Data are a systematic representation of observations about reality. “Raw data” is an oxymoron. Every dataset has some underlying agenda–selecting which parameters to measure, which to ignore, and how to present results constructs a narrative, whether evaluating if Paxil is safe and effective for teens or deciding which state is the worst in the nation for African-American youth.
We’re living in the age of Big Data. As of 8:17am this morning, the citizens of the internet sent out over 200 million tweets, issuing forth upwards of 7,000 140-character opinions every single second.
Since we first figured out how to sequence DNA, humanity has accumulated a Petabyte of genome data. Clever computer scientists predict that, at the current pace, the exabytes of genome information we’ll accumulate by 2025 will EXCEED THE CAPACITY OF THE ENTIRE INTERNET.
The massive mountains of large-scale information suspended in The Cloud can overshadow the fact that we’re also living in an era where individuals generate information at an unprecedented rate. The technological tools that get us through our daily lives measure multiple aspects of existence: locations, steps taken, minutes spent scrolling through photos on instagram, likelihood of swiping left on tindr when confronted with a mustachioed match.
The fact that our devices so closely monitor our existence can be deeply unsettling. However, we all participate in the continuously quantified modern world. Returning to idyllically remembered “simpler times” before the big data revolution isn’t a realistic option.
Wrapping ourselves in tinfoil and becoming digital drop-outs wont really work either.
What we CAN do is choose to be empowered by the deluge of data at our fingerprints. We don’t have to be slaves to our devices. We can use them as tools to answer questions about ourselves.
Being able to execute a well controlled experiment and then analyze charts and graphs makes my PhD-brain itch in an entirely pleasing manner. I’m aware that with a sample size of one, results from self-quantification experiments are hardly generalizable and rarely statistically significant. However, investigating your own behavior can be a worthwhile, self-revelatory exercise.
Two women on opposite ends of the planet recently embarked on a personal high-tech/low-tech big data experimental art project. Over the course of a year, each participant quantified some aspect of themselves for one week at a time: purchases, food preferences, negative thoughts, clock-watching, apologies, alone time…even smiling at strangers. Then they drew hand-written postcards displaying their results with an explanation of how to interpret the images. The cards, catalogued at dear-data.com, are beautiful, arresting, revealing, and motivated me to think about my own behavior. I highly recommend browsing their entire archive.
We all have ideas about the things that we do, how often we do them, and what influences our behavior. However, it’s impossible to back up these beliefs without solid evidence. Fortunately, those magnificent/malevolent machines in our pockets give us ideal instruments to observe our tendencies.
For example, an app called Moment can monitor and quantify exactly how many times you glance at your phone throughout the day.
I found out that I looked at my phone 157 times last Sunday. I’m not proud of that statistic, but identifying a problem is the first step towards taking concrete goals to solve it.
I recently embarked on more satisfying dear-data type experiment, which I’d like to share with y’all. Being a mileage-junkie, I was curious to find out just how far I go in all of my endeavors. So, for one week, I measured the distance I travel, the modes of transportation that take me through the world, and the places that I go. The reason I picked these parameters stems from my identity as an endurance athlete. I spend a lot of time on my feet, on my bike or in the pool during my training.
Additionally, because I choose not to own a car in Madison, I typically traverse the city on foot or by bike. Covering distance for exercise feels somehow different than commuting, even though I move by my own power for both endeavors.
I was curious to granularly determine exactly how far I go on a given day. I was also interested to see the routes I took throughout Madison. I collected numerical distance data using GPS tracking on my Garmin Vivoactive Smartwatch. The watch continuously records steps taken throughout the day, which allowed me to derive walking distance by subtracting other activities from the total mileage tally.
I also took notes on nominal variables: location, mode of transportation, and route.
The resulting figure represents a week of carbohydrate-fueled wanderings rendered in technicolor stacked bar graphs to visualize total distance traveled each day, with different colors representing different modes of transportation. The routes are traced in corresponding colors on a map of the Madison Isthmus. The biggest challenge was resolution of the small hand-drawn map. Initially, I thought that I could convey the number of times I traveled a particular route by thickness of the line. I abandoned that tactic after my first attempt devolved into an overcrowded scribbled mess. Additionally, small incremental walking distances (such as getting up to use the restroom, navigating the aisles of Trader Joes, or wandering around my classroom as I teach) were below the resolution limit.
In deference to reviewer # 3, I must address one potential source of error in these data. Saturday and Sunday represent outliers from my typical routine. My dad visited, therefore I had access to a car. We drove to Tenney Park to go ice-skating, and also to a Yoga class.
Had my Dad not been in town I would have ridden my bicycle.
If I extended this experiment, the distance covered via automobile or ice skates would likely represent a far smaller proportion of the accumulated totals. In the context of this limited dataset, however, those 7.5 miles over 2 days may disproportionately skew the results.
I was surprised to learn that my radius of destinations within Madison is relatively small. I frequently bike to and from Yoga, classes, and my work with the College of Engineering’s communications office. I walk up and down State Street. My limited range does take me to pretty awesome places, though.
I was intrigued to observe that running expands my range, taking me further afield than any other mode of transportation.
However, because my runs begin and end at home, even though they cover significant distance, they never really GO anywhere.
I primarily reach the places that I stop and spend time at during the day by bike.
Finally, it was interesting to observe that I walked between 1.5 and 2.5 miles each day. I’m aware that the built in pedometer on my watch is a far-from-perfect measurement tool, and that the walking distances are derived data, but I believe the trends accurately represent reality. Some of that distance arose from walking to specific destinations (i.e. to Collectivo or The Overture Center).
I was more intrigued by how much distance I accumulate from strolling between buildings or going grocery shopping. If I had a perfectly to-scale map covering the entire city of Madison that updated in real-time, I could accurately display those micromeasurements. However, as Borges so presciently pointed out, an ideal map that shows absolutely everything is ultimately only matched in perfection by its uselessness.
“. . . In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.”
My map is far from perfect, but I think it is both revealing and aesthetically pleasing.
What do YOU think about the big-data world we live in?
What would you measure about yourself?