Warp Factor Eleven

The UK Onshore Geophysical Library's William Smith - Interactive has wound me up.  It represents a cartofail that's extremely common.

William Smith produced his classic and beautiful maps of the Geology of England and Wales in the early 1800s. They are stunning. making them available digitally is also wonderful but...and this drives me nuts - why oh why, time and time again do we see people scan these wonderful old maps and then warp them to Web Mercator?

There's a reason Smith chose the right projection for his maps....because it was the right projection.

Would it not be easier to just change the projection of the web map service you're using and then allow the maps to be seen as intended? Instead we get the maps stretched and distorted. Horizontal text also becomes stretched and sits on a curve. It looks absurd.

200 years ago Smith made his map right. The very least we can do is honour it by using modern technology to re-present his work properly, not turn the warp factor up to eleven.

What's the point?

Campaign group 38 degrees have produced a map of the NHS crisis in the UK that purports to show the location of signatories to a petition demanding improved resources for the NHS.

Click here to put in your own UK postcode and here if you want to just see the map I've screen grabbed below
.

Each signatory is shown with a lovely blue Google map pin (zoom out to get the full 'death by map pin' effect just for kicks). Here's the cartography bit: "To protect anonymity, we randomly assign locations in the constituency for each signature. No real locations are shown."

Say what?

So you take data, you ignore location other than it exists within a certain boundary, you give it a false location and then put it on a map. Let's just zoom in a bit...

There you go. Mr Gordon Bennett in that lovely house round the corner signed the petition. Except he didn't, did he, because this is a randomly placed marker. Someone in the area whose postcode cannot define a particular property has had their data pinned to Mr Bennett's house. I suspect that pisses them both off.

This sort of map tells this huge lie while at the same time purporting a level of precision that assigns the unreality to very particular houses on the map.  It's a verson of the ecological fallacy in the interpretation of statistical data where  inferences about the nature of individuals are deduced from inference for the group to which those individuals belong. In this case precise location...albeit randomly assigned.

If you're going to randomize the data for display (a good thing) then aggregate it into a choropleth (you clearly have the boundaries which you're using to demarcate the selection) or show the postcode totals as a proportional symbol or do anything other than use point markers that make no sense and, worse, impute nonsense. Total cartojunk that obfuscates the real message. Put the damn numbers on the map. Make them big. Make those crucial messages the visual.

ht @StevenFeldman

Voronoi footballs

Via Keir Clarke's Maps Mania I saw the latest voronoi designed map this morning. Made by Guus Hoekman, the map uses voronoi polygons to subdivide the world such that each polygon represents a spatial partition that contains one football club.

It's a neat coded solution for the novice football supporter to simply locate themselves and then determine which is their closest team. 

Why get all cartonerdy about it then? Well, partly because I've not had a good cartonerd rant for a few months (despite several maps causing much ire) but moreso, because maps like these never seem to go beyond providing a small technical solution to an overly simplistic question. The real world is far more complex than maps like this ever try to take on. Closest is not necessarily the way you choose your team.

Football (probably most sport fandom) is a hugely complex soup. There are three rules for supporting an English football team. First, you support the team you were born and raised closest to so in that respect the map could be deemed a reasonable effort. Proximity gives ample opportunity for the young supporter to shift allegiance if parents move around a bit as well, before your fandom settles. The point here is that you don't need a map to tell you you're local birth-right football team but being close doesn't always stack up either. County or city boundaries, rivers and other features can all modify proximity.

Second, you support the team your father supported. Before someone screams 'what about your mother's team? Well, to be honest your father should have already got that covered if he chose his partner wisely. This is always a good option if your parents moved to somewhere bereft of a decent team yet hailed from a footballing mecca. If neither of these solutions appeal, you simply support Manchester United because that's what you do if you've never been anywhere near Manchester.

Regardless of these basic rules, supporting a team is so much more than a geometric solution that a map can provide. It's about territory, local rivalry, physical and social geographies and all sorts of other real world dimensions that cannot be adequately represented by voronoi polygons.

The map has omissions. It fails to show the lower leagues of most countries. It only considers the men's game and for some countries, such as the U.S. the women's game is arguably more popular anyway.

The map allows the classic 'neutral' fan to select a team based on tier. Why would anyone bother with lower leagues? Let's take a look at how this plays out by selecting just the first tier teams in an area I am familiar with.

So in England, being from Nottingham, the map would encourage me to support Leicester City. An odd choice since local rivalry dictates this is impossible. Worse, the map suggests that I would likely be sat alongside someone from Derby. This is utterly absurd. And look more closely...the English Premier League teams are on the same map as the Welsh Football League. They just don't compare.

My team is Nottingham Forest. I was born in Nottingham and raised 2 miles from the ground, on the right side of the River Trent to be a Forest fan. If my parents had decided to live on the other side of the river I'd have been a Notts County fan (shudder!)...or else I might have invoked the second principal and supported Chelsea since my father's lineage gave me that option. My mother's background was irrelevant...Rotherham United - footballing wilderness. I was fortunate when growing up that Forest happened to be one of THE most successful teams of the era (late 70s and early 80s in particular). What a fantastic quirk of location...I'd nailed it by luck alone.

Tragically, they've not been so good recently (by recent, I mean 20+ years and at least once I vaguely considered invoking the Chelsea lineage) and are now in tier two. According to the map below I am at least I'm properly deliniated from that lot from Derby and Leicester with perfect walls erected...though not quite in the right spot based on the geography of the places themselves.

 

Furthermore, most of Lincolnshire remains in Forest territory and this is wrong (unless you're my brother who sadly moved in this direction but at least maintains his footballing heritage). Adding tier 3 attributes the vast expanse of flat nothingness that is Lincolnshire to Peterborough United while Forest's polygon shrinks to make way.

But that doesn't stack up either. Peterborough's average attendance is 5,600 whereas Forest's is about 20,000 so the polygon doesn't really relate to the potential pool of support. Or does it...Nottingham is a much larger city in terms of population size (310,000) that Peterborough (116,000) though much of that expanse around the town is rural and sparsely populated. So, again, voronoi representations really don't adequately represent population distribution, structure or density of the real places from which support for a team is formed.

Finally when we add all teams into the mix and look at England's best supported team again...they are represented by one of the tiniest polygons. Most of Manchester United's fans live outside of this polygon and it's likely many of Manchester City's fans live inside it.

So voronoi's look nice, they are easy to make and when you have a point-based dataset you can compute them to demarcate space. Whether they make any sense whatsoever is down to understanding the input data and the questions you want the resulting map to support. In this case, the geography of football fandom is so much more complex than a voronoi can ever hope to show.

Want a more considered view of football fandom and how it is spatially formed? Check out James Cheshire and Oliver Uberti's Football Tribes map in their superb book The Information Capital. Football Tribes:

It's based on tweets (a dataset I've often been critical of) but heck...at least it demonstrates the complex structure of football fandom and how it is in no way possible to use a voronoi polygon as a way of reflecting on that geography.

Ultimately, data isn't just data. It has context. It often requires a deeper understanding and domain knowledge before you begin to represent or map it. Often, it's incapable of being used on its own to support meaning.

True Size of Africa - now in three dee!

A few years back, designer Kai Krause made his multi-viral 'True Size of Africa' graphic. It's what got me riled enough to start this blog and it was the focus of my first post as I re-drew the map using shapes from an appropriate equal area projection. I got called a 'marauding cartonerd' for making some salient observations and making the corrections.

He got a bit miffed that people were pointing out errors in his work but he remained committed to the cause of simply trying to show that Africa is a big place. His wholly misleading map constantly bubbles up on the internet. The critiques get largely ignored because few care about accuracy and the world keeps turning. Except he's only gone and updated the graphic.

Scientific American published his new graphic in a blog entitled Africa Dwarfs China, Europe and the U.S. in a section called Graphic Science.

Nervously, I went over and took a look...and this is what I saw:

Now let's be clear, the aim of educating people that the Mercator projection distorts our perception of reality and that Africa as a continent has suffered more than most is commendable. Fighting immappancy (as Krause described this lack of understanding of geography) is also close to my heart. But using maps incorrectly is where I get all cartonerdy.

You'd think, perhaps, that Krause might have taken some of the criticism on the chin and used this update as a way to correct his own immappancy. You'd also think that in a publication that profers the importance of 'science' that accuracy might be important. You also may presume that anything in the 'Graphic Science' section would be scientifically accurate in its visual display. Let's see eh?

Like many, Krause has embraced 3D. People love 3D. It looks cool and literally gives maps depth. So this new graphic is attention grabbing because of it's three dee-iness alone.

However - 3D blocks in perspective wrapped round a globe creates visual distortions. In just the same way that on a flat map that uses Mercator the north and south are distorted relative to the equator, on a virtual globe we see distortions in the relative size and shape of features as they move away from the viewing point - the point closest to us as map readers. China therefore appears predominant and his rendering of Western Europe starts to diminish as it begins to wrap around the curve of the globe. So, visually, comparing like for like from a single point of view on a 3D perspective drawing (or globe) isn't a good way of showing comparisons...particularly when it's based on the relative size of areas (I wrote of these issues in a separate blog).

Notwithstanding the visual problems with interpreting the relative size of shapes across a curved surface, if Krause has at least got all his shapes in proportion during the construction of the graphic then we might at least be able to assume some semblance of relative size. BUT...the sizes and shapes didn't quite look right to me so I popped open my GIS package of choice and played with some shapes.

Given I re-drew the original 2D version I thought it only natural to re-draw the 3D version so here's my attempt at re-making his map with the same countries on a virtual globe:

I had difficulties re-making his map like-for-like for the simple reason that the real world shapes are not the same as he presents. Here's where Krause's map seems to fail:

• China is not the same shape and has been warped to fit neatly over Madagascar.
• The contiguous United States is much larger than he presents.
• Krause included Germany and a partial set of Eastern European countries. There simply isn't room.
• The real India is larger than Krause represents.

Of course I'm being cartographically pedantic again but if the very thing you purport to show is misrepresenting reality I don't think artistic license is a sufficiently good excuse. Yes, you could argue it's only a little bit wrong but if you're going to do something, why not do it right? Few who look at the new graphic will even think to question its authority and they will glean a distorted picture. That's the real issue.

The world will likely jump on his graphic and proclaim it as a great way to visualize differences in the size of areas. Like his 2D attempt, it's inaccurate. Will anyone care? I do. Should I have made a 3D version? Probably not. The 2D version is far more useful at supporting visual comparison of areas. Adding perspective and extruding the shapes to volumetric blocks just adds unnecessary visual noise that creates problems for our human processing of the map's message.

ht to @cartocalypse for the link

Drug crazed mapping

I had told myself I wasn't going to bite when @Amazing_maps screamed once more for my attention. But the more I tried to ignore, the more it reeled me in so eventually I thought it worth a few comments.

Here's the so-called amazing map:

I've no idea who made it. It doesn't really matter. What I feel matters is the impact maps like this have on those that view it. This is more about the consumption of maps but, of course, their design and construction goes a long way to underpinning the message people take away.

Quick look and take away: Holy drug barons Batman,...San Bernardino is full of crack-heads! So are a few smaller areas I don't even know....but they're really small so they can't be as important eh? Right, must be time for Alaska State Troopers, turn on the TV...

That's how a lot of people will look at this map. Message delivered. Warped view of reality perpetuated. Job done. Wait for the next Amazing Map.

Here's the longer look and take aways I formulated...

Hmm. Something's not quite right with this map. Let's talk it through. It's a choropleth. We can assume from the title...well, the line that doubles as the legend title, what the subject matter is. It's about the labs, not the population so it's about production, not consumption. And the colour scheme goes from light to dark so we see where there are more meth labs and where there are fewer. I'll not repeat myself like a cracked record about it being totals (but it is) and not normalised (but it isn't) suffice to say it needs to have the data transformed into per capita or something equally sensible to allow us to compare like for like. Though critical for a choropleth, let's ignore that for the purposes of this because there's other 'take aways' in this map.

Look at San Bernardino County again...jeesz, it's heaving with meth labs.

This makes me a little more interested (perhaps concerned) as it's where I live. Notwithstanding it's totals, look at that large, expansive area filled with loads of meth labs. How many?...there's about...errr, well, let me look at the legend. hmm. It's dark blue. Does that make it 300, 500, 1000 meth labs?

It's impossible to tell without doing some assessment of the actual RGB values. It's actually closest to the RGB value about 1/3 along the legend colour ramp which would make it about 330ish...though there are no RGB values in the legend that match those found in San Bernardino County so it's impossible to be certain and why am I having to do an RGB analysis of a legend anyway? It shouts out from the map yet is nearer the lower end of the legend. That doesn't seem right.

So San Bernardino leaps out because 1. it's the largest county in the US 2. It has a lot of meth labs (though possibly not per capita or in relation to counties with many more) and 3. It's dark blue and that means 'more' except there's virtually no differentiation between the blue used at 330 and that for 1000. All the variation in colour value is at the lower end.

The map uses an unclassified choropleth approach. That means every data value is given its own position along the chosen colour ramp. I'm not a huge fan of unclassified choropleths. Choropleths are generally used to show where places are similar and that relies on classifying your data into groups that display similar characteristics. All you can really see from an unclassed choropleth is the extremities...which areas tend to the maximum and which to the minimum. It's really difficult to assess where those in-between values might sit...and that's assuming the scale is linear and the colour scheme is applied linearly. Of course, you can stretch colour to be applied non-linearly but then it's an even more confusing picture that's arguably more difficult interpret visually. If you don't classify data before mapping it then you're painting by numbers and it's a bypass to considering your data and teasing out the message through careful classification and symbolisation.

I'm going to add a caveat here - if the map is for interactive web display and the user can hover or click an area to retrieve the value directly, then unclassed choropleths are, arguably, less problematic because people can retrieve values across the map. I'd still contend, however, that if we know the map is classified into, say 5 classes using natural breaks then every county symbolized in the same shade of blue is 'similar'. It's an important metric we can easily see in the map and it's a good default. Other classification schemes exist to suit alternative purposes. If we use, say, a quantile scheme of 5 classes then we know each class shows 20% of the data values in rank order - again, similarity between values, across the entire range values, can be easily seen and it's simple to see which areas are in the top 20% of values.  If you make two choropleths then using something like a quantile scheme allows you to compare the two maps on a comparable cognitive basis. Clicking to retrieve a value is an additional step in the map reading process. Trying to remember values from one hovered-over area to another is equally taxing because our short term recall is not our best cognitive function (think of memorizing and recalling a pack of cards in order...it's not easy!). I like maps to 'show and tell' rather than require further processing or actions by the user to reveal the message.

Onto the colours. Because there are just so many different shades of blue across the map we get a sense of some overall pattern but we can't really tell which are similar to which. How similar is San Bernardion COunty's colour compared to the other dark blues across the other side of the map? It's called simultaneous contrast and is a problem for our map reading. Our perception of a colour (or shades of a colour) varies as we look across the map due to the colours that surround it. Look at the following two grey squares and how they are affected by the surrounding shades:

The grey square differs in perception depending on whether it's surrounded by dark or light.  A darker surround makes us see it lighter than if it has a lighter surround. Now look at how different colours modify the grey square:

The grey squares, despite being the same, take on a perceived tinge of colour based on what's around it. And when the image gets even more complex we have even more difficulty processing what we see. In the following animation, which grey square, A or B, is darker?

Of course, the greys in A and B are the same. In the above diagrams all the grey squares are seen differently simply because of their surroundings. The map of meth labs has over 3,000 counties, each shade of blue being surrounded by it's own different mix of blues.

These perceptual issues are also a problem in classed choropleths of course - but not nearly to the same degree because it's much easier to distinguish and differentiate 5 or 6 shades of blue across a map than it is to try and make sense of several hundred (thousands?) different shades of blue.

And what about labels? Yes we can probably all recognise it's the U.S. I know where my home is so I recognise San Bernardino County. I've no real way of describing where other patterns exist in language that makes sense. Giving people context is important. Interactive maps support this through basemap labels or, again, hover and click...but however you deliver the map, give people a way to reference the patterns they see.

So the take-aways for me...

• It's totals. If you can't or won't change to a rate or ratio then use something other than choropleth like a dot density, proportional symbol, dasymetric or cartogram.
• If you have to use unclassed choropleths then scale your data across the range of colour so that extremeties don't dictate the way values map onto the colours. Make the legend more useful by providing labels at key positions and make your map interactive so people can retrieve values.
• Go with a classed choropleth if you want people to 'see' more than just the extremeties in your data and how different areas are similar to others for all values that display similar characteristics. Learn which classification techniques are going to manage your data most appropriately for the message you want to share.
• Be aware of the problems of simultaneous contrast.
• Include some form of labelling to give people a way of referencing the geographical patterns they see.

Other problems...no real title, no source, no credits, no dates, no contact details. Nothing. Like I said, I don't know where the map came from but as is, it's a fail in every respect.

Finally, I tried to get the data to recreate this as a per capita but after a quick search I wasn't able to find it at county level. Instead I came across this abomination on the Drug Enforcement Administration web site:

I don't even know where to start with this one, and they've made one per year for the last few years. They were clearly on something or other. And if we assume the DEA reporting is accurate (and the most current) AND that the Amazing_Maps one is broadly of the same time period (OK, a lot of assumptions) then what's with San Bernardino having over 300 meth labs given California as a whole has only 79?

Clearly something's wrong somewhere. Amazing map? Possibly. It's just poorly designed and constructed and gives a totally misleading impression of a dataset that cannot be verified. It's another potentially mildly interesting dataset that's poorly mapped.

And by the way, San Bernardino County is the 5th most populous county in the US so per capita...we may even have a paucity of meth labs so a different map might support the assertion we need more to get our supply increased*. Additionally, while the overall area of the county is about 20,000 sq miles, the populated areas are predominantly crammed into the south west corner in an area roughly 450 sq miles...which makes a choropleth map of totals covering mostly desert even less useful (unless the meth labs are in the desert). And all those less important smaller areas...Seattle, St Louis, Tulsa and Grand Rapids. But because of the way the boundaries lie, choropleths are always going to cause difficulties in interpretation. That's the Modifiable Areal Unit Problem...and a whole different blog entry.

* this is a joke

Messy heat map

My last blog post on heat maps was an attempt to persuade map-makers that the term actually means something other than what you might think it means...and that doing cluster analysis of some form or other on your data more than likely requires a better understanding of data and technique than a so-called heat map generator provides.

My Twitter feed lit up today as Manchester City played Barcelona in the Champions League Round of 16. Lionel Messi, the Barcelona forward, had a fine game by all accounts (to be fair he pretty much always does) and Squawka were on the ball with their live analysis during the game.

Squawka provide a web-based view of sport that collates and presents data as it happens. They tweeted the following:

Needless to say it brought on a nervous carto-twitch. If you read the previous blog you'll know by now that whatever the above is, it's not a 'heat map'. It's a density map of some form of cluster analysis but it illustrates far more than just another example of an inappropriately named map.

Here are some of the issues I see with this map and how similar issues are seen in almost all of these sorts of maps. They may help to understand that it isn't, in fact, a map of Messi leaking all over the pitch.

What is the data that was used?

Messi presumably ran about the pitch yet the splodges look like they are based on point data. Is this where he had the ball? Where he received the ball? Where he passed the ball to another player? Where he was stationary for a period or simply where he stood watching as Suarez scored the goals? Etc etc. While logic suggests that a map of Messi's running should be linear we are immediately confused in trying to decipher what this data actually represents because it looks like points that have been analysed to create a representation of clusters (more points = larger or more intense splodge). Without knowing what data the map represents we cannot decide whether he was all over the final third or not. If the data is indeed points then is that an appropriate metric and can it justifiably be used to show what they purport the map to be showing?

What are the fuzzy splodges?

The typical symbology on these sort of maps tends to go through some form of spectral colour scheme and this is no different. The hazy blue splodges are likely where less clustering occurred but is this a fleeting movement or pass or where he tripped over his laces? As Messi moves more or passes more (or whatever more) the intensity of the symbology increases. But what precisely does this represent? We have no legend to tell us what changes in colour mean and whether colour is mapped onto the clustering values linearly or logarithmically or...

Indeed - if you look at the overlap of two hazy blue splodges near the bottom centre of the map you'll notice that a simple overlap at the edge of two hazy blue splodges results in a bright, intense change in symbol. But if these hazy blue splodges are built from point data (presumably at the centre of the hazy blue splodge) then the overlap is simply an artifact of overlapping symbology...not necessarily overlapping data. These artifact overlaps occur everywhere on the map so it's unclear what the relationship is between data and symbology and how that then translates to Messi's actual movement or involvement.

The statement of being all over the final third also doesn't exactly stack up either. The main splodges are in a zone towards the top of the pitch graphic...a little left of centre but certainly not all in the final third. We'll assume Barcelona are attacking the left half of the pitch graphic and that even though teams switch sides at half-time the graphic maintains teams in the same half for mapping purposes.

All in all it's a graphic that reveals very little except gross error and uncertainty and which is utterly impossible to interpret in a way that reveals anything sensible about Messi's contribution to the game. 

These sort of back of an envelope 'heat maps' are unhelpful for any visual or analytic task. Quick to produce yes, but you can't make any sensible or quantifiable interpretation. Finally, we have no-one elses maps to look at so we simply have to presume that every other player's heat maps are in some way visually inferior to Messi's map.

Messy data. Messy clustering. Messy symbology. Messy map. Messy communication and very messy ability to interpret, compare or understand. Poor old Lionel Messi who is, quite literally, an innocent bystander in all of this...as the map, sort of, shows.

Pretzel crust cartography

I saw an ad on television last night that may help the understanding of how cartographers think about good map design and construction vs what we perceive as poor map design and construction. It was for a new Pretzel Crust pizza available at Little Caesars. It's constructed with a pretzel crust as the base (poor basemap for a pizza in my opinion) and then goes on to slop on a thick yellow cheese sauce instead of a tomato based sauce (odd choice, gloopy and lacking taste), before topping it off with four more cheeses and pepperoni (solid choice for a final topping but a bit out of place on the base).

Take a look and you decide whether any of this should be allowable on a pizza. The pizza appears at about 16 seconds...by 20 seconds I'd hope you won't want one...by 26 seconds I'm hoping you're wondering what the hell they were on when they invented it. If you're thinking yum, gotta go get one now then you may as well not read any more of this post.

Want a pretzel? Have a pretzel. Want cheese dipping sauce with your nachos...go ahead (though forgive me if I don't - plastic orange goo isn't that appealing even in it's correct environs). But designing a pizza using these ingredients just doesn't work for me. If it was experimental then fine...but don't release it and ask people to pay for it. I wonder if I'm alone in this or whether sales prove otherwise?

There are clear parallels to mapping. Start with any old basemap - probably a default topographic one because you don't know what the others are for or, even better, use a satellite image because that's colourful and detailed and more must be better. Then slop some data over the top. Don't pay much attention to symbol choice or design...just dump your data across the top and smear it around. Actually, make it bright because it won't show up on the satellite basemap unless it's bright. Then if you have some point based ingredients (e.g. emoji...see previous post), position these across the top. Finish off with a smear of butter and a good dose of flavour enhancing salt and boom - you made a pretzel crust map.

On emoji cartography

Thinking of putting emoji on a map? Please don't

Whatever you call them: pictograms, pictorial markers and mimetic markers have always been hugely important in cartography. Well designed graphics that are used to represent a point of interest are fundamental to topographic mapping in particular but have become vital for web maps that show points of interest across a basemap. They should be clear, unambiguous and allow us to efficiently communicate the feature with simple graphic clarity. They should work in harmony with the rest of the map and subtlety often leads to a well balanced overall map.

They're not easy to design though. You're often working with a very restricted size, perhaps pixel count and, ordinarily, a single colour. With all those constraints it's often difficult to imbue symbols with the meaning required if the intent is to support a map reader's ability to understand the feature without constant recourse to the map legend. This reason alone is why it's more common to use pre-defined symbols delivered as part of your software or available online. There are perfectly good repositories for symbols (e.g. Symbol Store, Maki) but what about emoji?

Emoji - the Japanese pictographs which have become standard in electronic messaging. They're increasingly used as shorthand for all sorts of communication.

Their increased use doesn't, however, mean they are well suited to being placed on a map. Take a look at this map, made by Katy DeCorah (click to view the live map as part of Katy's blog).

Katy's blog entry explains she was interested in exploring a technical challenge, and she succeeded. But what of the outcome? Once the technical challenge had been achieved we still need to consider whether it's useful in a cartographic sense and in this case I'd suggest it isn't though Katy did at least use a limited set of POIs and did a good job of picking an emoji that vaguely represents the feature being mapped.

In general terms these sort of symbols create disharmony. The emoji are too detailed, too colourful and too 'cartoony'. They inevitably clash with the background map and where they begin to coalesce (as they will in a multi-scale environment) they become impossible to decipher. Their style doesn't suit most cartographic work unless you have a very specific mapping project...perhaps a large scale children's atlas. They simply don't look good on a map. For balance...there are other cartoony symbols that I'd also vehemently discourage in cartographic terms. Such as:

One of the tenets of the cartographic design philosophy that I was taught was to keep things simple. The KISS principle (Keep It Simple Stupid) holds true for 99% of cartographic tasks. The best advice any budding cartographer can heed is to learn how to be comfortable omitting detail in terms of the overall map and also the individual elements. Creating clean, simple lines leads to a much more harmonious map and one that is, crucially, much easier to disantangle and read. Symbol design goes a long way to creating that harmony. Just because a set of symbols is technically capable of being put on a map doesn't mean they should be.

Slopping emoji (or other 3D style, multi-coloured, shaded pictorial symbols) all over your map just doesn't work. Use them in your social messaging where a single emoji is often added as an exclamation or to characterise an emotion. Please don't use them en masse on a map...it hurts the eyes and as Kirsten Dunst might say, it's just a piece of poo (ht Craig Williams).

LyricMap: Where the Streets Have No Name

Inspired by the nonsense mapping of The Proclaimers 500 miles that I re-mapped, I was pondering a few other geographical lyrics and how they might be mapped. I'm going to call them LyricMaps ™ and there's a lot of them. First up -let's give U2's Where the Streets Have No Name a whirl and see what we come up with.

First, start with a nice healthy dataset of all streets in the contiguous USA and use some Geographical Information Systems savvy to process it. I'm fortunate to have access to the 2012 version of the Tom Tom data for North America which contains over 15 million street segments.

Second, apply a few of query analyses to extract any street segment without a name, discounting outliers like connectors, ramps, slip roads and such like. The result: a LyricMap of 3.5 million streets with no name, the beauty of which is that I don't need to worry about labelling because, well...there aren't any!

Finally, map each road segment with a huge dose of transparency so at the final scale the map shows areas that contain relatively few streets with no name as dark as the background. Where there are numerous streets with no name, the overlapping transparent symbols create a much lighter effect.

The map deserved to be styled as an homage to U2's classic 1987 The Joshua Tree which contains the track.

The overall pattern suggests that it's streets in rural areas that have no name. Pretty much all the major cities appear dark indicating a low number of streets with no name. This makes sense...the dataset contains every road in the U.S. and many of them would be dirt tracks. Despite there being over 3 million separate segments on this map there isn't much sense looking at the detail for a particular city...there are so few it makes the map sparse as the following larger scale map of California illustrates.

That said, if you want a giant 36 inch version at 300dpi then you can download one here. It's 12Mb.

Of course, there's more work that could be done to eliminate more categories of roads but hey - this is just a bit of fun. I've got plenty more geographically inspired LyricMaps planned so stay tuned!

Acknowledgments: Tom Tom data used and published under licence using Esri technology.

I would map 500 miles

When The Proclaimers released Sunshine on Leith in 1988 I was just about heading off to University (to study cartography and geography - that bit is important). They were not to my musical taste...why would I want to be beaten up for liking such a dreadful duo? Little did I know that over 25 years later I'd be making a map relating to one of their first and most celebrated ditties I'm gonna be (500 miles). If you want the background read on...if you want to see my map, scroll to the bottom.

The song is renowned for the lyric But I would walk 500 miles. And I would walk 500 more...blah de blah blah.... And so fast forward to 2014 and the following popped up in my twitter stream.

An attempt to answer @DragonXVI's fundamental question - Where the hell were the proclaimers actually walking to? pic.twitter.com/AYXs4IXTli
— Hazel McKendrick (@HazelMcKendrick) May 19, 2014

Now it's clearly tongue in cheek and fair play to Hazel McKendrick...I haven't seen anyone tackle this cultural dilemma before and she had a good go. Where, indeed, were The Proclaimers going to walk 500 miles to from Leith? And what about the 500 more? Unfortunately she used two perfect circles at the nominated distance around Leith but too late, another viral map is born and all the usual suspects begin clamoring to heap praise upon it.

I and a number of map-minded people folded our arms and began finding fault because the circles shouldn't be so, well...circular! Yet again someone had done something wrong on the internet (thanks to Barry Rowlingson for reminding me of the well observed XKCD cartoon).

Great idea. Nice bit of fun but...wait...the Web Mercator projection distorts shapes and areas pretty markedly. If you draw a line indicating 500 miles around Leith on that projection it would not be a circle.

Here's the classic example from The Economist on the threat from North Korean missiles that made the same mistake...

And here's the correction they were forced to publish after they had redrawn the lines properly and with respect to the projection used for the map...

Now it's questionable whether marking the range of North Korean missiles incorrectly is more or less dangerous than the lyrics from The Proclaimers (I guess it's a question of taste) but either way McKendrick's map is wrong. And then what about the fact that reaching Iceland would require them to walk on water? Now we're stretching the bounds of their talent just a little far with that one surely!

So, as a self-respecting cartonerd I re-did the map...

I still used Web Mercator and placed 500 mile and 1000 mile geodesic buffers around Leith (using the same huge assumption as McKendrick) to show the real distances as they appear on this map. These represent the theoretical extent of how far they might walk so if they went off-road and walked in a straight line that's where they would end up (notwithstanding the small matter of the wet stuff).

I also went a little further and used a bit on analytic acumen to calculate how far 500 miles would take them using the European road network. Then I calculated how far they could get by going 500 more. Those areas I show as shaded so we can see how far they would walk on land. I took some liberties...I presumed they only walked on roads and of course, they may know of sneaky short-cuts or go roaming cross-country. I also presumed the ferry journey's equated to a walking distance when they most likely sat down and had a rest (though if they walked round the deck then the eventual distances need reducing slightly)

It's not perfect (there's no North Sea ferries to Scandinavia and the Brittany ferry is also missing) but it's better than shoving circles on a Web Mercator projection and calling it cartography. The correct version applies knowledge of how maps work to make a sensible, correct map...even though the theme is distinctly daft and I still hate the song with a passion. I hate poor cartography more though.

That said, McKendrick's map has nearly 2,000 retweets at the time of writing. Mine? 88. Proof positive that actually nobody gives a shit about quality anymore...or when someone has gone to the effort of providing a correction they do their very best to ignore.

Update: Thank you to all the people who have read this since posted. And a particular thank you to all the other nerds out there who have found fault with my version. I have updated the map to make the necessary corrections and disclaimers.

Update 2: I couldn't resist...I did a Where the Streets Have No Name follow-up map...and I'm now thinking of all the other geo-related maps that can be made. I'm calling them Lyric Maps.

Update 3: Funny how frivolous work gets noticed...I've written an update in a new blog post called Pedantic cartography.

Spreading Light, Wasting Light

This blog entry is about mapping, honestly...but to get to my point I'll start with Dave Grohl and then get to Robert Downey Jr and Steven Feldman...bear with me.

On a recent flight I watched (for the second time) the great documentary on Sound City studios by Dave Grohl. The iconic music recording studio in Los Angeles was one of only a very few in the world to house a custom Neve 8028 24-track recording console designed by Rupert Neve. It was a hand-wired analog device which acted as the interface between the musician and the tape used to record the music but it was the console that gave the end product such a rich, unique sound. Often, musicians would need to play their track over 150 times to get it as they wanted it with all the imperfections ending up on the tape. They not only had to master their trade but be dedicated to giving their best live performance that would become the recorded piece. With only 24 tracks available on the console, the producers also had to be prudent and understand how a complete track was to be constructed to achieve their intended final sound.

The story is ultimately one of decline of Sound City as a viable business (it closed in 2011) despite it being the birthplace of countless classic albums produced in the late twentieth century as digital recording appeared and along with drum machines and other digital instruments, allowed people to record direct to a computer. The benefit's of digital recording are clear - the entry level for people making and recording music are massively decreased; the costs are much lower to make a recording; and anyone with a computer can record music. By using a program like Pro Tools you can play a track once then work on your computer to change duff notes, alter the pitch, add a range of effects (curiously with an image of an effects pedal you'll never likely have even seen in real life) and record as many tracks as you care. In short, it's making music for dummies and we've seen a proliferation of music appear as a result, all of it seeking perfection through a processed approach. You actually don't even need to be a musician to make an album these days. No craft, no art, no expertise as such...just working with digital data that equates to music when processed in a particular way.

However, as one contributor put it eloquently, there's nothing of the musician in much modern digitally produced music. A huge amount is over-produced with multiple layers of noise. What made music recorded through the Neve board at Sound City so immersive was the imperfections; the fact that you're listening to a real person play a real instrument with all minor imperfections in their playing exposed. It gave the music a 'feel' and a human quality that is difficult to express but which can be easily heard. It's an audible aesthetic and one that cannot be replicated in the same way using modern technology. The same commentator went on to say that yes, music recording has opened up like never before but he challenged us to consider whether it meant there was any better music out there. His thesis was simple..that all that has happened is more people with a lower level of ability or understanding of music (playing, recording, producing) now make music - but that there's a much higher proportion of poor music as a result. It's harder to find the quality any more because quantity sells.

Back to cartography - but as anyone who has read my blog before will realise, the above tale is pretty much verbatim my views on a lot of modern mapping. The death of expertise and massively reduced barriers to making maps has given us quantity but has seriously diluted the quality. People are becoming blinded to high quality mapping because they're consistently told to go look at this or that 'great' map by people who probably couldn't tell the difference anyway.

So my latest gripe is with the plethora of animated maps of social media data that are using CartoDB's torque engine. I like what CartoDB are doing and their torque engine is a very simple way to animate time-dependent data. But what of the result - how is it being used? Take a look at the following map of how Robert Downey Jr's twitter account gained followers in the first 24hrs after his first tweet:

And the man himself even commented on the map:

Just spreading light. RT @TwitterData This map shows what happened to @RobertDowneyJr followers after his first Tweet http://t.co/EhmewFyAdf
— Robert Downey Jr (@RobertDowneyJr) May 13, 2014

So what does the map show? I think Downey Jr was spot on...it just shows him spreading light. Actually, it doesn't really show anything at all, except for twitter's absence in China. So a huge global movie star gains followers in places where people live. Are we amazed? And I'll not even bother to go into the pitfalls of the problems of mapping and inferring anything from Twitter data (because I've done that before).

Here's another of the tweets that were posted around the recent F.A. Cup Final between Arsenal and Hull City: Again...it's just flashing light. What purpose does it actually serve? Visually, I like the effect but it really only shows us that people tweet. And therefore tweets reflect where people are on the planet. And Arsenal are much more popular than Hull City. And perhaps my good friend Steven Feldman is the one responsible for lighting up the UK as a twitter loving Arsenal fan?

There's just nothing particularly substantive about making maps like this. Once you've seen one you've seen them all. The digital tools make making the map very simple but it doesn't mean we're seeing good maps. It's quite literally a data dump on a map. There's no sorting, sifting, no trying to extract an interesting story or communicate a highlight (no pun intended though this would be a useful thing to do!). Light is cumulative and brighter = more but why are we so fascinated by 'more' of everything?

When I look at the map I see flashing light but after a short while I lose sight of the light area (most tweeting in relative terms..and really, the only metric this map is capable of displaying) because the almost strobe effect of the single tweets in the sparse areas becomes more prominent. Is this really the right message? And when the map is saturated with tweets what are we seeing? Anything?

I find the story of Sound City and its demise in the face of the onslaught from digital music has many parallels with my area of expertise. Whilst there's no doubt making maps these days is massively improved on many of the older techniques it doesn't necessarily equate to there being better maps. Like Grohl, who is a master of his craft (whether you like his music or not), many musical experts can still find ways to make their music and embrace digital technologies as part of their workflow. Trent Reznor is also a perfect example of this. A musician who knows his craft but is hugely experimental and who can weave modern technology into his work expertly.

I'm not decrying technological innovation and progress - just lamenting the decline of the thought that people used to have to put into making a map. If it was worth making it'd take time...and so that cost alone was a good way to decide if making the map was worth the investment. These sorts of maps can be made in minutes but without any sort of cartographic craft you end up making maps of flashing lights that tell us nothing or, as the title of Grohl's last Foo Fighters record stated...you're simply "Wasting Light'.

Update 1: there was an interesting side debate on this topic where some were suggesting that frivolous maps are nice once in a while. I agree. Firstly that this sort of animated map of social media data is content frivolous but also cartographically frivolous. It's experimental and at the moment we're in a period of cartographic change where for the first time in a long time technology is outpacing best practice. Experimentation is good and we need to figure out ways to harness these new approaches and to develop new best practices. This is a challenge and one that cartographers need to embrace. Unless they do, all we'll see is more of this type of mapping and more people telling more people how great it is.

Another day. Another hyperbolic map

Hyperbolic - of or relating to hyperbola, an adjective describing something that is overstated or exaggerated. And so to today's hyperbolic map.

The work is called Isoscope and is by students at Postdam University under the guidance of Till Nagel. The write-up is in The Atlantic by John Metcalfe entitled 'A striking new way to visualize mobility'. Well...'new' and 'striking'...what a fine way to start a Monday morning. I checked out the article hoping to be cartographically amazed. Only, once again I found myself exhaling a deep sigh. Metcalfe describes Isoscope as a 'beauteous, immersive experience'. He also litters his piece with other glowingly positive terms. It's also Infographic of the day over at FastCo Design. Good grief. Is this hype just the reporting?...

I went to the project web site itself to be told Isoscope is an approach to capture the rhythm and pulse of the city; to find the boundaries of reachability, organically. It reveals traffic infrastructure, connectivity and natural boundaries. It's all about mobility and urban morphology apparently. but wait...mobility is way more than how far you can drive in a given time. It's more than cars...it's public transport, it's bicycles, it's the provision of safe bicycle lanes, it's pavements for walking on, it's a reduction in barriers (physical or socio-economic), it's about levels of fitness, disability etc...

Now let's be clear here...this is a student project. It's fine. It's teaching people how to use APIs and to make online maps. It's a fairly neat effort but...leave it at that. But no...not only does the project web-site over-inflate the work but then it gets regurgitated by a news media site hunting for any copy it can find to 'amaze' its readers for the few seconds they pass by.

Why we have to read about it being the next most amazing thing we've ever seen baffles me. It's not new to people like me. In fact, it's not new to anyone because this sort of work has existed for decades. Now if you are unfamiliar with it, that's a different matter but just because you weren't aware of this type of map does not, in absolute terms make it new. If it's the first time you've seen this sort of map do you not wonder if anything like it has been done before? How do you know what you're seeing isn't a rip-off, or poorly executed? Do you not approach such work with a hint of skepticism or at least a semi-critical mind? If not then you're lost my friend, you will read every new piece of hyperbolic cartography placed before you and neither care of its quality or efficacy. Like anyone, I love to be amazed and to see new and interesting work in my field of expertise. It's what pushes us forward and keeps things interesting. But too much of what gets passed around at the moment is neither new or amazing.

In terms of this map, you probably won't care that it's just an isochrone map...a 'service area' that can be calculated from a given point to all other points that fall within a search distance based on some criteria - in this case drive times as specified in a database. The term isochrone was coined by Francis Galton in 1873 "[I] propose to employ the word isochrone (equality of time) in a special sense..." (hat-tip to Joshua Stevens for reminding me of this). In fact, the use of isolines (lines of equal value) in map-making can be traced back to the 18th century. The Halley isogonic map (below, of magnetic declination) is possibly the first use of contoured curves of equal value. It was published in 1701.

That's over 200 years of prior art...and we've been making isoline maps and isochronic maps ever since. Don't believe me? Check out Google Images using the search term 'isochrone map'.

So back to the Isoscope application. It's simply a way to show isochrones for certain temporal distances around a point the user adds to the map. It calculates drive times based on a model of traffic condition at different times of the day in relation to the maximum speed limit of the road segments. So it's really a time-slice isochrone map capable of showing us different views at different times. You can also add a 'pedestrian' isochrone to show how far you can walk in a given time. Except it's not very accurate.

Here's a 10 minute drive time isochrone around where I used to live in London at peak morning rush hour.

It's wrong. It's hideously wrong. I added the red squares highlighting a few key junctions where you may be backed up for 20 minutes or longer. These critical junctions in the network would dramatically reshape the isochrones. I know because I needed to get to the University from my house - so much so that I switched to a bicycle and also walked. It took 12 minutes on a bike and about 25 minutes to walk. So let's zoom in and check out the 10 minute pedestrian isochrone.

I added the red dashed line - it's a distance of about 1200 feet (360m). That segment of the journey used to take me about 4 minutes. And what happened in the area I marked with a red square? There is no barrier, no impediment to walking to there in about 1 minute from my house. It's just an irrelevant blue blob that does not in any way represent where you can reach within a 10 min walk from my house. However nice you think the map is...it just lied.

So the map is, as with a lot of maps, only as good as the data you pour in. Maps made by people in one city, yet creating a map for the whole world because the data exists...except the data is really not very good at doing the one job it's supposed to be doing and no-one bothers to do any ground-truthing or checking. Why? Because we're more interested in creating a beauteous, immersive, new and striking map than being overly concerned about the content (that and it's not really feasible when you're trying to map the world). But wouldn't you check areas you know well? Does the data actually do what it says or not? perhaps some estimation of error might be stated so we can proceed in our own interpretation with caution?

In terms of design, the use of a dark basemap and bright, single colour polygon overlays, with a nice dose of transparency isn't particularly striking either. We've seen a lot of maps styled that way recently.  Don't get me wrong...I like the look (and have made maps with a similar aesthetic myself)...but it's not new or striking. As for the typography? It's a little clumsy.

So, I wonder about all the things I am unfamiliar with that may also be new, or not as the case may be. Open your eyes people...go beyond the rhetoric, the marketing, the tediously simple journalism and learn a little of what you're consuming. A very good student project yes, but not a new or striking map.

I wonder what hyperbolic map will drop across my desk tomorrow?

Fanscape map excitement

I was sent a link to the following map by Rob Story. I can't bring myself to thank him...it made my eyes bleed and I genuinely do not know where to begin in dissecting it. It goes straight to the top of 2014's worst map so far list...and that's something given we only recently saw the NBC Nightly News abomination. It's from Newsweek's Tumblr though tracing the true origin and figuring out who made it is probably a good thing.

What does it show? Who knows.
What do the colours mean? Impossible to tell, even on a well calibrated screen.
What exactly is being mapped? No idea. I don't even know what sport (probably a Brit ex-pat issue)
What data is being used? Nope...dunno. 61% of what? What 'fan votes'?
Why map two variables with virtually the same colour? Why? WHY?
Why use an unclassed choropleth? Sorry, I give in.
Why does 'more' seem to be shown in lighter colours in the two things but the inverse is true? Bad.
What is the actual point? Possibly to show how bad a bad map can be?
Is it a joke? I sincerely hope so.

It is that far from the normal cartofail scale it defines its own scale!

Congratulations whoever you are...my opthamologist will be in touch.

Update: Thanks to Martin Elmer for pointing out an inaccuracy in the original post. He also points out it could well be a screen grab of an interactive map. Possibly yes...though most of the problems still apply.

Changing Face of America. Bravo!

No one wants to see bad maps...or maybe they do, because they keep those that can make good maps in business and they give educators some great material. Without cartocrap, what would we have to keep us entertained? How would we be able to discern good from bad? What would I have to write about? OK - that's maybe a question too far.

So today social media was lit up like almost never before at the sheer horror of the following effort from NBC Nightly News. Go on, drink it up, then rub your eyes and take another look.

What were they thinking? It's an area graph...showing three different time periods but they've gone and clipped the rectangular graph using the shape of the US to create what I am sure they thought of as an uber-information graphic.

Clipping to a shape destroys the visual impression of relative areas across the chart since we have no baseline or simple geometry to anchor our understanding of the pattern. Without reapportioning the areas of the graph to the new shape it leaves some of the categories completely dissected and reduced in area relative to the rest. That's those at the top if you were wondering.

We can't even make any sensible vertical interpretations because that wretched coastline gets in the way. But worse...has the space-time continuum gone awry? Do we progressively travel back in time if we go east to west? Argh...but the east coast is in the future and the present is roughly down the Mississippi. Great Scott!!!! Perhaps Emmet Brown threw the original graph in a flux capacitor and this is what was churned out the other end. Or given the rainbow colours, maybe Marty McFly threw in some ideas?

Back to what the graph shows...OK, it's on a map, so it's a fair assumption that we're seeing a spatial relationship because it's on a map...so all the white population live below a very specific curvy line - they get a lot of the west coast and southern states but poor souls are banished from the north east.  There's a few thin strips across the rest of the northern latitudes for asian, hispanic and black populations but seriously, I was under the impression that segregation ended decades ago. There's a small promontory for 'other' (whoever they are)? and it looks like Alaska and the Hawaiian islands have undergone some sort of ethnic cleansing. Hilariously, if Alaska and Hawaii had been positioned elsewhere they may have had a completely different ethnic composition.

Overlay this detailed map with a weather map and we could probably infer that 90% of the white population will experience a sunny day and the rest won't (thanks to Craig Williams for that observation). But not in Colorado... the 100% white population will likely find it colder on the front range in 2010. Another way to look at this map is that California, Oregon and Washington only existed in the 1960s and have been progressively been replaced over time with the eastern states. I guess for some that might be closer to reality than the map intended to suggest.

Really, it's almost impossible to stop finding fault - it's a piece of cartojunk of the very, very highest order and will be used for years to come as one of the most purile, ill-conceived pieces of cartographic arse-gravy that anyone ever invented. Bravo!

Only Maps and Horses

I increasingly hear quite a lot of the latest buzz about this map and that map but where is this noise coming from?

We're seeing the maps we're seeing because of one thing...ubiquity and ease of construction has created an appetite for them. Where there is a demand, someone is always going to meet the demand. The demand at the moment however is for quantity, not quality and there are plenty of middle men anxious to provide a mechanism to push their wares. These are the Del 'Boy' Trotter of the cartographic world. Buy cheap, Buy quantity, Sell at a markup and without a care for the consumer or the quality of the product you're shifting. Think yellow peril...

Take, for example, 'Amazing Maps'. Their Facebook and Twitter pages have tens of thousands of followers and so on...the site exists simply to push maps that are found on the internet to their followers. I'm one of them but for every one that piques my interest and which I find genuinely intriguing, well made and purposeful, there are dozens more that fail on a very basic cartographic level.  Often the maps display disturbing mistakes.  I see them. So do other experts. But most do not...they are busy being experts in their own field and simply see the map, consume it and move on.  Take today for example...here's a map of the Winter Olympics medal count they pushed:

Anyone who knows anything about mapping will immediately spot two glaring issues...the data are not normalised and the colour scheme is truly unhelpful in allowing readers to rapidly see the patterns. Here's a version I made...it's not particularly attention-grabbing but it's constructed with basic principles in mind so we are better able to see the patterns.

Not only are the patterns modified when you normalize so they can be properly compared against one another against a constant baseline measure but light to dark means less to more. I'm afraid spectral colours aren't read like that by humans - we see 'difference', not 'quantity' so although in the first example I can tell Australia has a different count to China and Norway...I don't know in which order. Purple 'looks' more than light blue (because it's darker) but if you look at the legend China has more medals. But once normalized, actually they have no more per capita than Australia meaning that they are pretty much equally successful. Sure, China gets more medals overall but then have a massive population by comparison so you'd expect more medals. We normalize to allow us to visually compare like for like. And are the USA really as good as the top map suggests being in the next to top class? No...given their population, actually their winter medal haul is relatively poor and on a par with the UK per capita.

So, back to the point...is the daily consumption of bad maps bad for you? I would say yes because you're getting the wrong message. It's a waste of map calories.  I'm all for quick and dirty maps made well...but not ones that are constructed shambolically and peddled to us by people who know no difference.

I mentioned this myself on Twitter a while ago and someone said to me that while they agree, they like fine restaurants but also dive into Subway on occasion.  I've used the food analogy before but I think it needs to be more subtle here. Sure...go to a Heston Blumenthal restaurant and enjoy fine dining. Go to Subway and enjoy a sandwich too.  Both different 'qualities' of food in all likelihood. However...would you want to go into Subway and order a meatball sub that comes with the meatball on the outside, trying desperately to envelop some bread? At least Subway construct their sandwiches according to the basic rules.  Bread on the outside, filling in the middle so it works on a basic level as a sandwich even though it might taste like crap (taste, of course, is a different argument altogether).

That, for me, is the problem with a lot of maps...they suffer from basic constructional issues that really affects their performance as maps. Yet the appetite is there because the 124,000 Twitter followers that @Amazingmaps has dwarfs the combined Twitter following of at least 50 of my map expert friends combined by some margin. Tabloid newspapers have higher circulations than quality broadsheets. The reporting is dubious. Same with maps...it's just that maps have in the last 10 years suddenly entered this realm of ubiquity so now we have professional cartographers along with good map-makers and not-so-good map makers and who cares who makes the map, how it's made or if it's any good because it all sells.

No-one seems particularly bothered who made the map and what their cartographic qualifications are when they peddle maps they find on the internet yet I would strongly argue that being authoritative in your domain is crucial in distinguishing quality work from the masses. It's therefore not the fault of the makers of map-making tools or the map-makers themselves that we see so many poor maps. Just like any service based on mass consumption, if the demand is there, there will be someone keen to feed it regardless of the quality. The demand is for maps, good, bad, big, small, whatever. There are plenty of people and organisations that have set themselves up in the last few years to satiate the demand purely to serve their own agenda of being purveyors of content. How many of these have any real cartographic credibility? Take a look...you won't find many publicly visible examples that have a strong cartographic background. Such sites are not curated by people who know anything about maps. That much is obvious.

Over at the International Cartographic Association blog we're trying to arrest this by providing a quality broadsheet version of Amazing Maps, set up as an antidote to tabloid cartography. I'd love you to go take a look and share the links if you care. We're running a daily series called 'MapCarte' where we're showcasing a curated map that evidences high quality classic and contemporary cartography. Beautiful maps, made well and described to explain something of why the map is regarded highly.

Maybe the Twitter handle @AmazinglyBadMaps was taken? In truth what they're peddling is potentially interesting data mapped poorly. It's like Del Boy's paint...perfectly decent paint but painting a Chinese restaurant in British Rail luminous yellow just doesn't work. If you prefer eating at a decent restaurant rather than Del Boy's painted Golden Lotus then head over to MapCarte and gorge yourself.