2018 Data Storytelling Studio @ MIT

Data Produced by Me on 02/21/2018

• Transaction data – Dunkin’ Donuts, Chipotle, Verdes
• Location data – phone tracking, Uber transactions
• Photo data – Snapchat
• Video data – street video cameras
• Browsing data – internet usage, searches
• Messaging data – text, emails
• Phone call data – calls, timestamp, location, people involved
• Future plans data – airline reservation, train reservation
• Food preference data – restaurant orders
• Sport team preference data – based on internet searches
• Shopping preferences/interests data – Amazon searches and purchases
• Spending patterns data
• Swipe-in/swipe-out data (with MIT ID card)

• Morning before classes:
  • Electricity usage data from turning on lights
  • Water usage data from shower
  • Location data from checking weather
  • Fitness data from step counter on phone during walk to campus
  • Apple Music usage data from listening music
• In class:
  • Took notes using OneNote
  • Took pictures of notes on blackboard
  • Google form data from in-class quiz and activities
• Lunch:
  • Credit card transaction data
  • Panda Express sales data
• After class:
  • Phone call minutes data
  • Credit card transaction data at Muji
  • Muji sales data
  • KungFu Tea app usage data (transaction, rewards system)
  • KungFu Tea sales data
  • SnapChat usage data
  • Fitness data on phone from walking to and from KungFu Tea
  • Attendance data from signing in at 6.009 staff meeting
• Dinner:
  • Electricity usage data from cooking on stove
  • Tap water data
  • Night:
  • Video data from recording videos at dance practice
  • Lab notebook data from prepping for tomorrow’s experiment
• Throughout the day:
  • Internet usage data (WiFi, phone data)
  • Various social media app usage data (Twitter, Instagram, Messenger)
  • Phone games usage data
  • YouTube video watching data

Here is a log of all the data points I created and collected on February 20th, 2018:

With digital devices:

• Digitally scanned my fingerprint several times using the touchID on my iPhone to unlock the device
• Connected to 3 different Wi-Fi networks
• I performed several taps and scrolls using apps on my iPhone
• Plugged a USB to USB-C adapters to my Macbook 6 times
• I visited more than 100 websites, 12 of them are new websites (never visited before). This generated around 14 tabs using Chrome.
• I skipped several ads on different platforms (especially on Youtube)
• Talked on iMessage with 3 different people and exchanged around 30 messages with them
• Played around 100 songs on Spotify
• Received 21 emails and sent 9 emails

With humans/world:

• Trash I have generated in the environment
• Executed a vast amount of social interactions with people (in the Media Lab, the restaurant…)
• Performed eye contact with another person several times
• Consumed oxygen and generated breathed out carbon dioxide

With Myself (I understand my thoughts as data points):

• Asked myself if I am happy at MIT twice
• Thought “What am I doing in this meeting?” around 6 times

It is very hard to collect and quantify all types of data we generate every day. Everything that exists can be analyzed, e.g.: Heart rate, the pressure applied to the ground with our feet…

The key questions are “What do we want to learn?” and “How can we learn that?”. Collecting data for the sake of collecting data is… somehow unethical and a waste of resources. At the same time, I understand that future technology might benefit from every single type of data collected in the past.

Throughout the day I:

• Took a shower which created water usage data
• Charged my phone/turned on lights which created electricity usage data
• Visited websites on my phone which created web traffic data
• Sent Facebook messages to my friends which created communication data
• Used my ID card to tap into buildings which created entrance log data
• Added myself to a lab queue which collects queue usage and timing data
• Walked to/from campus as well as across the Harvard Bridge while my phone collected location and “health” (number of steps) data
• Called my parents which created phone call data
• Swiped my credit card to buy a drink which created transaction data about my account as well as in Kung Fu Tea’s database
• Sent emails for a club which was stored in an Google Drive archive and created communication data about my account and the recipients

I logged my data on Tuesday the 21st and decided to aggregate it according to why the data was being captured. Was I logging it on purpose to collect and analyze information about myself? Was I willingly giving it to a company because I want them to do something useful with the data? Or was the data collection a by-product (from my perspective) of whatever I was really trying to do?

Data I deliberately chose to track about myself for the purpose of personal data analysis (most of which gets shared with other entities in the process):

• Heart rate, sleep, and steps were tracked via my smartwatch, which I never take off.
• Daily habits completed were recorded in a habit-tracking app (manual entry).
• Health and wellness information for the day was recorded in an app I built for women’s health tracking (manual entry).
• Time spent on work projects on Tuesday was recorded using HourStack (manual entry).

Data I chose to give to other entities in the hope that they would use it for my benefit:

• Listened to podcasts and music. NPR One app and Spotify track my listening habits and interests to make recommendations.
• Drove to work and choir practice. Car has a device that my insurance company uses to track my driving and (hopefully!) reduce my premium.
• Computer crashed. Chose to send reports to Apple to (again, hopefully) help them resolve issues.

Data other entities tracked as byproducts of my chosen activities (which were not primarily about sharing data)

• Location was tracked throughout the day by my computer and car GPS. I know I could turn this off, but haven’t even though I don’t use it.
• Campus facilities has data on when I entered my access-restricted office using my ID.
• Sent a lot of email. Google has most of this data (for multiple accounts) and Microsoft Exchange has the rest of it.
• Viewed, created, and edited a bunch of calendar events. Google has most of this data, Microsoft Exchange some of it, and iCloud has all of it (from all accounts) synced across my Apple devices.
• Viewed, created, and edited a bunch of documents in Google Drive and on my computer (local docs are all synced to Dropbox).
• Browsed the web for any number of things. Campus network, home network, Xfinity wifi hotspots, and AT&T cell network all presumably have lots of data about my web browsing and other internet usage, some of which is performed by background processes on my phone and computer that I don’t know are happening in the moment.
• I don’t know where they are, but I’m sure there were surveillance cameras at many of the locations I walked or drove through.