A Pizza, as a (GIS) Map

Geographic Information Systems (GIS) are how maps come together… my kind of cartographic dishes. And in honor of GIS day on November 18th, we’re going to look at how a well-crafted pizza, from top to bottom, is just like what we all know as a map.

Pizza has became a staple of the global diet (especially mine), but like most people I hardly think about the long distances ingredients must travel to reach my table. The same can be said for maps. The composition of a GIS product is much like the composition of your favorite dish (unless your favorite meal is a bag of chips, then just a screenshot of your data will do just fine). For most people, a favorite dish is composed of a number of individual items coming from (possibly) distant sources then working oh-so-well when together in the kitchen… and again at your table.

Take the amazing pizza, a personal and global favorite, composed of: cured cheese (a long process), grain raised from seed (again, a long process), sometimes meat which is raised from infancy to market (a long process), not to mention tomatoes, peppers, and any other toppings that make it what you want. These grow to maturity, transported to your local supermarket or pizza parlor, and combined (in a quick process) to serve on a plate for a (possibly) quick lunch between meetings, or family style sit-down for a movie at home. It’s a simple dish with a long trip to the table.

Maps are these great plates of information which allow intrinsic data to be transformed graphically, visually and, most importantly, geospatially. Ask a 6-year-old to draw their route to and from school and it ends up looking like a messy pepperoni pizza, BUT it also tends to be (nearly) spatially spot-on. Our brains work in a web of connecting lines—just like county lines, streets, or dendritic rivers—but we can understand data more easily when its thrown on a map. Like how a National Geographic map about shark attacks is very telling when viewed in tabular form, but throw it on a map and the distribution becomes instantaneously more evident.

The data that go into a map can “travel” a long way and [should have] been through multiple quality checks. Maps aren’t easy to make. A chef can’t pluck a pizza off the neighborhood pizza tree, ’cause these things take time. As with nearly any worthwhile food, great effort is exerted in preparation, “maintenance”, quality assurance and dissemination through zip files and hard drives (take-out), web portals (supermarkets) and the chefs themselves (cartographers). Look at the layers a GIS may have and compare it to a pizza:

  • The Pizza Box. Geogeeks see a GIS framework as this abstract intangible connectivity of data layers thrown together for visualization. The layers work like the way tomato sauce and cheese nearly meld in the oven but remain (mostly) separate. It’s easier to see the broad term “GIS” meaning a number of things, including a geospatial process, procedure, tool and even software, but it also refers to the concepts we cook up in our cubicles. The box holds our idea.
  • The Crust. Any pizza connoisseur will tell you the crust can be the most important part. This is the medium in which a cartographer will build a dish. The medium is dependent on what is expected of an audience, such as engagement, response, and retention, but adversely the type of medium is dependent on the target audience. The crust is the starting point for your canvas, choosing the best way to transport the ingredients (i.e. story map, poster, pdf, geopdf, foldable pocket-sized print, etc) and meld them together to make pretty maps.

    Where do all the basemaps come from?

  • The Sauce and/or Cheese. This is the what-goes-on-bottom mentality… the basemap. You can use a thin New York style (streetmap), Chicago Deep Dish (imagery), or even a no sauce transparent New Haven (NoData). Some pizzas are made without sauce and others without cheese, it’s up to the cook (and of course the dietary restrictions of the consumer). If the data is good enough on it’s own then sometimes only a block of text, a chart, or a table is all that is needed. Most data can benefit from a visual component for a visual boost to really stress the geographic significance and relation to it’s surroundings.  These can take a long time to find their way out in the world, like a first-rate stewed sauce or an aged artisan cheese. Developing the technology to have imagery as a basemap has taken decades and a number of technological breakthroughs. When my friends get directions online, they use “Satellite” as the basemap but never understand how the basemap came to be and get upset when their 6-month-old home isn’t on the imagery yet… “Why can’t they update this yet!?” Except for us geospatial geeks, the public will never understand how much time goes into all layers. In my humble opinion, great maps have two types of basemaps: vector and raster. I like to use both in order to get a rich feel for the area. Loading in a terrain model beneath a roads shapefile allows insight into how the lay of the land affects real world activities and possibly your data, which we load in next.
  • The Toppings. Your data drives map development, as it is the star of your map. It’s the focus of all your effort. “Geospatial” can be a broad term too because it refers to a number of types of data, but each particularly keen on location, such as algae bloom locations or automotive fender-bender locations or real estate location, location, location (… I sense a theme there). The more time we spend collecting, analyzing, and scrutinizing the better the data and map will be. Don’t forget there are “supermarkets” to get a map or data… federal, state, and county web portals. Most of these á-la-carte toppings have been analyzed and scrutinized for you, so it’s easy to go ahead and throw them into a map locally along with local organic toppings, like meats, vegetables, and even sometimes fruits! Too many can mask the star of the show, or too little make the data feel spatially unconnected.

But the star will be your data. This is topping that matters. Throw two or three toppings on the map to accent your data rather than having to compete with those other datasets. A pepperoni pizza highlights the pepperoni whereas the veggie style doesn’t really highlight any one vegetable in particular (if you’re into that kind of thing), and a Hawaiian pizza equally brings forth Canadian bacon and pineapple. So take care in the overindulgence, it may not help the map and muddy the point.

  • Herbs and Spices. These are all the other little bits with which to personalize the canvas, like oregano, basil, or thyme. These are the ancillary pieces that can make the dish all so impressive. Much like color schemes and logos put your personal stamp on a map, the toppings can make a map more flavorful. I see the toppings as items like route numbers, or church and school symbols and, of course, large symbols for your data to make their locations standout. This gives the map more reverence and connection to the real-world.
  • Ingredient List. All maps need legends and metadata… non-negotiable. All food products need ingredient lists too. They inform the customer what they are getting themselves into (and keeping food allergens at-bay). The legend is merely the ingredient list informing the audience what they are looking at whereas the nutrition label shows the map makeup. We easily ignore the nutritional label until we don’t understand the map then it becomes a crucial part of the puzzle. Same goes for metadata. We look at metadata kinda like a chef looks at a recipe. If we want to repeat the recipe, we need the how-to.

There you have it… a map. The crust, sauce, cheese, and your locally sourced toppings add up to a beautiful map. So the next time you look at a map, try to see it for the individual pieces mapmakers see. Look at GIS as merely a collection of layered (delicious) ingredients that all come together from far, distant origins to make the perfect map. That city limit extent is really just a pepperoni that took time to grow, that land cover basemap is a thin Italian inspired tomato sauce that took time to stew… and the beautiful (ancillary) artisan cheese in the middle binds it all together.

I love maps… and pizza. #gisday #maps #geogeeks #geoweek #pizza #ThanksJesse