A Day’s Worth of Data

I wake up at 9:00a, make breakfast, snap a picture of it on my phone and post it to Instagram with relevant hashtags. [Data generated: photographic data – which is also synced between my Dropbox as well as my iCloud, timestamp data, and social engagement data via likes on Instagram – note: I do not choose to geotag my photos, although who knows what data Instagram is actually relaying to its servers…] In the meantime, I catch up on the day’s headlines on NYTimes Now – creating data on the articles that I read, and the links that I click through.

I receive a few texts from a friend, as well as from a colleague who is going to meet up with me this morning to film some short scenes for a documentary. I reply to the texts, creating metadata (timestamp, to/from) and content within the texts – all donated to my wireless carrier and iMessage.

I meet up with the colleague, and we film around my neighborhood – her camera records video and time data. We also take a bus, and I swipe my Charliecard as I board, creating a few more data points on my bus usage – the stop I got on at, and perhaps how many times I’ve swiped within this month (I have a monthly pass instead of a top-up card).

After filming, I return home to answer emails, and work on rescheduling many meetings and other engagements that have been cancelled due to the snow storm. In the process, I generate data through my email conversations (text content + metadata + geolocation through my ip), and through my calendar updates (schedule content and time data on when changes are made).

Once I get hungry, I make lunch and Instagram it, again generating more photographic data, timestamp data, and social engagement data.

I return to working on my laptop, editing documents and spreadsheets on Google docs while collaborating with other students on a research project. I leave behind a data trail of my document edits – both the content and timing of the edits. In the process, I also get in touch with my collaborators via Gtalk – generating more text data and metadata.

Taking a small break before transitioning to my next work-related task, I log into Pinterest (a guilty pleasure!) and browse for a bit. I notice that Pinterest is now showing me suggested posts (instead of only the posts curated by the people I choose to follow), and I update my settings to suppress these superfluous pins. I realized that no user setting will get rid of the “picked for you” pins, and I use Google to attempt to find another workaround (creating search data) – however, this effort is not successful and I end up closing all of the tabs that I opened related to this break – and in the meantime, generating more browser history data.

Later on, I finalized a paper submission – this created a few updates to my Dropbox history as I completed some last minute document and content edits, and reformatted a few images. I submitted the paper, and generating data about my submission – both the actual content submitted, as well as the metadata of when I submitted, the file names and types that I submitted, etc.

I take another break to watch an episode of “Modern Family” on Hulu, creating data (linked, unfortunately, to my Facebook account – since at some point in history I had linked my Hulu and Facebook accounts together) on my viewing behavior, on which ads I watched, and also on my click behavior, as well as adding more to my browser history data.

I go back to emails again, sending more emails and generating more email and conversation history as I confirm the meetings that I have tomorrow.

Finally, as I’m writing this blog post, I’m generating data via the hyperlinks that I add, and also the content that I’m generating (metadata on the post category, revision data, as well as the actual text)!

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