I aim to shape products, interfaces and services that mediate meaningful dialogues between people, systems and their environments within everyday life.

Sep
15
2013

Visualizing Your Everyday Data

The Microsoft Garage hosted Everyday Data UX Hackathon last month posing the challenge to create an interactive visualization of data that surrounds us in our everyday lives.

We are always producing data; with the pervasiveness of wearables, we can collect so much information about ourselves to monitor, maintain, and improve our health. We looked at existing quantified self tools like Fitbit, Jawbone’s Up and the Nike FuelBand, which all visualize results of users’ actions but in very discrete bits of data that do not provide mid- to long-term perspectives, nor do they allow easy correlations to one to understand how to adapt or change behaviour. What if the data from those sources could be tied into dynamic and reactive visual documents to reflect, in real-time, how adjusting your behaviour could directly impact your life?

We set out to build a visualization that bridges the gulf between reflection and execution. We determined three main problems to tackle in order to achieve this goal: 1) data heterogeneity (how can we combine data of multiple dimensions to make correlations?); 2) macro overview vs micro details (how can we drill in to details and navigate our data points over time?); and 3) emotional design for motivation (how can a visualization motivate people for behavioural change?)

sketches

We explored many visualization methods to combine different dimensions of data. Metrics we were interested in were number of steps, activity level, hours of sleep, calories burned, number of floors climbed, etc. We used radar charts to summarize a person’s activities over a day, where each dimension is measured along a different axis originating from the same point. This produces a unique shape that can be overlaid on previous days’ activities to compare how you’re doing over time or it can be overlaid over a goal shape you’ve set. We also enabled detailed drill-downs to view a timeseries charting a single metric over a longer period of time, which can also be compared with other measures (e.g. calories consumed vs calories burned.)

day_view
multi_views

We also proposed an aesthetic, glance-able lock screen that show’s your day’s abstract shape. Live tiles on your phone can also who you a summary of your day’s progress through an easy to digest visualization.

mobile

Our design struck a fine balance between data art and raw data with a visualization combined with aesthetics that is not only functional in correlating your multiple activities but making it easily understandable and motivating people to adjust their behaviour. For future development, we’d like to look at plugging in different data sources (currently we’re only using Fitbit data), increasing interactivity like enabling manipulation of one dimension to see its impact on another aspect (eg. can increasing step count improve sleep quality), and providing smart inferences to make the data more actionable.

screenshot

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