This month my selections of visualisations to share are all ones which have been derived from large sets of data. Following on from my discussion last month about whether the aim of a great piece of data visualisation should be to tell a story or to allow for audience exploration of data, these are a mixture of data-set representations, some showing a clear story, others allowing the reader to find their own questions and start exploring and others which are a little bit of both.

How safe is flying?

My first selection is sadly very topical given the number of aviation accidents which have been in the news in the past few weeks.  It’s a gathering of all fatal commercial passenger plane incidents over the past two decades, using colour and size to represent the causes of death and the number of fatalities in each, with an introduction ahead of the visualisations which provides strong reassurance that air is still by far the safest method of travel. In the snapshot below, taken from the main exploratory visual, you can see the huge big orange (orange = crime) bubble which represents the twin towers disaster in 2001.

Fatal flight incidents including 9-11

It’s possible to hover over each event to find more details and it’s possible to filter by both flight stage and incident cause.


Worldwide migration

This next visualisation draws on a paper published in Science this month. The birth and death locations of more than 150,000 notable individuals across history have been visualised (blue for birth, red for death). This five minute video gives some insight into the changing migration patterns over the past several centuries, including pilgrimages from Europe to the US and the resulting movements from East to West America.

Trend in the US of individuals moving from the East to the West coast

US Migration

Then on a similar topic, the next visualisation I’ve chosen is a lovely representation of migration within the US over the past century. There are separate charts for each state, which can be viewed either as “migration into X state” or “migration from X state”. They all have the same colour key, splitting the US into four main regions to avoid the potential confusion of having different colours for all 50 states.

Then each chart shows how trends for migration have changed. For example, the below representation of migration out of Waashington D.C. shows an increasing reduction in the proportion of people who were born in Washington D.C. who have chosen to move out of the state in their lifetimes, with Maryland in the NorthEast being the key destination and Virginia in the South taking second place.

Migration out of Washington D.C.
A nice thing about these charts is how the ordering changes so that the bands are ordered from highest to lowest in each year, creating a ribbon effect but also making the information in the chart clearer for the reader.

Californian drought

These scrollable charts show how the drought in California has worsened over the past 4 years. It’s also possible to view them as an animation, which is maybe quicker, maybe not – but as an animation it’s harder to stop and look at anything that catches your eye. It’s an interesting question then … is the animation a better or worse view?
I’ve chosen this as an example because I like the small multiple charts, how many representations of similar visuals can tell a story more effectively than lines or bars on one picture.

Finally, for beauty

This isn’t a visualisation from an enormous dataset, but rather one which is only possible because of the increasing trend for people to wear technology which records every nuance of their daily routine (or lack of it). This is a fascinatingly beautiful visualisation of the preparation of 7 runners for the Nike Women’s 10k run. Computer algorithms run over the daily data from the 7 women chosen create twisted fibres showing their training patterns. Interpret them as you will.