Data Visualization: Weed Decriminalization and Its Aftermath
We’ve all seen data visualizations — some of them effective; many of them simply pleasing graphics. We’re going to dive into the process of conceiving and crafting visuals that communicate information in ways that are useful, usable, and desirable. To do so, we need to create or find data to use for the project.
For our third project, we are compiling data on a topic and visualizing the complex data in an informative yet beautiful format. I’ve toyed with a couple of ideas, ranging from 1. looking at the number of Syrian refugee asylum applications, and how many of them were accepted to see if there’s a pattern (http://data.unhcr.org/syrianrefugees/asylum.php), and 2.comparing the usage percentage among teens in the US, vs. teens in Netherlands.
I’ve decided to narrow it down to visualizing firstly how the CO/WA legalization of cannabis has led to decrease in Mexican drug cartel rates involving cannabis distribution in the States, then comparing this to how much of a counter effect this has had on enabling the Mexican crime groups harvesting in the West to sell higher quality cannabis back to Mexico.
From a brainstorming session I had with my classmates, I realized I could take this many different and interesting ways. I am primarily interested in exploring two sub-topics:
- How did the decrease in U.S. demand for Mexican weed contribute to an increase in legal seizures in imported hard drugs like meth or heroin?
- How did U.S. weed legalization affect the overall crime rates in CO?
- Is the decrease in crime rate due more to increase in tourism (i.e. increase in police force) or to a decrease in alcohol consumption?
Boiling Down Ideas
After exploring several possible directions, I decided to tackle a more general overview of the subject, as I thought that it would leave room for more personal interpretation both from my side and the audience’s. So, the big question I’m asking with my data is:
Is there a link between the decriminalization of Soft Drugs and sales of Hard Drugs?
Let’s find out!
Hard Data to Work With — Objective Interpretation
With that question in mind, I started looking into press releases from the last year or two. I found that due to the decrease in U.S. demand for Mexican weed, sales profit for drug cartels in Mexico had plummeted: the quality of weed harvested in the States (legally) were much more superior than that grown in Mexico, and the price per gram of weed had decreased to less than half what it went for to CO-WA legalization. To make up for this loss, they apparently had started cooking methamphetamine that was purer and more potent, and they were aggressively pushing the sales of this much hard drug to the U.S. consumers, as suggested by the seizure numbers along the border.
I then started collecting the hard (official) numbers related to the topic and found that the US Drug Enforcement Administration released very thorough data with numbers, analyses, and trend reports annually. I found that while seizures numbers in marijuana — both domestic and along the US/Mexico border — were decreasing since the ’14 legalization in a couple of different US States, the numbers on meth seizures along the border had more than doubled from ’11 to ’14.
Soft Data to Work With — Subjective Interpretation
With this hard data, I wanted to convey that the decriminalization of a soft drug was unexpectedly giving rise to the consumption of harder drugs, and that this has an extremely dangerous effect on the health and general well-being of U.S. consumers, leading to an escalating number of drug-related deaths from ’11 and on.
Visualization Version #1
My first iterations of visualization was essentially an initial exploration of various possible forms that my data could take. The most important aspect that I wanted to show with my data was the general progression of changing numbers in drug seizures both domestic and along the border. Essentially, the user would interact with the years (2011 through 2014) to get a sense of how much shift there had been since the last year. I decided to first color code the four types of main drugs traded (marijuana, meth, heroin, and cocaine).
Per Stacie’s suggestion, though, I also wanted to somehow represent the geography pertaining to these data points, and I thought about mapping out a slightly abstract representation of the border line territory between the US and Mexico. It was, however, a struggle to represent it without having some of the data points fall on different geographic locations of the map, suggesting that the datas had something to do with certain specific border States, and specific Mexican cities, where in fact, the numbers that I wanted to display were simply US and Mexico drug seizures.
I toyed with circles, balloons, horizontal bars, vertical bars, geographic maps, and even layers of some of these combined, and concluded that the vertical bars with drugs color coded was closest to what I’d intended to represent: the different types of drugs, the progression of the changing numbers throughout the years, and an abstract representation of the geographic locations — the top bars representing domestic seizure numbers, and the bottom bars representing border seizure numbers.
Visualization Version #2
Another round of feedbacks from Stacie and my classmates brought another issues to the surface: why was the representation so cute and bright?? I mean, it is a rather depressing subject. And although I hadn’t intended to, I realized that with this data visualization, I was indirectly suggesting against the legalization of weed, even though I’m a strong proponent. A true designer’s dilemma that I don’t think I have an answer for.
In any case, I proceeded to opt in darker & more sobering colors (no pun intended), and embed some sort of organic representation pertaining to the suggestion of health implications following the increase of meth consumption.
Researching into the long-term effects of the drugs, I was able to gather that among other serious effects, heroin causes severe depression (dark blue), meth causes failures in the heart, brain, and reproductive system (dark red), and marijuana a sense of sluggishness and possible lapses in memory and bodily functionalities (dark green). This determined the colors of my string/bars.
I then wanted to somehow link this data with the previously mentioned soft data about the negative health risks caused by increasing meth consumption, for a “subjective” representation. After sketching out some quick sketches of the changing string/bars linking to brain/heart failures, I decided to represent this bit of data with an eye. As marijuana seizure decreases, meth seizure (and consumption) increases, and throughout the years, the strings penetrate more and more into the pupil.
Visualization Semi-Final Version
For the semi-final version of my visualization, I came up with a chart system with kg numbers that increase both downwards (for border) and upwards (for domestic) that grows exponentially to accommodate for the astronomical seizure numbers of marijuana compared to other drugs.
After the presentation and final round of feedbacks from the class, I made the following revisions:
- Revise the chart system so that there’s only one starting point now, as opposed to two from before
- Introduce a more clear indication of how user will interact (click) through the data
- Make individual drug data clickable and highlight the grid closest in number to actual data
- Add back in the cocaine data so that the data is a more comprehensive overview of the four major drugs being traded and seized
Further revisions I’d like to make are:
- Link the visualization more with the subject matter of drugs (i.e. eye symbolism’s too subtle as of now, how would I validate and better represent such qualitative data?)
- Think of a better way to introduce the individual drug bars, as the swirls seem to cause confusion
The growth of the U.S. marijuana industry has devastated drug cartels in Mexico, evidenced by fewer seizures of…dailycaller.com