TED Talk by Artist Nathalie Miebach takes weather data from storms and turns it into complex sculptures that embody the forces of nature and time. The sculptures then become a musical score for a string quartet to play.
The musical score played was made up of interactions of barometric pressure, wind and temperature readings that were recorded from Hurricane Noel in 2007.
Every single bead and every single coloured band represents a weather element that can be read as a musical note.
From the beginning, Nathalie extracts information from a specific environment using low tech data collecting devices and compares her findings with information on the internet. So she now has historical and real data, which she then compiles on separate clipboards and then she begins her translation process.
What Nathalie loves about her work is that it challenges assumptions of visual vocabulary and where it belongs in the world of art versus science.
The sculpture, depending on where it’s placed could be a sculpture, a three-dimensional visualisation of data or a musical score, and that’s what she likes is that it challenges the viewer as to what visual language is a part of science versus art versus music.
Reflection
The final TED talk by Natalie Miebach was an interesting use of data sets and how she turned these data sets into beautiful pieces of art. I learnt that as a designer there is a lot of uses for data and turning data into art sculptures is very inspiring and exciting.
David McCandless: The Beauty of Data Visualisation
The TED talk by David McCandless is about turning complex data sets into beautiful simple diagrams.
Good design, he suggests, is the best way to navigate information glut and possibly change the way we see the world.
McCandless believes that if you ask the right kind of question, or you work it in the right kind of way, interesting things can emerge.
To see the bigger picture, what’s needed is relative figures that are connected to other data, this can lead to changed perspectives
McCandless’ process begins with applying information visualisation to ideas and concepts. He believes that solving problems and providing elegant solutions, and information design are about solving information problems.
Visualising information can give us a very quick solution to those kinds of problems. Even when the information is terrible, the visual can be quite beautiful.
Reflection
The TED talk by Michael McCandless was an insightful lecture about the art and beauty of data visualisation. He talks about the complexity of data and how to turn these sets into beautiful simple diagrams.
Data journalism is the use of key information sets, key data and/or key reference elements to inform a story.
Data lets you tell a story in a way that people watching and receiving it will understand it an enjoy it.
As long as the workings and evidence behind the story data journalists can be open and transparent about that, it makes the story so much stronger.
Data journalism is the recognition of the power of measurement in helping public conversations. It is a modern way of doing journalism.
The Guardian are regraded as the pioneers of data journalism, they’ve had a strong history in data visualisation.
There are a number of people across the organisation who work with data everyday, from the research department to journalists to interactive designers and people who visualise data for a living.
Data is very important these days because there are huge amounts of data and we have access to tools and the ability to analyse it, find patterns, structure it and reveal trends.
Part 2: History of Data Journalism at The Guardian
Data Journalism is brand new, it relies on the technology of the moment and didn’t exist before 2009.
Journalists at The Guardian have been using data since the first issue of 1821.
The Manchester Guardian, 1821, has a front-page that consists entirely of averts, whilst the recent news content can be found on the inside of the paper.
An example of early data journalism in this edition is a table of data that lists every school in Manchester, with how many children in each school and the cost of girls and boys, this was 60 years before compulsory education.
By 1947, the paper quality is better and the content is much more visual.
The Guardian Data blog in 2013 is digital, an example from this new age era is when the meteorites hit Russia, data was taken from the meteorological site and used to map out and plot meteorite locations over the world. This gives journalists and news companies the power of speed to create a data visualisation, something that people would envy many decades ago.
Part 3: Data journalism in action: the London Olympics
The alternative medals table
The Guardian worked with the Imperial College London to create a live tale that sorts through nations at the 2012 Olympics.
You don’t want a designer to keep having to re-draw a new data visualisation each day.
The interactive designer had this visualisation running off a google spreadsheet,
The numbers were updated everyday and those changed those graphics live as it happened.
The most important thing about data that is supplied is it has to be precise and accurate, there has to be a logical way for the coding to talk back to the visual.
By exploring through the data ad visuals yourself, you can make your own assumptions and stories and engage within that community aspect of data journalism.
Reflection
In this lecture pod, I learnt what data journalism is and why it is useful. I also found the history of The Guardian interesting and the use of history and data journalism used for the London Olympics and the Battle of the Somme useful and engaging.
There is a great range of ways to present data to achieve this goal, often graphic designers use the wrong way because of aesthetic or what’s fashionable.
An example is the overuse of bubble charts
A chart recreated by Alberto Cairo from a Bloomberg news story, in his book “The Functional Art”
Alberto Cairo, The Functional Art, 2013
The chart shows the change in market capitalisation of various banks between 2007-2009.
The light grey bubbles represent 2007 and the dark grey bubbles represent 2009.
From this snapshot we can say over the two years their capitalisation cap decreased, all of these banks experienced a fall in their stock price.
The bubble chart is difficult to interpret figures from but looking at the same data in a bar chart it’s much easier to make a comparison and get the estimated figure.
You can make a graph wanting your audience to compare areas but they will automatically compare heights and widths. Using circles always makes us underestimate the size difference.
A ranking of different graphic approaches to compare data
Alberto Cairo, The Functional Art, 2013
Based on human visual perception, as we need to tailor the way that we show stuff. We need to understand the way human perceptions work to decide which way we’ll present data. The more accurate and easier the judgment is for your audience to make, the more likely they’ll take away the correct perception of the patterns you’re presenting.
Alberto Cairo, The Functional Art, 2013
A case of disastrous use of poorly designed charts is the Space Shuttle Challenger launch accident.
Cold weather leading up to launch day at the Kennedy Space Station
There were discussions between NASA and the manufacturers of the booster rocket about should the shuttle be launched on a cold day.
The discussion was about the O-rings which sealed the sections of the booster rocket and the possibility of if they would become damaged and unsafe.
The booster rocket engineers made a no launch recommendation, which was their first no launch recommendation in 12 years.
They faxed 13 graphics to support their recommendation.
History of O-Ring Damage in Field Joints
It shows a catalogue of all the earlier launch damage to the booster seals. It’s shown in the historical launch order from 1 to 24.
The problem is that obscures the two most important variables of interest, the relationship between temperature and the degree of damage.
The temperature is shown in the nose of the rockets
The degree of damage is in the legend in shaded areas
The rocket engineers chose to order their information by time, that is the order of launch not be temperature or degree of damage. This makes the diagrams cluttered and any pattern difficult to see.
Edward Tufty took that same data and redrew the rocket diagram as a starter plot graph.
Showing the relationship between temperature and O-ring damage. It reveals a clear pattern of damage and severity.
Scatter Plot of O-Ring Damage and Temperature of Field Joints
Bar Chart
Easy to use and the audience have a familiarity with them. It makes it quick to compare information and reveal highs and lows at a glance. Effective when you have numerical data across categories.
Line Chart
Connect individual numeric data points. Primary use is to display trends over a period of time.
Pie Chart
Commonly used but also very commonly misused. They are used to show the relative proportions or percentages of information. Limit the number of wedges to 6, if you need more than use a bar chart.
Reflection
In Lecture Pod Five, I learned why we use graphs as well as graphs being overused and not used properly and ultimately leading to disaster. Then the use of particular charts such as bar, line and pie charts are defined.
Historical and Contemporary Visualisation Methods – Part 2
Why visualise?
To help us gain an insight and an understanding into complex issues
The Functional Art:
An introduction to information graphics and visualisation by Alberto Cairo.
Visualisations are Useful and Functional
Cairo reads an article on the population of the world, he then reads of the conflicting ideas on the fertility rates; the average number of children born in each country.
Rising fertility in poor regions is the reason the earth has to support 7 billion people now and a forecast of 9 billion in the next 2 decades. Other doomsayers focus on the aging populations in developed countries where fertility rates are below 2.1 children per woman. This number is known as the replacement rate. If the replacement rate in a country is significantly below 2.1 that population will shrink over time, if it’s much higher than 2.1 you’ll have a much younger population in the future which can cause problems. Predominantly younger populations show greater rates of violence and crime.
The author of this article contradicted both of these apocalyptic thinking by discussing two interesting trends. On average fertilely in rich countries is very low but in the past few years, there has been a slight increase in the trend. On the other hand, poor countries are showing a decrease in average fertility. The author suggests that due to these trends, fertility rates everywhere will converge around 2.1 in a few decades and the world population will stabilise at 9 billion people.
The Rational Optimist: How Prosperity Evolves by Matt Ridley
The graph, however, does have some insufficient information, the graph is an aggregate of the data of all countries in the world it doesn’t show the multiple patterns the author discussed, it doesn’t show the rich countries with recovering fertilities and poor countries stabilizing their populations.
It’s hard to extract meaning from a table. Data from a table is difficult to look at and find a number and then memorise additional numbers and then make a comparison. It’s much clearer when looking at a graph and then easier to make compassions.
All the examples of graphs require an active engaged reader.
Reflection
Part Two to the history lecture pod continued to expand my knowledge and understanding of why we visualise data, how useful they are their primary functions.
Historical and Contemporary Visualisation Methods – Part 1
We use visualisation as a way to present large or complex data sets in a way that enables our audience to grasp those complexities with the least amount of work possible on their part.
Visualisation: War and Death
Napoleon’s invasion of Russia 1812
Napoleon’s Grande Armée of over 400,000 men, the largest army that’d been ever assembled up to that point in European history, headed towards Moscow.
Once they arrived in the Russian capital they found an empty city, it had been completely evacuated and stripped of its supplies. The army had to retreat and supplying the army on the way back was near impossible due to the harsh weather. The lack of grass weakened the armies horses, all of which died or were eaten by starving soldiers. Without horses the French cavalry became foot soldiers, cannons and wagons had to be abandoned depriving the army of artillery and support convoys.
As starvation and disease took their toll and desertion rates soared. The grand army was attacked several times by the Russians in their retreat. The crossing of the river Berezina was the final french catastrophe as two seperate Russian armies inflicted horrendous casualties on the reminisce of The Grande Armée. On December 14th 1812, The Grande Armée was expelled from Russian territory, only 10,000 out of 400,000 survived the Russian campaign.
Charles Joseph Minard
Napoleon’s invasion of Russia 1812
Made 50 years after the map shows the Polish border. The distance from the Polish border on the left to Moscow on the right is 900km
The orange line left to right shows the army crossing the Neman River and advancing to Russian territory. From right to left the dark line shows the army returning to the west crossing the Neman River with only 10,000 men.
The lower portion of the diagram is a graph, it reads from right to left and shows the temperature the army endured through Russia, the vertical lines connect the temperature with the army at those certain times. Starts at 0 degrees at Moscow and minus 30 degrees towards the retreat they made.
The diagram shows the magnitude of the events and how the campaign went from bad to worse over the course of a few months. A strength of data visualisation is that it can reduce the time necessary for understanding a given event.
Florence Nightingale Crimean War 1858
Crimea, South of Ukraine
War between Russia and the alliance including the British and the old ottoman empire
Florence Nightingale pioneered modern nursing practices while caring for wounded soldiers
Nightingale and volunteer women came to work in the hospital to take care of the soldiers. In 1855 things got critical and care was needed, Nightingale saw that soldiers were dying from malnutrition, poor sanitation and lack of activity. She strove to take care and improve the living conditions of the wounded troops.
She kept meticulous records of the death tolls in the hospital as evidence of the importance of patient welfare, she turned those records into graphs to show British commanders.
Otto Neurath 1882-1945
Otto Neurath ISOTYPE
A pioneer in the realms of socialists politics and economics in Vienna.
He invented a system called ISOTYPE
International System of TYpographic Picture Education
Serialisation of images, multiples of the same size
The reason of the industrial approach was a key idea was to bring the museum to the people. A exhibition pack could be shipped and then used to be put up display everywhere.
Reflection
I enjoyed this lecture pod as I like the historical events mentioned and how data was used to show statistics and hardship through stories. Using data historically taught me just how useful it is; as it changes perspective and helps tell history more accurate.
Ordinal Numbers assigned to place groups and items in a certain order; Order
Interval Numeric, has no meaningful 0 point
Ratio Like interval data except it does have a meaningful 0 point
Nominal, Ordinal, Interval and Ratio
Qualitative and Quantitative Data
Qualitative and Quantitative Data
Qualitative Non-numeric data
Quantitative Numeric data and quantifiable
Discrete Counted
Continuous Measured
Reflection
I found this lecture pod useful as I learnt about the types of data there are and what you can do with them. I also learnt how to distinguish these types of data between them all.
As individuals, we create a lot of data each day such as social media traces, smartphone trails, credit card purchases, travel locations.
Everything we do is quantified, this leaves an everlasting data trail.
New visualisation strategies and older ones are used to make sense of it all. We are enmeshed into a data economy that is more complex and generative than ever.
To Put Data In Perspective…
23 Exabytes (EB) of information was recorded and replicated in 2002. We now recored and transfer that much information every 7 days.
– School of information management and systems, University of California, USA.
* 1 EB = 1 Billion gigabytes
What is Data Visualisation ?
Data vis is the vis of data, it involves the creation and study of data
Data vis is an essential part of the communication process
Data rich time. contemporary digital world
Why We Need It
Users may have particular analytical tasks, such as making compassions or understanding causality, and the design principle of the graphic follows the task.
What Data Is
Data are values of qualitative or quantitative variables belonging to a set of items, can be visualised using graphs or images.
Effective visualisations helps users analyse and reason about data and evidence. It makes complex data more accessible, understandable and usable.
A bar chart may be simple but it is the best form of data visualisation if you have two variables.
A line chart is a good choice to show data over time.
Difference between a data visualisation and an infographic
Not all information visualisations are based on data, but all data visualisations are information visualisations.
In essence, some examples of infographics are just lists with pictures and not a data visualisation.
Effective visualisations help users analyse and reason about data and evidence. It makes complex data more accessible, understandable and usable.
Reflection
This lecture pod was useful as it introduced me to what data visualisation is and when it is needed in certain situations. My understanding of data visualisation has changed and I now see data visualisation from a while new perspective.
Jordan's Data Visualisation Blog 