Collecting data on oneself as a means of self-improvement: this is the goal of the movement known as “Quantified Self”,  whose tagline is self-knowledge through numbers, which uses life-logging/self-tracking as way to measure your personal activity, in order to make future judgements on your life choices. Data recorded on yourself can be used to give yourself new ways of dealing with health problems or prevent future ones. It can also be used to track and monitor your personal finance and spending patterns, in order to help you improve your financial planning.

Typically, participants of Quantified Self record a range of raw data on themselves over a time period: spending habits, calorie consumption, exercise logs, steps walked, mood, blood-sugar levels, sleeping patterns and so on. Collecting this data can be done through sophisticated means, such as wearable sensors, API’s, screen scraping, or through simple,low-tech solutions like writing it down in a logbook.

Data visualisation and the Quantified Self

With Quantified Self  life-loggers collecting raw data on themselves, how else can they analyse and make use of it? Through the practice of data visualisation- by giving form to your everyday habits, you can gain meaning from it.

The majority of data collected through self-tracking is chronological, as the person doing the tracking wants to look back at their past to see their mistakes. Charts like the line graph are ideal for spotting trends over time and in the example below you can see this clearly.

Quantified Self participant Steven Dean failed to take the advice of his coach that if his resting heart rate was 2-3 beats higher than on previous days, then it was very likely an indicator that his body was fighting an infection and therefore would need to cut back on the amount of training he was doing.  Steven fell ill three times, which is clearly reflected in the graph with the spikes in his resting heart rate.  Looking back on this evidence proved that what Steven’s coach mentioned was indeed true and gave him the proof to follow his advice.

On the Data Is Beautiful subreddit, user bozackDK used data collected from MyFitnessPal to create this visualisation below.  The smaller graph on the bottom part helps illustrate his progress and success in losing weight.

Some visualisations can reveal patterns influenced by other factors.  Using his Fitbit device, Eric Boam visualised the days he went cycling by colouring them yellow.  You can see there’s more yellow around the months of June and July, indicating that Eric was frequent in his cycling routine.  Most likely this was because of the good weather typical to those months.

Not all time based data needs to show trends.  Since 2005, designer Nicholas Felton has been producing his own “personal annual reports” that vividly present his life’s activities in a mixture of boldly displayed numerical totals, charts and maps.  Although some of his reports pages contain a few time-series graphs, Felton has relied more on typography and graphic design to make his everyday statistics engaging.

In her 2014 Personal Annual Report, Jehiah Czebar visualised in an interactive chart, the total amount of time she had visited each coffee shop within a year:

Geography can be another source of self-tracking.  Logging places you’ve visited and where or how far you’ve jogged on a map are common forms of this.  Felton has also been recording and displaying various geographical data on his yearly reports as well:

While some of the examples above are visually impressive appropriations of personal data, some have been able to monetise their data.

Federico Zannier launched a successful Kickstarter campaign in May 2013, in which he raised $2,733 in just 30 days – all from selling his personal data online.  Zannier logged all his e-mails, GPS data, chat logs, browser history, mouse movements, screenshots and even collected webcam shots of himself every 30 seconds.

Openly selling such intimate information online would be shocking to most people, so why did Zannier violate his own privacy?  According to him, it was to make a statement about privacy.  By being able to sell your own personal data, Zannier hopes people can take back ownership of it.  Social media websites make millions of dollars selling our online information to marketing firms, so why can’t we do the same and be the ones doing the selling instead?

In a forthcoming article , I’ll be looking at data visualisation and Quantified Self  in Financial Services. Nowadays most of our day-to-day transactions are handled by digital means. On one hand, the flow of money in and out of our lives has become easier, yet we are becoming less able to interpret , or visualise what’s happening with that money. How can financial services organisations address that?