Category: data logs

• Throughout the day: sent/received emails and texts, logged content and date/time by app software
• Throughout the day: water and electricity usage, logged by water/electricity meters
• Took the T: tapped RFID, logged account and value on account by MBTA
• Ate at Boston Burger Company: paid with credit card, logged payment information by Boston Burger Company, and location by credit card company
• Entered the Broad Institute: tapped RFID, logged name and time of entry, as well as elevator usage by the Broad
• Entered dorm: tapped RFID, probably logged things but not entirely sure what was logged? by MIT
• Watched TV: logged viewership by show network

As part of the CMS.631 Spring 2016 class, I decided to log all of the “data-generating” actions/activities that I did throughout the day (data-generating being defined as an activity that generates data that is being actively collected at that moment). Here is a log of what happened from the moment that I woke up until right now when I am about to go to sleep:

Format: Activity ; data sent ; entity that logs that data.

1. Turned my iPhone’s “Do Not Disturb” feature off ; Data about my phone settings; Apple iPhone log.
2. Sent a few texts with my iPhone ; Text-based message files ; Apple software and phone service provider.
3. Signed into apps like GMail, Notability, Google Maps, etc ; User information like location and app-specific action data ; Application provider.
4. Presented a ticket for a beer/wine tasting event ; User information such as name and ticket ID ; Tasting event manager who is verifying that only paying customers enter.
5. Used my credit card to pay for lunch at a restaurant in Chinatown ; Personal financial information such as credit card # ; credit card payments processing company + restaurant.
6. Used my credit card to add value to my T card ; Personal financial information such as credit card # ; MBTA.
7. Used my T card to tap into Park Street metro stop ; Personal location + basic info ; MBTA.
8. Used my MIT ID to get into MIT buildings ; Personal location + basic info ; MIT.
9. Took a picture with my phone ; Picture file + associated meta-data ; iPhone log.
10. Sent emails to various people ; Content-specific information ; Google.
11. Sent a few texts with my iPhone ; Text-based message files ; Apple software and phone service provider.
12. Modified a Facebook Event ; Content-specific information ; FaceBook.
13. Communicated with parents via FaceTime ; Meta-information about video stream ; Apple/iPhone log.
14. Used my credit card to pay for dinner at a restaurant in Kenmore Square ; Personal financial information such as credit card # ; credit card payments processing company + restaurant.
15. Sent emails to various people ; Content-specific information ; Google.
16. Sent a few texts with my iPhone ; Text-based message files ; Apple software and phone service provider.
17. Modified a Facebook Event ; Content-specific information ; FaceBook. 

    It is very interesting to see on even just a somewhat superficial level how much data is created during normal day-to-day operations due to the technology-based and data-rich communication and interaction systems that we have today. It is also a bit scary, and brings to clear light the necessity for ethical use of the data and the importance of data privacy and protocols.