For my data collection, I decided to use the application Rescue Time. Rescue Time is ideally used to enhance productivity and manage the amount of time spent on ‘disruptive’ sites. The user can indicate a set of productivity goals with a set of sites that would be considered disruptive and calculate productivity on a daily basis based on media consumption.

 I, on the other hand decided not to set any goals and just record my consumption based on sites visited. I do have to note that I have reservations regarding the pre-defined categories in the application, especially when Twitter and Facebook are considered disruptive sites. I find this problematic, not only because I use both platforms to conduct research, but also because I find that both sites can be valuable sources of information and news. Let alone the fact that other forms of media, such as daily interactions and talks are obviously not recorded and thus not represented in this data set. My other reservation is the fact that I can pause the application and stop recording any media I consume. I have to admit I used it on multiple occasions, which gives a skewed result of how many hours I was online and the media I consumed. Regardless, I found quite interesting results and patterns in the data set which I present below.

When I first thought of doing this assignment, I thought of creating a time lapse video of the sites I consumed using the data I collected from Rescue Time. Unfortunately, I face a number of hurdles, one being that the data collected was difficult to translate into a video. More importantly my search for a tool that would be able to create this time lapse proved futile. I tested out Popcorn Maker, (I recalled someone once explaining how easy it was to use, but also the ability to add comments to the videos) However, when I signed up and started using it I realized that I can only create a video from already published media on the web. Not wanting to duplicate some steps and publish material online to then use for a video, I decided to use iMovie, which I surprisingly had never used (Final Cut Pro was my program of choice.) As I started to compile images and graphs onto the program, only to realize that I couldn’t truly translate what I wanted to do with the data using this program.

I eventually, and for the sake of time decided to stick with an info-graph which you can find HERE. I used the site infogr.am to create this graph, it is one of the many tools that are available on the web that can create info-graphics from raw data.

In addition to the info-graph I created, I decided to look into and present my daily consumption which varied from day to day, especially on the weekends.

Day 1 – Wednesday, not a complete report since I started Rescue Time in the afternoon.

Day 2: Thursday

Day 3: Friday

Day 4: Saturday

Day 5: Sunday

Day 6: Monday

Day 7: Tuesday

What became a noticeable media pattern is that I was consuming more social media in the early morning and late night during the day. Whereas during the day I spent most of my time on e-mail, scheduling and ‘learning’ sites.

Over the weekend I noticed that I had more time to catch up on the news. I have to admit as someone who considers themselves a news junkie, the fact that I spent so little time reading the news was shocking. Although, my news reading behavior has changed in recent years and I’ve started to rely more on social media as new source.

Having noted all those observations, I would still place a disclaimer and indicate that the data collected by Rescue Time is not entirely accurate and does not indicate time spent at talks, watching a film or media consumed on my phone.