Page 36 - GIS for Science Technology Showcases

SMART MAPPING AND ARCADE TRANSFORM YOUR THEMATIC THINKING
Mark Harrower and Jim Herries, Esri
ArcGIS® Arcade is a simple scripting language for data in your maps. Arcade frees you to explore anyone’s published data, no download required, saving valuable hours of time. The expressions created in Arcade run on the fly, meaning you do not have to own the layer to calculate what you need for your map style, pop-up, or label.
Smart mapping is built into ArcGIS Online as a simple workflow for exploring your data, trying various styles of maps that might suit your data, and polishing the map’s final appearance. Smart mapping takes the guesswork out of making great thematic maps by using data-driven styling and intelligent defaults. But how do these two capabilities in ArcGIS change how you understand and map your data?
Arcade lets you explore and even extend the data without having to own it on a hard drive. Working with the data, you begin to see what you need for your map’s symbols, pop-ups, and labels.
Arcade expressions can be as simple as calculating a percentage, or converting a year from a string to a number. Other expressions use if-then logic to look at several attribute fields in each record and return an evaluation of that record’s data. Many of the map styles available in smart mapping are rooted in Arcade expressions that find relationships and patterns hidden among the columns of attribute data.
Crafting good maps traditionally requires authors to make dozens of interrelated decisions: what renderers, scales, basemaps, and colors to use; how many labels to use; how to classify the data; and whether the map needs boundaries, and if so, how to draw them.
Smart mapping taps into that desire for an easier but also useful pathway. Once you choose one or more attributes or Arcade expressions to map, smart mapping examines the types of attributes you chose (text, numbers, date) and suggests map styles for you to use. It doesn’t force you to use these settings. You can override the settings as needed.
Iteration and exploration are founding principles of geographic visualization. Why? Because data are complex and no single depiction of the data can answer every question. Sometimes we start a project thinking we know what kind of map or treatment we need, only to find, after some exploration, that there are more productive avenues to explore. Using Arcade makes it easier to uncover new patterns and share hidden insights within your data.
After settling on a map style, you then bring your expertise or research into play. The best maps use some kind of standard of comparison to communicate what’s “normal” and what’s not. You change the default colors and sizes to emphasize what’s important and de-emphasize what is less important—just as a road map clearly distinguishes major highways from residential streets and filters out dirt roads altogether.
Let’s consider some real examples. Say you are a climate scientist and want to compare average air temperatures for two different years for a bunch of cities. You could make one map for each year and scan back and forth to try and spot differences. But Arcade allows you to calculate the difference in temperature between two years—on the fly—and makes it easy to see which cities are getting warmer or cooler. The ability to derive new data from the raw data using Arcade expressions is the real magic in cartographic analysis.
Flexible data manipulation tools joined with flexible map visualization tools allow us to work at a pace unheard of in the past. You can say “show me only events that happened on Mondays” or “remove areas larger than 100 sq km and rerun” or “proportionally increase the symbol size of stores based on % year over year sales growth, because we need to see regional sales growth trends.”
Arcade can also help connect people to your maps by changing data into information and insight. You can easily format facts in map pop-ups so they are easier to digest. Earlier mapmaking technology often required users to read pop-ups with capitalized field names that seemed to shout at the reader (“AVGTMP02: 65.66”). But testing shows people learn and recall better if that information is presented in the same way that we speak (“In July 2002, the average temperature in London was 65.7°F”). But why stop there? Facts are far more meaningful when they’re contextualized. Arcade allows us to automatically derive context and significance for our information: “In July 2002, the average temperature in London was 65.7°F, while in 2019, it was 68.9°F (3.1 degrees higher).” Explaining information this way allows readers to uncover insights without having to do all the busywork.
The old pattern was to dump the data onscreen and let readers sort it out, if possible. Useful pop-ups verbally reinforce the map patterns that smart mapping reveals. The goal of all useful and engaging maps—whether they’re made for an audience of one or one million—is to turn data into insights and understanding.
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