Data visualisation and Art

Data is often seen to be as far removed from art as can be. A way of obtaining facts, information and statistics, it is technological rather than personal and beautiful.

Or is it?

Many designers and artists have straddled the line between art and information and used infographics and visualisations to create something that is not only relevant, but beautiful.

Bryan Christie, a New York based designer who regularly produces visualisations for the New York Times, is doing just that. Christie has used a combination of medical text books and MRI scans to reproduce the human hand in a virtual 3D space. The image is both scientific and beautiful.

http://ngm.nationalgeographic.com/2012/05/hands/zimmer-text

Christie said: “The medium I work in is a new form of photography; it is both sculptural and photographic. I model the figures in digital 3D on the computer then use a virtual camera within the computer to take a picture of the piece. There’s an interesting process that occurs in that my work is sculptural and exists in virtual three-dimensional space yet in the end it is viewed in two dimensions much like a photograph.”

Another example of the crossover between data, art and popular culture is Radiohead’s music video for House of Cards from their 2008 album, In Rainbows. The video was created using data visualisations created by Aaron Koblin. It uses 3D plotting technologies to collect information about the shapes and relative distances of objects, including lead singer Thom Yorke’s face, and then visualises the data. The result is eerily beautiful and surprisingly human, with the fragile nature of the lyrics and Yorke’s ethereal vocals perfectly complimented by the ghostly appearance of his face and the disconnected nature of the overall visual image.

http://www.youtube.com/watch?v=8nTFjVm9sTQ

Artists, too, have recognised the potential of data in art. In 2008 the Museum of Modern Art featured an exhibition by Harris and Kamvar, entitled I Want You to Want Me, and which made use of data visualisations to present the pieces. The exhibition, which included a fully interactive 56 inch touch screen installation, chronicles the world’s long-term relationship with romance, and gathered data from a variety of online dating sites in order to give viewers an insight into people’s personal lives. I Want You to Want Me was a beautiful collaboration of computer science, maths and art that uses data to evoke viewers’ emotions at a very personal level. The infographic image further raised questions about the virtual nature of modern relationships regarding dating sites.

http://iwantyoutowantme.org/statement.html

Data visualisations are thus not only an informative way to present a narrative, but can also be a beautiful one. In certain circumstances it can even be considered to be art.

 

 

Why Data Journalism is Important

After studying Data Journalism for a year at City University I have come to appreciate the importance of having the skillset to make the most out of numbers and statistics. Many aspiring journalists still see data as something that is separate from journalism, and as something that does not interest them. In response, I have compiled some reasons why data is increasingly important:

1.       Make sense of Mass Information

Having the skills to scrape, analyse, clean and present data allows journalists to present complicated and otherwise incomprehensible information in a clear way. It is an essential part of journalism to find material and present it to the public. Understanding data allows journalists to do this with large amounts of information, which would otherwise be impossible to understand.

2.       New Approaches to Storytelling

Able to create infographics and visualisations, data journalists can see and present information in a new and interesting way. Stories no longer need to be linear and based solely on text. Data can be grafted into a narrative which people can read visually. Interactive elements of data visualisations allow people to explore the information presented and make sense of it in their own way.

3.       Data Journalism is the Future

Understanding data now will put journalists ahead of the game. Information is increasingly being sourced and presented using data. Journalists who refuse to adapt to the modern, increasingly technological world will be unable to get the best stories, by-lines and scoops and their careers will suffer as a result.

4.       Save Time

No longer must journalists pore over spread-sheets and numbers for hours when there could be a simpler way to organise the information. Being technologically savvy and knowing the skills to apply to data sets can save journalists time when cleaning, organising and making sense of data. Not making mistakes due to lack of knowledge can also save a journalist time.

5.       A way to see things you might otherwise not see

Understanding large data sets can allow journalists to see significant information that they might otherwise have overlooked. Equally, some stories are best told using data visualisations as this enables people to see things that they might otherwise have been unable to understand.

 6.       A way to tell richer stories

Combining traditional methods of storytelling with data visualisations, infographics, video or photographs, creates richer, more interesting and detailed stories.

7.       Data is an essential part of Journalism

Many journalists do not see data as a specialist and separate area of journalism, but an interwoven, essential and important element of it. It is not there to replace traditional methods of finding information, but to enhance them. The journalist that can combine a good contact book and an understanding of data will be invaluable in the future.

Data and the London Mayoral elections – let the data help you decide

The Guardian’s Data Store have compiled a catalogue of all the data to do with London, to give readers an objective and overall view of what is happening in the capital.
Polly Curtis’ reality check on 12 April, pins Boris Johnson and Ken Livingstone against each other and asks, “Who is right on police numbers?” She then outlines the Met police figures for London, highlighting what each party have claimed. Polly’s verdict:

Johnson’s campaign is correct in claiming that police officer numbers have risen over his term, albeit only by 2.4% if you take the baseline to be the March 2008, closest to when he was elected in May. But Labour is right that since 2009, the last year that Livingstone budgeted for, numbers have fallen overall by 1.17%.

An interactive map of the number of cycle and pedestrian road casualties offers in insight into road traffic accident hotspots across London. The map produced by ITO World for campaigning group See Me, Save Me, gathers together a decade of road casualty data from the Department for Transport called Stats19. The map distinguishes between pedestrians and cyclists and divides them up between those who were hit by Heavy Goods Vehicles (HGV) and those that weren’t. It also shows the age of the pedestrian or cyclist and the year of the accident. The stand first of the map asks, “With transport a key issue in the mayoral election, what patterns does this map show?”

In addition to showing a map of poverty and deprivation in London, data behind health, education and crime, the Data Store have also created a map showing how London voted in the last Mayoral elections, to give an overview of the Conservative and Labour areas across the capital.

Looking into data and presenting them as maps and infographics can show the bigger context behind a story and make figures more accessible. The Guardian Data stores compilation of London Data allows readers to get an objective view of their city before making decisions on who to vote for this coming Thursday 3 May. Take a look at the data for yourself at http://www.guardian.co.uk/uk/series/london-the-data before voting begins in a couple of days!

VISUALISATION ANALYSIS #3

http://www.guardian.co.uk/news/datablog/interactive/2012/mar/26/office-for-national-statistics-health

Simon Rogers has published a fantastic interactive graphic for the Guardian Datastore that maps teenage pregnancy rates in England and Wales from 1998 to 2010.

The visualisation shows the conception rate of under-eighteen year olds, per 1000 women, in different counties across England and Wales. The interactive map is an ideal way to present the information, as the visualisation contains a large amount of data in a comprehensible way. From the graphic we can derive that the number of teenage pregnancies has declined in the last decade, although this varies by area.

In order to focus on a specific county the user can scroll the mouse over the map and click on a different area, labelled by county at the side of the map. Once you click on a county the line graph changes to show the counties’ change in number of teenage pregnancies by year and how this compares to the England and Wales average. This allows the user to have more detailed and specific information simply by clicking on the infographic. Thus the graphic allows users to see the more personalised, local data.

By using this tool the user can focus on various localised data, and see how they compare with each other. For example, in Wales it is apparent that poorer counties, such as Merthyr Tydfil and the South Wales Valleys, are significantly over the national average regarding the number of teenage pregnancies. In contrast, geographically close but wealthier counties like Monmouthshire and Powys are below the national average. In most cases this has not altered over the decade.

The map thus proves that in certain circumstances seeing only the larger data can give a limited understanding, as it shows a national decline in the number of teenage pregnancies but does not tell us that many individual counties have not changed significantly. In this way a graphic of this kind presents to users the ‘big picture’, in a clearer way than text alone.

The graphic also allows users to ignore information that is not of interest to them and to focus on geographical locations that are. This gives users a certain amount of control over the visualisation, as information is not decided for the user, as would be the case with textual narrative.

The interactive element of the visualisation allows users to find the story or information for themselves with no difficulty. This is more satisfying than simply being told information. At a time when the general public’s trust in journalism is low, visualisations such as this demonstrate that the journalist has not played around and sifted information but presented all of it to the user and allowed them to draw their own conclusions. In this way the user can get a more detailed, accurate and neutral understanding of the issue presented. It also breaks down the barrier between journalist and user and implies trust in the user to interpret and organise the data in an intelligent way.

The graph also uses visual symbols to organise the large amount of data. The map of England and Wales is easily recognisable, as is many of the counties. The counties that are under the national average are a light shade of blue and this gets darker as the percentage increases. The use of blue and purple makes the map visually attractive and the differences in shade easily identifiable. It is apparent that darker areas cluster together and that generally the North of England is darker than the South. In this way the user can obtain information from the visualisation by looking at it alone. The darker shade of purple stands out amongst the generally lighter shades and thus the graphic signals to the reader some of the most dramatic information. Thus, although the user is given control and the freedom to explore the data and draw their own conclusions, visual signals guide them to the most extreme data.

The orange circle that is drawn around a county when it is selected contrasts with the blue, making it clear. It also correlates with the colour of the line graph, making the visualisation easily readable.

By pressing ‘play’ the user can focus on one county and see how it breaks down by each year, as well as how the colours across the UK has changed by year, thus presenting more information.

The visualisation thus works as it presents a large amount of data comprehensibly. It allows the user to interpret and organise the data, but gives them visual signals to guide them. It also gives information for the whole country, as well as localised data, thus presenting the ‘big picture’. It is clear and easy to read and breaks down the barrier between journalist and user. It is therefore an excellent way to present the data.

Visualisation Analysis #1

Following on from my earlier post exploring different ways to present data, I have decided to analyse two examples of visualisations from the Guardian Data Store.

http://bit.ly/HsqsLf

The first is a map of UK fuel shortages; ‘The Petrol Panic Mapped’. The map works because it is clear, simple and easy to use. The map is interactive, giving the user control and allowing them to display the information in the way that best suits them, prioritising data that they find most interesting. It also makes viewing the map a more entertaining experience, keeping users on the page for longer.

Continue reading “Visualisation Analysis #1”

How to do a good visualisation and why it’s important

Visualisations are an important tool when presenting data, and can be used to show patterns, correlations and the ‘big picture’.

Ben Fry has said that visualisations ‘answer questions in a meaningful way that makes answers accessible to others’ and Paul Bradshaw explains that ‘visualisation is the process of giving a visual form to information which is otherwise dry or impenetrable.’

Traditionally stories have been conveyed through text, and visualisations have been used to display additional or supporting information. Recently, however, improved software has allowed journalists to create sophisticated narrative visualisations that are increasingly being used as standalone stories. These can be be linear and interactive, inviting verification, new questions and alternative explanations.

Continue reading “How to do a good visualisation and why it’s important”

15 Well Designed Twitter Infographics

 

FLASHUSER

Infographics are probably the best way to show different statistics ( social media, internet marketing, online advertising etc. ) in a pleasant and enjoyable form. The infographic, in most cases, communicates complex datas in a simple and understandable fashion. With a few words and lot of stylish, fun images a well designed infographic for sure will remain for a long period of time in your memory.

Because I enjoyed much of using Twitter, I assembled some of the best infographics around this social media network. Some of them are funny, while others can help you in your Twitter bussiness process.

Sit back in your comfortable chair and enjoy this colorful list of Twitter infographics 2011. For a full-size version please click on each image or visit the source author website.

1. A Visual History of Twitter

Source: Mashable

infographic-graphics-twitter_history

 

2. Twitter Facts and Figures

Source: Touchagency

twitter-facts-figures

[Read more…]

 

 

 

 

Are You Addicted to Your Mobile Phone [Infographic]

 

INFOGRAPHICS SHOWCASE 

This UK-based infographic asks if you are addicted to your mobile phone.  They say that 83% of people own mobile phones, and I am thinking they are talking about the population of the UK, because no way for the whole world, you know?  Of that 83%, 35% own smartphones.  Of the people who own cell phones, about half of them admit to be addicted to their devices.  Scary. [Read more…]

 

 

How does Google make money? [INFOGRAPHIC]

So Google is pretty much in every part of our online existence now. It helps us find information about random things, access our emails, watch videos online, sort our friends into circles, get analytics for our websites. It even helps us do data visualisations thanks to Google Fusion Tables.

There is no doubt that Google is making a lot of money but what is the actual break-down? Well, here is an awesome infographic found on the Awesome Inforgaphics website that answer that question. What do you think?