A Year in The Life of a Computer

What does a year in the life of a computer look like?

Well, something like the map below! This is a map every bit of of mouse movement, every mouse click and every keyboard press I have done on my home and work computer over every day of a whole year.

2013-2014 [click for a bigger view]

To make it I wrote a little python script using pyHook to grab inputs in Windows, which I compiled to an .exe using py2exe. I set this up so that it starts recording the mouse movement, clicks, and keyboard presses after I log into my home or work computer. After 2 years it had collected nearly 10 Gb of data! This was far too much to look through by hand, so I wrote a second set of scripts to plot it to an image.

So what does it all mean? Well the map breaks down a bit like a normal calendar, with days of the week running from the top to the bottom of the map, and successive weeks running from left to right. The years and months are marked at the top of the map.

Within each day my computer activity is broken down by time. Time runs from the top to the bottom of each day, from midnight to midnight. Coloured speckles on the dark background indicate computer activity. It is easy to see that I use computers a lot, with a chunk of time from around midnight to 7 am when I am normally asleep, then smatterings of activity from around 8 am to midnight when I am at work or awake at home.

Different types of computer activity are shown in different colours.

The structure within each of the colours also contains information; distance in the horizontal direction corresponds to horizontal mouse position across my two screens (for mouse movement) which mouse button was clicked (for mouse clicks) and which key was pressed (for keyboard presses).

2012-2013 [click for a bigger view]

In these maps of usage some interesting structures jump out; you can spot the type of work I was doing with my computer based on the type of mouse and keyboard activity:

This is usage on a day where I was writing my PhD thesis. The keyboard (cyan) has loads of activity, while the mouse (magenta) did relatively little.

This is a day where I was mainly using Blender for 3D graphics. The mouse (magenta) has huge levels of activity, centred on just the left hand screen). The keyboard is hardly active except for the control and shift keys, which light up as a single column of bright cyan pixels.

It is quite scary how much information can be gleaned from these maps of computer activity. Without knowing which programs were open or which keyboard keys were being pressed it is still easy to work out where I have been, when I have been working, and the kind of things I was doing on my computer. Similar data can be collected remotely; particularly if an internet company tracks when and where you use the internet.

Stop for a second and think about the companies you interact with, and the data mining they can do. Think how much they can learn about you and your habits; Google and the websites you visit, your phone company and when and who you text and call, the supermarket you shop in and what you buy. These companies can work out what you are interested in, what you like and dislike, when you are awake and when you are asleep. This is big data, and it is valuable and it is powerful. Big data is how Target knew a man's teenage daughter was pregnant before he did!

Software used:

pyHook and py2exe: Data logging.

ImageJ: Data plotting.

Inkscape: Plot annotation.

Tree of Plants

Everyone knows what plants are like; they have leaves and roots, flowers and seeds. Or do they? All of these classic features of plants are actually relatively recent developments in plant evolution. Conifers don't have flowers, ferns don't have seeds or flowers and moss doesn't have leaves, roots, seeds or flowers! Leaves, roots, flowers and seeds are all features that evolved as plants adapted, starting at something like seaweed, to life on the land.

This term's issue of Phenotype has a bit of a focus on plants, and my research comic for this issue focuses on how plants evolved and adapted to land. You can download a pdf of this feature here, the full issue for the summer (Trinity) term will be available soon here.

While I was making this I started reconsidering just what the plant life cycle looks like, as a classic school education about how plants reproduce isn't very accurate! The classic teaching is that the pollen produced by a flower is like sperm in mammals (and humans), and the ovum in the flower is like the egg in mammals. In fact pollen and the developing seed are more like small haploid multicellular organisms, gametophytes, that used to be free living. If you go back through evolutionary time towards ferns then the gametophyte is a truly independent multicellular organism. Go back further still and the bryophytes spend most of their time as the gametophyte.

If you imagine the same evolutionary history for humans then it is easy to see how different this life cycle is to animals; if the ancestors of humans had a life cycle similar to ferns then, roughly speaking, ovaries and testicles would be free-living organisms that sprout a full grown human once fertilisation successfully occurs. I can't help but think that would have been a little strange!

Software used:
Autodesk Sketchbook Pro: Drawing the cells.
Inkscape: Page layout.

Figuring Out Good Figures

The main point of doing scientific research is to share the things you discover. After all, what is the point if discovering something if no one knows about it, to work or learn from it? Science is typically shared in research papers, but the actual date is normally just in the figures (the graphs and images) while the the text describes what it means (as I have talked about before). Sharing scientific data is important, therefore good design of figures is also important. So how do you make a good figure?

Each term I make a research comic for the Oxford University Biochemical Society magazine called Phenotype. This one is all about figuring out figures. How do you make a good one, and how can you avoid getting tricked by bad ones?

Check out the comic here, the whole issue is available to download for free from here.

Software used:
Inkscape: Page layout and drawing.

The Shape of a Cell

Each term I make a research comic for the Oxford University Biochemical Society magazine called Phenotype. The topic for this cartoon; the function of cell shape in bacteria. You might not know, but bacteria can have one of a huge variety of different shapes, but why cells have a particular shape is not a commonly asked question. To quote Kevin Young: "To be brutally honest, few people care that bacteria have different shapes. Which is a shame, because the bacteria seem to care very much.".

Check out the comic here, the whole issue will be available to download for free from here soon.

Software used:
Autodesk Sketchbook Pro: Drawing the cells.
Inkscape: Page layout.

Decoding The Encoding

Decoding The Encoding is my new infographic/research comic feature in the Oxford University Biochemical Society (OUBS) magazine Phenotype. This term's feature is all about the ENCODE project, a massive international research project to move beyond just knowing the sequence of the human genome and moving towards understanding how that translates into its function. Check out the full issue here.

Software used:

Python: General data parsing and reformatting.

ImageJ: Creating the chromosome map plots.

Inkscape: Page layout and design.