Initial Research & My Data
December 5, 2013 § Leave a comment
What is data visualisation?
Data visualisation is the study of the visual representation of data, meaning “information that has been abstracted in some schematic form, including attributes or variables for the units of information”.
“The main goal of data visualization is its ability to visualize data, communicating information clearly and effectively. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often tend to discard the balance between design and function, creating gorgeous data visualizations which fail to serve its main purpose — communicate information.”
– Vitaly Friedman – Data Visualisation and Infographics
“Data visualization is the presentation of data in a pictorial or graphical format. For centuries, people have depended on visual representations such as charts and maps to understand information more easily and quickly. As more and more data is collected and analyzed, decision makers at all levels welcome data visualization software that enables them to see analytical results presented visually, find relevance among the millions of variables, communicate concepts and hypotheses to others, and even predict the future.
Because of the way the human brain processes information, it is faster for people to grasp the meaning of many data points when they are displayed in charts and graphs rather than poring over piles of spreadsheets or reading pages and pages of reports.”
– What Is Data Visualization from sas.com
The difference between information graphics and data visualisation
Data visualisation presents [of amounts/statistics]:
- patterns and relationships
What is my data set?
The data I have collected for this brief is of me moving around via different modes of transportation, categorised by walking, cycling, skateboarding and motorised transportation. The data tells me [for each means of transport (where applicable)] how many hours I’ve travelled, how many miles I’ve covered, the amount of calories burnt and the amount of steps taken on a single day. I’ve collected this rather complex set data over a period of two months, from the 22nd of August to the 22nd of September, using a free mobile app called ‘Moves‘ developed by graphic and infographic designer Nicholas Felton. I chose to go through with this data set as I tend to move around quite a lot and I was interested in what my movement would look like if I were to track it. I wanted to measure up my movements via different means of transport next to each other, looking upon these factors:
- Economics – efficiency (fuel, cost (over distance))
- Distance travelled
- Time spent travelling
- Geographical location
- Narrative of my movement
- Comparisons (primary and secondary data collection)
As well as collecting my own personal set of data I set out to gain data from other people. I created this survey called ‘Transport and You’ on the 18th September posting it on Facebook, gaining a total of 56 responses, which is a pretty good set of primary quantitative data to work with, allowing for comparisons and contrasts. As well as this I will research national statistics of people’s travel habits to gain a broad set of secondary quantitative data also for comparison, to attain this data I will use statistical facilities and resources such as Key Note, ONS (Office of National Statistics) and ProQuest.
“An ill – specified or preposterous model or puny data cannot be rescued by a graphic no matter how clever or fancy. A silly theory means a silly graphic”
– Edward R Tufte: The visual display of quantitative information
With the vast amount of data I have collected, I don’t think I have to worry about having “An ill – specified or preposterous model or puny data “
What I’m doing
My research process will help me gain more of an understanding about data visualisation and the many ways of presenting data into various formats, this research will help me choose how to present my own data. I will also reflect upon my data set and compile and analyse the survey results drawing observations from them which will be presented in my own data visualisation.
The below video is a TED talk about data visualisation and it’s importance.