The Visualisation is the Student Winner at the Information is Beautiful Awards, 2018.
As part of our Information Visualization-1 module, we were given an assignment in line with the DearData project by 'Stefanie Posavec' and 'Giorgia Lupi'. Design a layered visualization based on an area from our personal lives.
Being an avid cyclist, I decided to visualize my cycling rides over the past two years. The motivations in this endeavour were to observe seasonal variation in my cycling rides. I gathered few other interesting insights during my analysis.
The list below describes the variables and their description in the dataset. While some of these variablse are obtained from the web app Strava, others are personal annotations to add a layer of qualitative description.
- date: Date of the ride
- day: Day of the ride
- ride_name: Ride name as enetered by the user while saving the ride.
- origin: Place of origin for the ride
- prim_destn: Intended destination for the ride
- secn_destn: Additional areas covered on the ride
- time: Time (hour:min) taken to complete the cycle ride
- distance: Distance covered (meters) in the ride
- speed: Average speed (kmph) of the ride.
- elevation: Height gained (meters climbed overall) during the ride
- ride_type: Describes the type of cycle ride - workout/errand/commute/leisure
- ride_nature: Describes if the ride was a roundtrip (bothways) or a oneway trip
- achievements: Strava measures the rider's performance in local segments(ections of the road). Achievements highlights when the rider outdoes his previous 3 best attempts (Gold - Personal Record , Silver - Second Best, Bronze - Third Best)
- upload_type: How the ride was saved/tracked in Strava - Live(During the ride); Later (Post the ride)
- kudos: Appreciations given by your followers/ friends on Strava
- eateries: Places where I would stop for breakfast or a small food break
- highlights: Interesting events that occured during the ride (Derived from memory.)
Interstingly, during the initial phases of data analysis, I found that people (community members) tend to appreciate my commute rides more, than my workout rides. Commute ride - 6kms/ 1 kudos. Workout ride - 20kms/ 1 kudos.
- Since I wanted to analyze my cycling rides over the past months. I began drafting concepts for how a month would appear.
- Considering the cycle and its parts as the background context, I decided to consider each month as a wheel and the bike rides during the month be depicted as the wheel spokes.
- Further, I explored other bike parts to analogize with variables in my dataset (ride type, origin, destination, ride_nature etc.)
- Having gained an idea of the viz. schema and layout, the initial set of renders were developed in Tableau.
- I further visualized the same in Processing, to design for multiple months , considering the attributes.
- Rotate+ Map functions were used to draw the spokes as lines from the moving origin to the desired end point.
- Wheel Hub Size - Distance cycled in the month
- Wheel Hub Cap - Pie chart depicting the share of cycle rides by distance.
- Spoke length - Length of the cycle ride
- Spoke color - Type of ride (commute, workout, errand, leisure)
- Brake Pads - Indicators for origin and destination (spots where I stop my bike ride).
- Tread Length - Kudos by the community (how the community appreciates my cycle rides).
- Gear Icon - Achievement in the ride stages as measured by Strava (gold: PR, silver: second best time, bronze: third best time).
The final output is an A0 sized print visualization.full sized visualization.
- Refine acheivement icons
- Add Weekday-weekend analysis
- Resize wheel hub
- Add annotations.
- MS Excel - Collating, cleaning the ride data and structuring it into the final required data framework.
- Tableau + RAW - Basic intial plotting of the data to observe trends. Generating the required charts for the trial run.
- Processing - Rendering multiple Monthly charts for the years in the final visualisation.
- Illustrator - Composing the rendered charts in the final layout. Adding annotations and insights to the visualization. Apart from this, I also designed the required glyphs (brake pads for origin-destination, achievement icons, speed indicator) in Illustrator.
- Strava web app - Ride Statistics tracked via the mobile app.
- Accurat