Life 2. The SDK comes with the game and I’ve played around with it. It’s very powerful.

Once the car comes to a stop, the outer paneling flies off, exposing a simplified version of the car’s innards. Thus begins the simulation, with (hopefully live) data being fed into the system and the display showing various activities on the screen.

Statistics like network activity and CPU usage will be on-screen at all times, in the form of pie-graphs and “sparklines” to show trends over time. Atomic events such as sensors being activated and sensors failing will be shown as alerts, possibly through a picture-in-picture system that shows a zoomed-in version of the full model at the point where the incident occurred. Clicking on this PiP box will then focus the main view on this area, through a camera movement. This device was used in the household simulation game, “The Sims”, to announce events like burglaries and housefires.

So, that’s what I’ve got so far. Of course, I’m leaving out all the bits about multiple displays and pulling elements from the main screen down onto a PDA or something crazy. It’s early days yet though, so this could still go in any direction.