Lecture Pod 6

Data Visualization

David McCandless hosts a TED talk explaining data visualization and its importance in today’s world. As a society and with today’s technology we a re producing more data than we ever have, allowing us to work with this data in opening new worlds and leads to information.

McCandless continues to show the audience several different types of data visualization. The sets of data are humorous in a way, yet can be read clear and concise in the accuracy and simple details, demonstrating how through data we can develop these new ideas and information to reveal interesting things. He continues to say:

But if you look at it directly, it’s just a lot of numbers and disconnected facts. But if you start working with it and playing with it in a certain way, interesting things can appear and different patterns can be revealed.”

McCandless goes on to mention that seeing data in context is very important; as visual representations of data are not there to just look pretty, they are guides in leading  individuals to the story or answer to their questions. Overall, McCandless demonstrates these importance of data visualization and how information design is about solving information problems.

Click here to view video.

Lecture Pod 5

What is data journalism?

Data journalism is the use of information, data and key data elements to develop stories.   As creators and analyzers of data we can use stories to create and find new patterns in data and use data to create new stories. Not only does data journalism focus on the source of the data, but it allows us to exhibit the data in all its entirety. This form of journalism allows data and stories to work hand in hand in presenting and informing individuals of key information.

In today’s world, data has existed for hundreds of years, where as data journalism did not exist till 2009. With today’s technology and the use of data it has opened up a world which allows us to interpret and create visual data on new levels. From simple printed visuals, to now interactive graphs and data, technology has allowed data and their stories to grow almost effortlessly.

A great example of the development of data visualization in journalism was a project created and developed by the guardian (2013), which showcased the Olympic nations and how other areas aside from athletic abilities would affect their performance at the Olympics. The data was set clearly and was concise allowing the audience to create endless stories and develop even more stories with focusing on specific areas of their desired country. This is a prime example in the development of data journalism and how it is used to create stories.

Lecture Pod 4

Why do we use graphs?

With the abundance of data and information in today’s world, graphs can be used to gather and display this data accordingly. We use graphs to make data comparisons easier. When creating graphs some shapes can be more effective when representing the data. Circles for example can be used using different size, although circles can cause some misjudgment when analyzing data, squares can be very effective in being very effective in accuracy of data representation.

Different graphic approaches can tailor to different types of human perception. Specific types of graphs can allow the audience/viewers to take a better perception of the data presented allowing the correct information to be processed

Bar Chart – Popular because they are very useful, easy to use and many have a familiarity to them which is a big advantage. Quick to compare  information and to compare data across categories.

Line Chart – Primary use is to display trends and changes within data over a period time.

Pie Chart – Used mostly to compare data in percentages.

Lecture Pod 3

Visual data has grown to become one the key elements in understanding data and information presented. With access to hundreds and thousands of different types of data in today’s world, it is critical we use and present this data in the easiest way so that individuals comprehend and analyze this data in order to develop significant stories, information or connections.

A prime example of collecting and presenting data, comes from Florence Nightingale. A nurse during the Crimean war between the Russian and British in the 1850’s, she took care of wounded and fallen soldiers during the war. During this time, Nightingale realized that soldiers began to die more than frequently, this was due to malnutrition, poor sanitation and lack of activity (L.Cmielewski, 2016). Nightingale kept records of the deaths within the medical ward as a part of patient welfare, turning these records into graphs. 


Overall the graphs developed by Nightingale indicate that the wounds of the soldiers were not the true responsibility for the deaths occurring within the ward. Suggesting that due to poor conditions and the level of hygiene during this time allowed for diseases to be the main cause of death within the ward.

Ultimately, this allows for us as designers to understand the fundamentals of collecting specific data and creating a clear visual representation of the data so that it can be analyzed and comprehended by other individuals easily.

image source(s): https://upload.wikimedia.org/wikipedia/commons/1/17/Nightingale-mortality.jpg


Lecture Pod 2

There are 4 main data types. These are nominal data, ordinal data, interval data and ratio data. Nominal data consist of name categories and is ordered. Ordinal data is usually data collected of non numerical categories, the key for ordinal data is to use order. Interval data is collection of numerical data which has value and can be differentiated.Ratio data is similar to interval data, it uses numerical values and can tell and differentiate between numerical values and units. However it does have meaningful zero point. This zero is the absence of whatever is being measured.

The main point of the lecture pod would be learning to differentiate the types of data and what types of data can be collected from using one of these types of data.


Lecture Pod 1


Data is the values of qualitative or quantitative variables which belong to a specific set of items, when applied with visual components data can be interpreted and given meaning. Data visualization demands designers to engage with aesthetics and form in order to create data with a meaning. Data visualization is one of the key foundations and a modern equivalent of visual communication

The main point of the lecture pod would be the key difference between data visualization and information visualization. The key difference between the two is that;

 Not all information visualizations are based on data, but all data visualizations are information visualizations. (Sarah Waterson, 2016)

Image: https://static01.nyt.com/images/2013/06/20/technology/20DATA_SPAN/20DATA_SPAN-tmagArticle.jpg  (accessed 25/07/16)

Data Visualization critique

What story does it tell?

The data visualisation titled ‘The depth of the problem’, is an inspired representation of a deep sea search for a missing Malaysian airliner that was discovered from the sound of the commercial aircraft’s underwater locator beacon. The example was produced as a result of the wreckages discovery by the Australian vessel, Ocean Shield, and the extent of the crews recovery attempt.

How does it tell it?

The story is told through an infographic that displays the depth in which the Malaysian airliners wreckage had sunk down to based on the Ocean Shield’s pinger locator data projections. Told through the a series of contemporary and historical milestones, the data representation emphasises the extreme lengths recovery crews would have to go through had they recovered the missing Malaysian airline.

Does it allow for different levels of interrogation that can be seen or used on the part of the reader? eg can they drill down to discover more detail?

The visualisation relies on comparative analysis to interpret the extent of the wreckage’s depth. The significance of each depth milestone is used by the reader to better understand the situation. There is very little in terms of hidden meanings or underlying messages in the datas representation but there is definitely room for further study if the reader desires. For example embedded within the infographic are a few interesting facts that refer to historical events, world records and deep sea marine life, all of which have great research potential. Unknown to the reader is whether the Malaysian airline was actually retrieved which is something that can be further explored.

Are you able to create multiple stories from it? If so what are they?

The comparative and cascading nature of the infographic suggests a journey into the deep both in past and present. The infographic holds historical value in its almost timeline like approach and reference to historical events whilst still maintaining contemporary value as a measuring tool.

What can you say about the visual design- layout, colour, typography visualisation style?

The visual approach takes on a flat design and a monochromatic colour scheme. Shades of blue represent the sky and the ocean and illustrate depth based on the darkness of the shade. The exception of the colour yellow within the infographics limited colour palette acts as a directional tool that signifies the focal point. Simple silhouettes creates excellent contrast that provide clarity in distinguishing background and foreground elements and text readability. The visualisations elongated nature and portrait orientation compliments the data in relation to depth.

What improvements would you suggest?

If I had to improve the infographic I would suggest incorporating more milestones to emphasise the sheer scale of the journey and compressing the graphic height-wise to improve view-ability. Arguably however, these features as they stand enhance the experience in both respects. Fewer milestones force the viewer to draw their eye further down and the elongated nature maintains the illusion of depth. Story-wise the information could be enhanced to mention what happened in the retrieval attempts, i.e., was the wreckage actually found?

Link: http://apps.washingtonpost.com/g/page/world/the-depth-of-the-problem/931/

Group members: Timothy Coloma, Adam Bills and Sebastian Delapaz.