Thursday, December 26, 2013

2013 Recap

A quick scan of my 2013 projects here shows three distinct types of posts.  The most interesting and fun is the hey I just made this thing sort of post.  Followed by the try this out posts.  And lastly the more day to day housekeeping of this and that posts.

Thanks for the fun conversations, project ideas, and support all year long.  2013 was both difficult and thrilling and certainly packed with lessons which I didn't necessarily want (but those turn out to be the truest sort).  Here's a 2013 rundown of this blog:

Projects

Drunk Driving in American Cities
A follow-up to late 2012's traffic fatality series, folks morbidly(?) wondered how their city's drunk driving stats stacked up in a more ranked sense.  Well you got it!  This is a sort-of bump chart of the biggest US cities, with some interesting city signatures, for sure.

Seattle People Dots
A pile of dot maps illustrating Seattle area commuters.  You know, that dot-mapping thing where each person is a tiny speck tumbling about in a sea of other tiny specks.  Hang on, Dostoyevsky just called, I have to take this.

Biking & Walking to Work
More commute dots.  This time they show the "top" bike-friendly cities and differentiate between biking & walking vs everything else.  I drive to work, but if I lived close enough, I like to think that I'd bike there in the two months a year that it is feasible.

Map Math
The process of making data maps is way more fun than looking at them.  Here's a behind-the scenes look at some raw data sets and how they get crammed together into ratios (and ratios of ratios).  It's so meta.  I earned a fair bit of scorn for my garish color ramp.  I defended it at the time, but the benefit of hindsight has won me over to the side of my critics.

Sandy and the Buildings of NYC
The age old story of floods and buildings.  Buildings and floods.  This was a take at seeing one data set (actual and predicted flood zones) cookie cut by another (building footprints).

Color Theory Through the Google-ifier
Orange makes you hungry.  Yellow bedrooms are associated with schizophrenia.  I hear stuff like that a lot.  So I asked Google Image search what different terms looked like and sampled them down to their average color.

Tornado Travel Map
Big shocker, tornadoes tend to move to the northeast.  But here is a picture that takes a step at illustrating just how overwhelming that overall trend is.  This was my first chart is star, maps are second fiddle layout and I like it.

Language and Color
A lot like that color-theory-googlifier thing above, but this time I wanted to see how connections of colors with ideas vary across different cultures.  Listen up, grad students, there is a solid thesis in there (for anyone better at math and psychology and anthropology than me -which is everybody).

A Breathing Earth
This wamma-jamma turned out to be three times more popular than all other posts this year, combined.  I got all dopy and sentimental about it, but so did other folks, too, so shut up just shuuut up!  I am NOT crying, YOU'RE crying!

Football Game-Day Traffic Fatalities
In addition to fearing I'd be sued for libel, of all the projects this year this one stole the most sleep because of my struggle to describe it.  Pro tip: any time you have to paraphrase statements of statistical significance in a map, maaaaybe it's time to re-think things.

The Dispersion of Life and Gender
2013 had me asking all sorts of questions to myself.  This map series was a natural result of paying extra attention to the arc of birth, ambition, love, and death.  Hey, P.S. we found out recently we're having a baby due in June and I'm really excited to meet him/her.

United Nations of Bitcoin
Sort of a map of the international adoption of Bitcoins, but really just a map of operating system popularity by country.  If I had this to do again, it would be much different.  It's pretty lame, actually -but I am pleased with the aesthetic.

How-To

Severe Satellite Basemaps
I have a love-hate with satellite imagery used as basemaps (mostly love, but local news uses it so poorly).  But, when I do use them I like to crank up the drama to eleven using a couple tricks.  Plus I've gotten pretty good at rationalizing why this is the way to go.

Mercator Globe Hack
Nine pennies, some yarn, and a globe my wife got me at Salvation Army are the props employed to illustrate Mercator's warping of size and direction.

Hex Mapping
Necessity of the mother of invention.  When you don't have a tool that does what you need, maybe try a bunch of tools and sneaky uses of them.  The things I go through for my lack of programming capabilities.

Dasymetric Dot Density and the Uncanny Valley
Frankenstein's monster of a blog post.  Lots going on in this one, including my tendency to associate everything with the uncanny valley.  The takeaway: if you have any use for country shapes clipped down to populated areas, then have at this shapefile.

Unrequested Map Tips parts One and Two
Whenever I find myself writing advice, I ratchet up the self-deprecation to counteract sounding like a know-it-all crank.  But in the end I probably just sound like a self-deprecated know-it-all crank.  Wait, I just did it again!  Anyway, there are some good bits in there for cartographers, or those who enjoy reading about the human condition by way of cartographic techniques.

Silly Geographic Precision
Sure, it's a pull-through of sloppy database configuration, but exceedingly long coordinates are misleading and bloaty.  Best to match precision with their recording accuracy.  The gist: six decimal places is all you need -the rest ranges from dumb to pure evil.

Paper Globe Template
The one where I copy my wife's Pinterest-inspired Christmas ornament project and try to make a globe-like thing out of it.  Resulting globe-things are for decorative purposes only and I will not be held responsible for gross navigational errors, or the grievous loss of comfort and property, experienced as a result of their misuse.

Updates

Freaky Friday
Every now and again we have a hack day.  These were the projects.  The fat flow of idea to demonstration, and the clever and creative folks I get to work with here are two of my very favorite aspects of IDV.

Tribute to a Geographer
I wrote this way too soon after losing my Mom, but I was proud of her and writing to you about it seemed appropriate.  What's the point in writing anything if it's without sincerity?  Grief is weird, and I learned that I tend to do it privately -except for when I write, which helped give shape to the pain.  Many thanks to those who reached out with their comfort.

Welcome
This summer Josh Stevens joined us as Visiting Cartographer.  He was a valuable collaborator on several spatial projects and was a lot of fun to have around.  Unfortunately, a lot of product work sprung up at that time so I didn't get to spend as much time with him as I'd have liked.  Brilliant guy.

Best American Infographics
It's a treat to be on a scouting team with such talented folks and a thrill to see the tornado tracks map conjured in print.  The other day I was in the bookstore and I showed the book to my littles.  It was a proud moment for a dad, showing off a little to the only ones it matters showing off to.

Adventures in Mapping
The slide-share of a lecture to a class of informatics students at UC Davis.  I have found that I never really understand something so well as when I have to explain it to somebody else.  Teaching is reciprocal.

Amazing Maps from 1880
Whenever I need a real kick in the gut, I browse historical data mapping archives to realize that it's all been done before -collected via horseback, aggregated by hand, etched on copper plates, and bound individually in leather.  And here I am whining that I have to define hex values for color gradients.

Anyway, be thankful for your 2013 and do well in 2014.  All the best,
John

Monday, December 16, 2013

3D Paper Globe Template

Merry Christmas from IDV Solutions!  Behold the fun that is a NASA satellite imagery Christmas ornament!

While your future holds a fair bit of cutting and stapling, I assure you the lion's share of the hassle of this project lay in the creation of the globe template, trying to figure out good-enough coordinates for each of the 20 panels, and getting those pesky registration letters right.  So, I hope you can overlook my less-than-perfect seams, and don't use this globe for navigation purposes.


Grab the template and get your home-made 3-D NASA imagery globe ornament on!
Dominate your map nerd Christmas decorating with this crazy December satellite imagery sphere!



Also, if you have kids, make them do it.  That way, you'll feel the smug satisfaction that they are "learning" something and you can keep your 24-year streak of not having used scissors alive.
Maker Mama, in addition to having a cool blog handle, gives a way more useful set of instructions, here.  She uses a glue gun and an insanely specific circle-cutting tool, but I was lazy and used a stapler and some scissors.  Good enough!  The gist: cut out all 20 circles, fold their three edges up, then join them based on the little letters I meticulously provided.  Magic!

FYI, the imagery comes from the fine folks at NASA's Visible Earth, who provide could-free (not sure how they did that for Michigan) global satellite imagery for each month of the year.

To download the PDF template and get the global assemblage going, click here or on the image below.  Print that template, and make what might be your first globe ever.  You can do it!!


P.S. If you accept the challenge, and rock your tree with this ornament.  I'd be excited to see snapshots of the festive results on Twitter.  So keep me posted, nerds!

 

Thursday, November 21, 2013

Amazing 1880 Statistical Atlas and some clunky GIFs

I stumbled on this 1883 atlas and my jaw dropped.  Scribner's Statistical Atlas of the United States.  I've never before seen such a mastery of graphical information design packed into one book...and it was produced 130 years ago.  The data comes from the 1880 census and is a real pleasure to behold.  Here's the full title:
Scribner's statistical atlas of the United States showing by graphic methods their present condition and their political, social and industrial development. By Fletcher W. Hewes and Henry Gannett, Chief Geographer of the United States Geological Survey. Formerly Geographer of the tenth census of the United States.

Go ahead and lose a day over at David Rumsey's site, where he provides scanned versions of every page of this and other books.

This cover, that I wish I could touch.

Stuffed with pages like this, that I wish I could smell.

Anyway, since so many of the pages showed categorical information in sequence, I couldn't resist slapping them into some clunky animated GIFs.

Different ways of dying, and what those proportions look like across the states.  FYI, "apoplexy" is the old name for stroke. Washington state?  Deadly with pneumonia!  Utah is the place for abdominal distress.  Half of New Mexico deaths were attributed to heart conditions.  The Consumption?  Pretty much everywhere.  Everybody dies.  And while that inevitability is fresh in my mind, seeing a picture of the spatially varying causes tells me that there is more than environmental determinism at work, but evidence that leads to better care and precaution.


The particular geographies of economics.  Not far removed from emancipation, the South, former slave-holding domain of cotton plantations, was still the overwhelming agricultural zone of the nation.  The fertile plains of the Midwest had yet to be fully tilled under into the corn belt and bread basket of a hemisphere.  As the railroads expanded west, zipping crops and livestock east became more logistically feasible.


In the late 1800s the United States were a magnet for Europeans looking for opportunity and room to spread their legs.  Shortly after this map was made, my Norwegian ancestors landed in, not surprisingly, Chicago.  More than 20% of Ireland's population left their homeland in the preceding decades, many of them to the young United States, particularly Massachusetts, fleeing famine when the mono-culture of the potato collapsed, among other things.

Anyway, it is works like this that make me feel a combination of exhilaration and and anxiety.  On one hand, it is an inspiring example of thoughtful and artistic work by a team that is not just at the top of their craft, but wielding an expertise that makes cartographers 130 years into the future envious.  On the other hand, I am taken aback at the herculean feat of data wrangling at a time when these locations were distant and dangerous and remote by weeks.  I don't hold a strong confidence that I would be able to replicate their work in its own right even with the massive technological and communications advantages that I enjoy. But, of course, it's not about the tools but rather the care taken in communicating a story. Ironically, I look at visual performances like this and suspect that it is in part precisely because our ability now to churn out products so quickly and effortlessly that the results often do not compare to those that required an inordinately greater investment and therefore commanded a sense of magnitude in the proceeding that has few analogs today.  But I recognize the debate between quantity and quality is largely a false one, as there are data artists today who are no less thoughtful in their approach.  And while the overall volume of visual work has exploded, I see this as evidence of a broad pool of new and interested participants who have every opportunity to improve and thrive.
Though as for this, I say well done, Fletcher, Hewes, Gannett, and team.  You are still wowing, generations out.

Monday, November 18, 2013

Silly Geographic Precision

I tread water in oceans of latitude longitude coordinates.  Every vector data set I encounter is big fat sets of latitude (up-downiness) and longitude (left-rightiness) bits of info which combine (the "co" in coordinates) to pinpoint a spot on the surface of the Earth (and those combine to trace lines or areas).  The more precise the coordinate's numbers, the finer the pinpointing.  But sometimes I see data (usually the results of address geocoding) with a ridiculous number of digits past the decimal place, implying waaaaay too specific a location.  For example, today I saw the sample below as the result of an address geocode.  I'll use a large courier font to connote just how epic this is...

47.640120461583138
-122.12971039116383

That's a tight geocoding.  Not only does the level of precision pinpoint a building, it pinpoints a specific atom in the building.

Here's a breakout of coordinate precision by the actual cartographic scale they purport:

Decimal Places
 Actual Distance
Say What?
6 10 centimeters Your footprint, if you were standing on the toes of one foot.
7 1.0 centimeter A watermelon seed.
8 1.0 millimeter The width of paperclip wire.
9 0.1 millimeter The width of a strand of hair.
10 10 microns A speck of pollen.
11 1.0 micron A piece of cigarette smoke.
12 0.1 micron You're doing virus-level mapping at this point.
13 10 nanometers Does it matter how big this is?
14 1.0 nanometer Your fingernail grows about this far in one second.
15 0.1 nanometer An atom. An atom! What are you mapping?

As a reference, six decimal places of precision is generally plenty-good-enough territory for cartography.  Unless you are collecting the cornerstone base survey coordinate for a mechanical engineer, let's call this good.

Not all Longitudes are the Same
A degree of Latitude is about 68.71 miles, and that's pretty* consistent as you go north or south (when you climb up or down the ladder of latitude, each rung is the same distance).  A degree of Longitude is widest at the equator (about 69.17 miles) but gets narrower and narrower until they all pinch together right down to nothing at the the poles.  The examples above are pretty much best case examples when it comes to Longitude; they get even sillier when you move away from the equator.

A Fine Mesh
Latitude and Longitude lines are the tics of an imaginary mesh that covers the world -like pixels on a screen.  Every time you add a number to the right of each decimal in a Lat Long coordinate, you subdivide the mesh of the Earth by ten each way (bumping your resolution 100 times finer each step).  Things get crazy in a hurry and it's common to encounter data with not just meaningless, but deceivingly precise coordinates.  Just because something is precise, that doesn't mean it's accurate.

P.S. I read a really good book by Dava Sobel a while back on the surprisingly epic history of Longitude.  It's called Longitude.  If you are nerdy enough to have read down this far then it's a safe bet you'll enjoy it.


Monday, November 4, 2013

20 Unrequested Map Tips part 2

...continued from 20 Unrequested Map Tips part 1

Unfortunately, my niece Kadence's definition of maps is, frequently, correct.  Here are some tips to avoid landing squarely within this sentiment.

Alright, you didn't ask for it, and here they are!  The final ten unrequested map tips.  As with the previous ten, I'll use examples from my stuff because it's easy to ask my permission (and slightly less because of rampant megalomania).  Also, to attach credibility, please read the following with the inner-monologue voice of  Morgan Freeman...

#11: Thinking choropleth for count data? Maybe try dot density. It self-normalizes for area, is emotionally resonant, and looks cooler.
They are speckly little wonders.  They dispense with the whole normalize-by-area problem, sure, but they also detour you right past that abstract business of data range classification and tying those ranges to a color key (and the good old legend, map, legend, map workflow as working memory constantly vaporizes).
A single dot representing a single thing is a big fat affordance of interpretation and a smooth on-ramp to an natural cognitive association of your data with volume and dispersion.  Plus it's easier to personalize, encouraging emotional uptake.
Sure, while dot density randomly disperses dots inside the polygons, if the polygons are small and numerous enough then the bummer of randomness is marginalized.  Also, there are dark tricks for constraining your dots into more realistic areas (no dots in vacant places).
Dot density isn't always the right way to go, but if you want to illustrate general dispersion and volume (especially if you have a couple of categories to highlight) it's worth a go.  Some inspiring characters in this space are Kirk Goldsberry, Andy Woodruff, and Brandon Martin-Anderson.

Can I actually count up all the commuters?  No, but who cares.  I get a good sense of the dispersion of commuters though, plus, bonus, what method they use to commute.  Alternatively, this would have required four separate choropleth rate maps to get the same point across, and even then I'd have huge low-population areas gobbling up most of my visual plain.  From People Dots: Seattle Area Commuting.

When mapping individual human counts, nothing resonates emotionally quite like a one-to-one dot density approach.  From Gender Flow in NY.  Those are people, man!

#12: Be intentional about aesthetics. Good design buys a second, closer, look.
This one's harder to write about because it's more subjective (plus any attempt to elaborate makes me feel like a pretentious know-it-all).  But there are definitely good lookin maps and ugly maps.  And all things being equal, the good lookin map is going to visit a much broader audience.  Maps are portraits of a phenomenon so other humans will look at it and appreciate the message.  That's it.
In my experience, the first time that became obvious to me was with the tornado tracks map.  This map went mainstream because people thought it was pretty.  Then they started noticing things and asking questions.  When people stop and look because something is cool, the thing to note is that they stopped and looked.  When something you design is visually striking, you stuff it with the currency that buys thoughtful attention.
The greatest step you can take towards honoring the aesthetics of your map is to avoid defaults (#3).  Also, I like this discussion at Stack Exchange -lots of variability (and more detail than an unrequested tip).

I feel like a real tool actually citing an example for this, but it was a solid lesson for me in the importance of aesthetics in map design and its capacity to infiltrate a wide audience.  Geographic data has potential energy like no other form -appealing design converts that into kinetic energy. From Tornado Tracks.

#13: Sometimes maps are a terrible way of presenting a geographic phenomenon. Don’t carto so quickly.
Because you are a cartographer, of course you'll be inclined to map geographic data geographically.  But some of the inherent properties of geography make the strict spatial representation of a phenomenon an inefficient and ineffective means of presenting it.  It's not heresy to present it another way and I hope you never feel bound by spatial in the presentation tier.

I first saw this data rendered as a set of many many maps that you could pick to see one at a time (one world map for every historic Olympic games).  Effective comparison between games was tough.  Also, the geographic size of countries varies dramatically (and distracted from the message) and many of them I couldn't see or even tell which were which.  The data was compact and awesome, but divested into a string of maps wasn't doing it justice.
In one cell chart, the mutual dimensions of countries, eras, and rates, increases findability, and traces the lifelines of whole nations at a glance.  Plus it happened to look like a DNA stain, which was serendipitous.  P.S. This is a screenshot of Excel.  From Olympic Medal Counts In Perspective.

While the lion's share of the work was heavy geoprocessing across several spatial data sets, the result above is a distilled set of lists.  Just because something is hard to do doesn't mean it should look like it was hard to do.  The opposite, really.  The relative geographic sizes, shapes, and locations of these cities made their literal mapping impractical and damaging to the message.  From Drunk Driving in American Cities.

Sparklines provide a data-dense and intuitive representation of 100 years of the apportionment balancing act for every state.  From Visualizing Apportionment.

#14: Using Mercator if you don’t have to, or Equirectangular for...anything? Use something else, anything else!

Another plea to avoid defaults!  Equirectangular is the convenient de-facto of GIS data distribution (pretty much what you get if you never consider projection in your process).  Once you are looking at that data, Equirectangular's job is done.  A hallmark of the bush leagues, it should under no circumstances survive into map production (except maybe if you are tracking satellites, but really, are you tracking satellites?).
Mercator is, admittedly, a fair tradeoff if you are making a web map.  Currently there isn't a ton you can do about that.  But if you are making a static map from scratch and you aren't leaning on a tiled service for your basemap then why would you use it?  Picking a projection that illustrates your phenomenon well, or in a novel perspective, can be the most mind-blowing part of cartography.

While a little disorienting at first (that's fine, there is evidence that struggle promotes memory retention), the polar projection is my favorite part of this map.  It reveals the nestedly cyclic nature of hurricanes and invokes a fun fractal-like consideration of the universe.  From Hurricanes Since 1851.

{Are you still reading this with the inner-monologue of Morgan Freeman?  I was serious about that.}

#15: Don’t box out your legend or supporting charts. They should be integrated, not quarantined.
I used to be the carto-segregation king.  Everything got a box!  In time, and with the advice of Amy Lobben, I began dispensing with the neatline and integrating visual elements.  There is research that shows a more integrated placement of data-conveyance elements (words, charts, maps, images...) facilitates a faster and firmer understanding of the phenomenon.  Also, I've an ally in Tufte in this regard so take it up with him if you want to stick all your illustrations in a crappy appendix!
Daniel Huffman (once more) provides detail and clarity in the plight against neatlines.


Nobody puts Baby in the corner.  Integrate map, notes, charts, graphics, legend, whatevz (also, check out how that chart is also a legend! Boom, #4!).

Conversely, the understanding that proximity implies a relationship can be leveraged to team elements up for cross-comparison within a single graphic.  From Telling the Truth and Mapping the Truth.

#15: Do you need that basemap? Can it be simplified? Sometimes enough data can provide its own geographic context.
Mostly what I mean is, does your data really need to have that Google Maps background?  Google Maps is a great wayfinding and placefinding utility, but not so much for the background of a data map.  Often there is much more noise than signal in a consumer-oriented basemap, altering and sometimes damaging the effective presentation of your phenomenon.  Try out some alternate (simpler) tile sources if you are making a web map.  And if you are making a static map, try pushing back your basemap prominence either a lot or into oblivion.
If your data is dense enough, it may well provide enough context to support itself.  A basemap is only there to provide a geographic reference, and should not be an almanac of all things spatial (maybe it doesn't need all those roads, railroads, golf courses, rivers...).

Sometimes even a single data source, like building footprints, is so data-dense that its cookie-cut negative space provides the context for the phenomenon.  From Sandy and the Buildings of NYC.

The phenomenon is the focus.  Faint major arterial roads and state borders are enough to provide a geographic orientation.  From A National Portrait of Drunk Driving.

#16: Show that same mapped data in companion charts. More visual dimensions for discovery.
Companion charts don't have to be different data.  If you can present some quality of that geographic data in one or more other visual constructs, than a fuller picture of the phenomenon is presented.  They all begin to support and illuminate eachother.  An ecosystem of goodness.

Showing the exact same data in many dimensions illuminates trends and strengthens the value of each.

#17 Stuck with stoplight colors? Pick similar hues that are still cool for the color-deficient. I blow this all the time.
Sometimes the effective cultural conventions of color override what might be a more efficient means of assigning color.  Bring on the stoplight metaphor.  If you are mapping poor, good, best or slow, medium, and fast, then you will be forsaking an awful lot of reader pre-programming if you don't use good old green yellow and red.  But that doesn't mean you have to use the more troublesome flavors of those hues, pushing green one way and red another way makes them far more discernible to the color-deficient.
Red-green vision deficiency is just prevalent enough that you can't ignore it with notions of practicality and just rare enough that the use of troublesome color combinations is still common.
I botch this all the time, but I increasingly take efforts to run graphics through color-deficiency simulators and tweak hues so that the colors are discernible.

Simulators are great empathy resources.  You can tweak your hues to be more palatable (wink) to the color-deficient.  From Charting for Understanding.

#18: Try de-saturating that satellite background. Like, a lot.
Always maintain focus of message.  Only use a satellite background if that satellite imagery is providing more benefit-through-context than deficit-through-complexity (#15).  If your mapped phenomenon sits atop a satellite basmap, mute the saturation of the imagery so it does not fight with or diminish the star of the show.  Also it just looks really cool (#12).  When I reduce the colors of satellite background imagery I generally push it back to about 20% of its original saturation.  Fully black-and-white is alright, but there is a sort of gravitas, and plenty of valuable surface context, when the imagery retains some of its hue.

Desaturated satellite imagery is easier on the eyes, feels more profound, and is a more effective basemap.
From Severe Satellite Basemaps.  Source satellite imagery via NASA Visible Earth.

#19: Put unfamiliar units into meaningful context, or tangible comparisons. Nobody really understands what a Megawatt is.
If you can translate an unfamiliar or intangible unit into something readers can picture or feel, then the map is more relateable and the nature of the phenomenon is more likely to speak to the reader (communication is the only reason there has ever been to make a map).  However, if you are mapping electrical field specifications for aerospace specialists and electrical engineers, definitely do not convert technical units into something cute (engineers were bred to reject metaphor and had their cute receptors surgically removed in college).

Not that I totally relate to units of nuclear power plants either, but parsing Megawatts into something remotely tangible provides perspective and clarity of message.  From Major Fires Flip-Book.

#20: Did you make a pretty cool map? Pretty AND cool? Put it on the web and get ready to live! People love maps!
When you suspect you'll be releasing something into the wild, that map will dominate one you know will have no audience.  I assure you that sharing your work will sharpen its quality.  Also, people eat maps up, and the world needs more excellent examples of them -be ready for all sorts of insights and questions from people who are experts in all sorts of things and people who are simply curious.  You may be surprised to learn that there is an eager market for your product and you have little right to keep it to yourself.


Edward Appleby gets it.

You might find, as I have, that making maps and flinging them out into the world is intensely rewarding and to not participate in the adventure of creation when you suspect you've got what it takes is a shame.  If making maps or making whatever is something inside you that you just enjoy, chances are you'll get reasonably good at it and that satisfaction will permeate you and those that encounter your work.

If one advances confidently in the direction of his dreams, and endeavors to live the life which he has imagined, he will meet with a success unexpected in common hours.


 

Thursday, October 31, 2013

20 Unrequested Map Tips part 1

Golly I like maps.  I make them and I look at them and I imagine them in my head when I look at spreadsheets.  Some are better than others, and after a while I've noticed some things that tend to work and plenty of things that don't.  I'll tend to use examples of my own stuff because it's easy to ask my permission (not because I know everything and always get it right).  Here are some map-making tips you did not ask for...

#1: Aggregate reluctantly.
Rolling up data into bigger chunks removes information.  When you do that geographically, you inherently degrade the resolution of the data and maybe mislead (on the flip-side you get a tidy summary of a phenomenon...that may or may not be true).  But almost certainly you make it look less-cool.  People are shockingly good at detecting patterns from noise (sometimes too good).  Maybe it's a good call to aggregate your map data into bigger units and that's the way to go, but don't just do it as a knee-jerk reaction to a big data set.  I mapped on mental cruise-control in that way for a long tome and in hindsight missed out on lots of cool opportunities.

Aggregation inherently diminishes nuance.
Which map will give Bear a more realistic sense of the political landscape of his fellow citizens? From Election 2012.

#2: Makers need to make. Give them the chance or they'll move on.
If you are a cartographer, or hire cartographers, the ones that are any good are the ones that have maps in them that are going to come out one way or another.  If a maker doesn't have a creative outlet for their own ideas, they will feel a diminished sense of purpose as the fine abrasion of solving other people's problems wears down the sharpness of their intrinsic satisfaction.
Seeking Truth is one of the three pillars of motivation in the human endeavor, according to the compact framework of Plato (by way of Jeffrey Wagner).
A solid portion of official time spent mapping what you feel like will make a you as a cartographer more intrinsically motivated, more curious about and practiced in alternative methods, more tuned-in to the community, and more invested in the rest of the work you do.  You'll be better.  Or you'll find yourself mysteriously interested in other opportunities.

I don't have a graphic for this one.

#3: Defaults are evil! Stay away from the defaults!
You are not among the legion of mappers that are happy to crank out a GIS-ville map where not a single default was considered and changed.  But if you were...
Default whats?  Default projection (Equirectangular, see #14), default colors, default range classification (whatever the GIS threw at you -probably "natural breaks"), default range labels (truncated attribute names with underscores) default auto-layouts full of huge north arrows, overzealous neatlines, and scalebars that label in meaningless units and precision.
Defaults are nice because they let us see our stuff right away without manually setting 19 preferences before any data is rendered.  But that's it.  Change each and every one, because you thought about them.  I've made plenty of ugly maps in my life, and they were usually the result of my lazy acceptance of the default assembly line.
Daniel Huffman did a great job of helpfully describing why certain maps fail, over at Cartastrphe.  I recognize lots of default-ridden examples in there.

I made this unfairly poor map, using the magic of defaults.


He hates these cans! Stay away from the cans! In this illustration...the cans are defaults.  And I'm Navin.


#4: Can your legend double as a supporting chart? That liability is now an asset.
Legends are like collateral damage.  An unfortunate reality of getting a job done.  They only exist because the map is too hard to decipher on its own and needs a de-coder tool, and often, that's just the way it is.  But if you can add a dimension of data into the legend then it becomes a chart and pulls its own weight.  You can think of this in reverse, too.  If your map has a companion chart (which is awesome), use the same colors, for example, as the map and in that way they support and explain each other (then just scrap that dead weight legend).

In this case, the chart steals the show while also serving to legend the maps.  From Tornado Travel Map.

Acts of piracy color-coded to time makes a helpful chart and removes the need for a dedicated legend. From the Piracy Top 5.

#5: Does your phenomenon care about political boundaries? Maybe not.
Political units are the most over-used geometry in mapping.  They are really convenient because you can download them anywhere and the lion's share of geographic data is already aggregated into those areas.  And that's fine.  But remember that you aren't mapping data, you are mapping a phenomenon.  And if your phenomenon couldn't care less about counties, states, and countries (pretty much anything that doesn't involve humans) then neither should you.
BUT even if your phenomenon doesn't care about political boundaries, adding them in as a faint reference will provide geographic context.

A tornado doesn't care what state it passes through.  But adding a minimal state reference helps readers orient themselves and identify familiar places ("What's up with the tornado-free zone around West Virginia?"). From Tornado Tracks.

#6: Only aggregate to political boundaries if you want to (should) pin the phenomenon to politics.
This is pretty similar to #6, but its overuse bears some repeating.  What should you stuff into political polygons?  Anything that you want to associate with a politician or a cultural identity.  This includes the bulk of social scienc-y data, like population demographics, economic measures, and cultural characteristics and perceptions.  Even if mapping to political areas is the way to go, consider something other than a boring old choropleth.  Mapping data to political shapes does not automatically mean you make a choropleth.

Identifying specific counties with extremes in home vacancy rates is a natural fit for mapping with political areas. From Lights Out.

Sometimes the desire to attach a cultural place (building footprints) with a natural phenomenon (hurricane flooding) is such that that you take efforts to cram a-political data into political zones (as a means of personalizing a phenomenon using relateable places). From Sandy and the Buildings of NYC.

#7: To animate or to small-multiple?  Just make both.
Seriously.  If you've made one then you've pretty much made the other.  Throw them both out there and let folks get insights via either one.  Do you get more out of cartoons or comics?  Here's a cartoon of the comic, and here's a comic of the cartoon.
But, if you do animate, be wary of interpolated (guesses) transitions between stops (knowns).  Long smooth transitions damage change detection -which is why you are animating in the first place.  Readers will notice more change in a flip-book style animation than when there is a longer transition (short-term memory leaks between data A and data B); the "pleasing" transition inherently disguises differences.




You have the materials for both if you have them for either.  Just release the both of them and hedge your carto bets.
From Somali Pirate Years.

#8: Were you asked to use a dozen colors to denote categories? Run, it’s a trap!
This is one of those instances where you should hear what you are asked to do but listen for the actual problem to solve.  This is a really big issue and a huge (and valuable) skill to develop.  You were hired for your expertise, so don't be timid to respectfully propose preferred alternatives to a client.  But be ready to rationalize it.  I use this example because it seems to be the most common evidence in the map-making world of the gap between assuming the role of a technical resource (cog) vs. being a knowledge worker.  "Make them different colors" is easy to request but try to deliver an actual solution, rather than scratch off a task item (this is more easily said than done depending on the customer).
Since you know that our visual system is increasingly terrible at differentiating beyond a handful of hues, it's ok to suggest strategies that are effective (and likely more aesthetically pleasing).

Don't do this (sorry Guardian).

#9: Did you make it? Put your name on it! Were you influenced by others? Hat tips all around!
Always sign your work.  There is no better quality assurance measure than stamping your name to something.  If you are designing in autonomy it can be too easy to crank out sub-par work.  And on the flip side, you ought to be proud of the work you've done and it's right to attach ownership in this little way.  Earned esteem is another of the big three motivators.  Don't be ashamed by it, on balance.
The cartographic community isn't huge, and like any ecosystem we're influenced and inspired by others.  That's terrific, and much of the fun of being among a group of familiar faces is the leapfrogging that might not happen in a professional vacuum.  Just be generous in the citations and hat tips you attach to your work.  If your map is an extrapolation of somebody else's map, say so -they'll probably be excited to see it.  If yours is an exercise in applying somebody else's aesthetics to some new data, say so -they'll likely be honored.  Plus, you'll increase your audience and maybe find yourself to be an exciting thread in your own professional network.

Develop a citation layout that you like and try to be consistent with it.  If you have a writing domain like a map blog or Visual.ly, you can elaborate on the cast of influential characters there. From Election 2012.

#10: Can you get away with encoding color right in your map's title and scrap the “legend”? Go for it.
Sometimes the phenomenon you are mapping only needs a little bit of help to let the user know what they are seeing.  Especially when you are using a few colors to represent different categories.  If you can, try coloring the names of the categories right in the map's title and do away with the overly literal math equation (this = that).

The largely-pictoral title of a commuting map intrinsically connects topic and color. From Biking & Walking to Work.

The encoding of color to meaning in this title carries over to four separate types of illustrations throughout the graphic. From Game Day Fatalities.

A map of gender dispersion in New York is legended directly in the title. From Gender Flow NYC.

Rather than a legend that noted the dot-to-people ratio (1=1) and indicated color with little equations (this colored circle = this type of commuter) the use of color in the title removes unnecessary elements and provides smoother continuity from topic to graphic. From People Dots: Seattle Area Commuting.


Give up, or are you thirsty for more?! Head over to Unrequested Map Tips 11 - 20...


  

Wednesday, October 23, 2013

Dasymetric Dot Density and the Uncanny Valley

All of cartography is a lie.  And there are pros and cons that go along with lying more truthfully.  Dasymetric dot density mapping is one way of lying more truthfully.  Here's the lowdown...

Dasymetric just means cookie-cutting the areas (like countries) for which you have data (like population) into more specific areas (NASA's zones of populated places) that do a better job of restricting those zones to where your data actually occurs.

Hmmmm...
One of the great things about dot density mapping is that it normalizes for area all by itself.  You don't have to do a ratio of population divided by square miles (a cognitive abstraction) and then key that up to a sequence of colors (another cognitive abstraction) like you would with a choropleth map.  But one of the sort-of drawbacks of dot density mapping is that the dots are randomly distributed within their areas -all you can control is how many dots.  And if the dots are representing any sort of human data (like bicyclists, demographics, votes, commuters, downloads, etc.) then you are assuredly sprinkling many of them around in places that are obviously unpopulated.  Sometimes that's ok, but sometimes it's pretty silly.  Dasymetric mapping means we pare back our areas to only those that are likely to contain the phenomenon of interest (which was collected at that lower resolution).
Here's the Natural Earth cultural boundary file of countries.  It is a fantastic and generous resource, which I hope you check out.  It also has a field for estimated population, which I'll use as my example.

The countries of the world, provided by Natural Earth.

Inspired by Derek Watkins' fantastic squinty-eyed look at population densities (itself inspired by Wild Bill), I downloaded NASA's population density imagery and retained only the areas where they have estimated a population density of at least 5 people per square kilometer (seemed like a reasonable cut-off for "populated place"), converted it to a vector polygon set and then clipped the Natural Earth countries by it.
This is the result, in blue.  You can download this file for your own pursuits, here.

The countries of the world, pared back to populated areas.  Download this shapefile.

Before Dasymetric Clipping, and After
Here's a dot density map of the world showing population per country (each dot represents 50,000 people).  By the way, I use population because it's convenient for illustration.  So the map below is ok, and I do get a sense of which countries have more turf than people -overall, but it is not all that characteristic of how distributed the people are where people actually are.
Take Australia for instance.  The average Australian lives in a city perched along the coast.  And the fact that the rest of the continent is pretty much devoid of humans doesn't mean that they look around their neighborhood and see fewer people.  It's an imprecise look at population for countries with vast stretches of low or unpopulated areas (i.e. pretty much everywhere except Europe).  Alaska sucks up many of the dots that really ought to go into the lower 48.  Other obvious examples of people dots happily dispersed in vast lonely tracts are Russia and Canada.

Before
A standard dot density map of population (each dot represents 50,000 people).  There is comfort in this view, because it is familiar, though that familiarity is a lie.  Or at least wildly imprecise.

Below, I did the dot density mapping only inside my new clipped country shapes, where there is actually a population.  Overall there is much less visual country-to-country variability in the density, compared to the map above, but this is a much more accurate* picture of real population density.  Check out Australia.  Now, instead of implying every neighbor lives miles away, I get a truer sense of their actual population density.  I also get previously invisible insights into local distribution, like Egypt along the Nile, Canada in scattered cities nearer the border, Russia in their southwest, Algeria along the Mediterranean, and so on.  Dots dutifully avoid deserts, water, tundra, jungle, and more deserts.

After
A sort-of-dasymetric dot density map of population (each dot still represents 50,000 people).  While each country's overall population density (not all that meaningful, when you think about it) is harder to distinguish, the local population density is way truer.  But maybe misleadingly precise?

*All of Cartography is a Lie
The act of constraining a dot density map to more realistic (dasymetric) zones has a couple of drawbacks.  The first is that I lose that raw at-a-glance illustration of an overall national population density (though I would counter with the fact that this is a truer representation of actual local density). The second, and much bigger problem is emotional shenanigans.  A dasymetric dot density map can impart too great an expectation of precision.  Because I've taken the half-step of tighter population zones, it is entirely likely that readers assume more of its local distribution than is appropriate and take this is a direct and literal placement of people dots.  A problem of scale and false confidence.  The dot density map is still spraying dots randomly inside areas (it's just that the areas are more realistic).  India is a good example of this.  Because virtually all of India met the do people live here requirement (compared to scattered specks of population areas in the American west and pretty much all of Canada), all of India gets an evenly random dispersion of dots.  In reality there is a way higher density of folks living in the northeast band.  While this map doesn't have population data at that resolution, the precise speckles elsewhere in the world imply that it does.

The Cartographic Uncanny Valley
As a map-maker you will have to understand the balance of actual precision and perceived precision.  Doing your best to take steps toward an honest representation of a phenomenon could mayyyybe land you in the cartographic truth version of the uncanny valley.  Really generalized maps are clearly generalizations and are generously interpreted models of a phenomenon (at the cost of nuance).  Really precise maps are understood to be more literal pictures of where (at the cost of larger trends and scale-ability).  In-between precision can leave the reader wondering what level of scrutiny to apply which can inspire mistrust and revulsion.  So there's that.
The uncanny valley.  The hypothetical emotional response in terms of perceived realism.  This concept may come into play when a map reader is unsure of the level of generalization a map is showing them.