Wednesday, 10 December 2014

Types of Data Visualisation

There are various types of data visualisation, depending on the information and format you would like to display it in.

Chart:
Map:

Network:

Time-series:
Hierarchy:
Flow:
Matrix:
Infographic:

Data Visualisation

Data visualisation is what infographics is more commonly known as within science. Its called data visualisation due to the nature of it taking written discoveries and tests and turning them into a visual format that describes the results in a more concise way. Some people argue that data visualisation is different to infographics due to that infographics aims to communicate rather than comparison like data visualisation.


This data visualisation represents the different codes found at the end of web addresses which identifies the country it originates from. They way they chose to visualise it is by placing the code to corresponding country on the map replacing the outline of the world map with alternating size codes. On the full version there is also a key at the bottom that lists the countries and colour codes them with the map. The visualisation turns what could be a boring list into an engaging visual that readers can have fun with.

"The main goal of data visualization is its ability to visualize data, communicating information clearly and effectivelty. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful."



This data visualisation represents fatty molecules dissolved in biological tissue which can render organs transparent and easier to examine. The key part is tagging fluorescent colours to certain cell types which gives a colourful render of brain, coded and ready for identifying. The brain in the diagram above is a mouse brain.

Picture Superiority Effect

The Picture Superiority Effect is the idea that the brain has a higher retention rate for images rather than text especially over longer periods of time. The effectiveness of the image though is determined by its ability to reinforce the message in the text. They must correlate for the brain to retain the information.



“Based on research into the Picture Superiority Effect, when we read text alone, we are likely to remember only 10 percent of the information 3 days later. If that information is presented to us as text combined with a relevant image, we are likely to remember 65 percent of the information 3 days later.” - John Medina, Brain Rules, 2008

Types of image that use the Picture Superiority Effect include charts, graphs, digrams and data visualisations. These images dont work alone but increase the effectiveness of the information found in text and helps the brain to retain it longer.

One theory suggests that the reason the brain retains image better than text is because the brain has 2 compartments for remembering. One for image and one for text. But in the text part image is also encoded as well which suggest the picture superiority effect. Because the brain uses 2 memory stores for image and text is often considered to be why we have high level of retention.

"Because pictures are often encoded in both memory stores whereas words are not; pictures invoke naming upon study more often than words invoke imagery." [5]

Early Scientific Visualisation


 Power of Data Visualisation


This early diagram by Florence Nightingale is a perfect example early data visualization. The impact of this diagram comes from the shapes and subtle colours used, the alternating size of shapes gives little consistency but strong structure. The digram displays mortality rates during Crimean War. More specifically it shows the causes of mortality. The red in the centre shows wounds and the blue on the outside shows preventable diseases aquired in hospitals. The right diagram shows mortality rates from 1854-1855 whereas on the left it is 1855-1856 when health and sanitation had been increased and shows the decline in deaths. Showing it in the format of the 2 circles also decreases the amount of space used and in turn helps it to create more impact. That displaying something rather complicated in such a clear and consise way hadnt been seen before and "Is truly of those diagrams that has actually changed the world, its changed science, its changed the way in which things were done"

Are scientific visuals art?

Design of Science

Wired compiled 10 research graphics that visually standout. They are often glanced at or overlooked within the design community simply because of functional nature of material they are asscociated with even though this seems unfair.


This visual above demonstrates the "waggle dance" done by honeybees in there hive. It involves and series complicated steps that inform other bees of there exact location. The image above shows the steps of 742 waggle dances by individual bees. Using this data scientists hope to make honeybee robots and that can replicate this data. The visual itself creates a nice effect with intense colours. The image almost looks monochrome if it wasnt for blackened areas and a hint of yellow in the centre.

"The Power of Visuals to Solve Problems"

The Power of Visuals to Solve Problems

In this blog post a man talks about how he is helping his 10yr old with a maths problem and that to help him they both have to understand it on the same level. The man discovers that in order to reach the right answer and better understand the question he has draw graphs and visuals.

 "They look at strategy as something new and full of words they’ve heard and numbers they’ve seen before, but it comes to them in a way that it reads like a story problem. It’s just words and figures on paper. It’s hard to see them come to life – to become something meaningful that they can relate to."

The visuals help solidify the entire problem into one solid image that can be digested and understood better than any 500+. The words may convey specifics better but the visuals help to display the basic idea and meaning behind what your reading so as soon as you have finished reading the visual ties it altogether to create an actual understanding.

Proposal

Aims:
My aim is to explore and research visuals and infographics within science to see how they crucial they are to informing readers and helping them understand. Because science is so complicated and requires understanding of lots of theories, ideas and words visuals are often much easier to engage with and comprehend when it comes to science. I aim to explore this and see how the visuals inform and whether the approach has changed over the last 15 years due major technological and scientific advances. I will also examine the effectiveness of the visuals based on the its target market or whether he visuals are unbiased towards age or prior knowledge.

Question:
Is scientific data visualisation the only way to really understand science and can everyone interpret them?

Keywords:
Design
Information
Visuals
Graphs
Diagrams
Infographics
Science

Structure:
Introduction
Modern scientific visuals
Scientific visualization
Data Visuliazation
Picture Superiority Effect
Developing or emerging aesthetic trends
Contrast and differences between both
The introduction of computers and did this change the scientific communities approach?
As science became more complicated did the visuals?
What is the importance of these visuals in science?