As part of my project, I wish to inform and educate readers of my e-book about statistics, concepts and ideas emerging from our relationship to work and how the numbers translate to our beliefs.
I’ve watched a TED-Talk episode when David McCandless talks about importance and context of data visualisation, which gave me interesting insights and then ideas of how to incorporate data visualisation in my project.
David McCandless, self-titled Data Detective, emphasises how data can change our perspective and opinions on issues around us. We live in information era, and often we’re bombarded with numbers and figures, which can be overwhelming to a lot of people. Rather than putting all data into sentences full of numbers, without context, focusing on designing information so it makes visual sense and tells a story is a key to communicate said information.
‘Eye is an exquisitely sensitive to pattern in variations in colour, shape and pattern’, as David says. By combining written language with visual language, they can work together in the same time, so we can understand the information better without much confusion. By visualising data, it feels effortless and easy to grasp what the information is and have it already put into context, new perspectives and ideas can be born.
Data visualisation can be applied not only to numbers, but also to ideas and concepts. In my project I’m talking about women as work and societal concepts of it, and by visually presenting collected data on these subjects, I can communicate these ideas in a compresses, easy to understand way.
Example of how context of data is important to present full-picture of an issue:
In 2014-15 55% of apprenticeships were undertaken by women.1 This sound great, we can come to conclusions that women are training themselves and are more conscious about their careers and actually have time and resources to progress in a professional environment. Quite positive feeling.
However, when we add more context to this figures, it changes how we feel about it.
Whilst 55% of apprenticeships were undertaken by women, women only comprised 5% of those completing a STEM apprenticeship.2 This paints slightly different pictures. By adding more details about the apprenticeships, such as specific industry the apprenticeships were undertaken, it suggest that women are still subjected to gender discrimination while choosing a career.
Data collection and visualisation, depending on the amount of each, can become a long process, especially when only one person works on it. Because of my time constraints I’m only going to use already collected data, and visualise it in a simple but clear way.
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INDEX
- WISE, analysis of 2014/15 apprenticeships data, 2016.
- WISE, analysis of 2014/15 apprenticeships data, 2016.
