Week 8 – Story

Our Time Data Exploration

Tree Map
Bar Graph
Gannt Chart

Make a Story

Gender Time Use

From the gannt chart shown above, females spend more time on personal care than men but the same amount on recreation. Even though there may be more females in the data, the results show how they use they use their time. It’s interesting to see that the recreation results for both genders are similar. By looking further into the recreation category, you can see that men are spending more time on video games while women spend double the amount on social media.


Flowing Data – The exploration of data by designers, statisticians including topics and data visualisation.

ABS – National Statical agency for the government of Australia.

Eager Eyes – Blog point by Robert Kosara who helps to visualise and understand data.

Guardian Data – Data stories told and visualised by the Guardian

Our World in Data – Data site designed to tell stories from the worlds largest issues

Data Art – BBC data visualised to show the connection between art and data with projects and images

About the Author

Hi there! My name is Tahlia & I’m currently in my second year of Visual Communication. I enjoy photography, videography and graphic design – I have built my own online profile under ‘Subtle Scene’ on Facebook and Instagram. From this unit, I’d like to further improve my skills in graphic design, illustrator and be able to understand data to design infographics.


Analysis of a Data Visualisation

By Chantelle & Tahlia

How People Like You Spend Their Time

Data visualisation: https://flowingdata.com/2016/12/06/how-people-like-you-spend-their-time/

What story does it tell?

This data piece tells the narrative of how different groups of people spend their time in a 24-hour period.  

How does it tell it?

It is told through showing a correlation between day to day activities with the hours spent per activity in a person’s day. 

The data type is a connected scatterplot. 

Vertical axis – activities 

Horizontal axis – hours in a day 

Does it allow for different levels of interrogation that can be seen or used on the part of the reader? eg can they drill down to discover more detail?

You are able to interrogate the data by gender, age, employment status and organising the data into a weekday or weekend. By filtering the variables the chart will determine the median hours for each activity shown through the orange line. At this point you can’t interrogate the data any further. We can’t interrogate the activities into sub categories. For example, under the activity travel/commute, we are unable to determine the type of transportation used. 

Are you able to create multiple stories from it? If so what are they?

Yes, each filter is interpreted different for example, almost 6 hours is spent on weekend leisure for a male aged 18-24, which is two more hours than females. 

What can you say about the visual design- layout, colour, typography, visualisation style?

The design layout is small and simple and blends to the content on the page. There are 2 colours used to display the data -the orange line helps to see which line is active making sure to include the grey inactive lines to visualise the amount of people surveyed. 

The typography is a little hard to read as the font used is smaller than the content, it would help if the activity headings were different from the hours by maybe using a different font weight or colour. 

What improvements would you suggest?

Being able to interrogate the data further. 

Being able to compare and contrast the data with different variables of gender, age, employment status and time of week. This would make the data more meaningful as you would be able to see a comparison of how a day is spent by different groups of people. If you were able to highlight the highest or lowest value to see comparison in the data. 

Where does the data come from, and comment on it’s source.

The data came from ‘The American Time Use Survey’ from the Bureau of Labor Statistics. 

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