Data Visualisation Links

These are some links to data visualisations I liked.

This data vis is a mapping of USA with colour coding part owned by different people. https://www.bloomberg.com/graphics/2019-largest-landowners-in-us/

This data vis is an animated graphic of school statistics in the USA. https://www.washingtonpost.com/graphics/2019/local/school-diversity-data/

This data vis is an animated video of the globe and the area which are affected by fires. https://earthobservatory.nasa.gov/images/145421/building-a-long-term-record-of-fire

This data vis compares graphs to highlight the change in time and difference for gender names. https://flowingdata.com/2019/08/28/gender-switched-names/

This data vis is a motion picture of earthquakes through time colour coded. https://www.nytimes.com/interactive/2019/07/19/us/california-earthquakes.html

Mini Tasks

Mini Task 1

This Data Visualisation is of University Students and the amount of time they spend on a screen. In more detail the dashboard has sheets conveying the types of screen used, during what times and also comparing screen use between males and females.

University Students Screen Time

Mini Task 2

Story

Analysis of a Data Visualisation

The Data visualisation me and my partner Marc chose was from a Washington Post on Natural disasters reported by Meko (2019).

Meko, T. (2019). Mapping America’s wicked weather and deadly disaster [Image]. Retrieved from https://www.washingtonpost.com/graphics/2019/national/mapping-disasters/?noredirect=on

Questions

1. What story does it tell?

This data from the washington post shows data visualisation using a heat map on America to depict the natural disasters that occurred during 2008 to 2018. So for the first one, it shows which part of america was the most affected from flooding, through the heat map this data conveys, the part which suffered the most is conveyed with different shades of blue. These data visualisations are very easy to understand. Like for the second one, it shows the tornadoes and hurricanes that passed through america, with the green representing tornadoes, while the orange representing the hurricanes.

2. How does it tell it? 

As mentioned previously, this data uses heat maps to visualise their data.

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

We noticed that the right side of America is more prone to natural disaster compared to the left side of america, so maybe, by creating a data vis it can highlight the top to lowest affected states.

4. What can you say about the visual design

The data vis is minimal in design as well as the colour of the map so the bright colours of the natural disasters can be highlighted for the viewers to focus on.

5. layout, colour, typography, visualisation style? 

They both use the same map of the united states and visual style of having minimal design to their data vis and they show this through the use of a heatmap. The flood map uses different shades of blue to symbolise the water level in the areas shown. The hurricane/tornado map uses contrasting colours for the tornadoes(green) and hurricanes(orange) which also have different shades to them, to signify their wind speeds.

6. What improvements would you suggest?

An improvement I can see that could be to add are animation to the data to show the movement and directions of disasters as well as making the state lines and text more visible, as sometimes, the white text doesn’t contrast enough with the data, which makes it hard to read.

7. Where does the data came from, and comment on it’s source.

From the washington post and they got the data from:

  1. NOAA Storm prediction centre
  2. National hurricane centre
  3. Iowa national environmental mesonet archive

This source is reputable as they are government websites with specialists in this field of study

Reference

Meko, T. (2019, April 25). Mapping America’s wicked weather and deadly disaster. Washington Post. Retrieved from https://www.washingtonpost.com/graphics/2019/national/mapping-disasters/?noredirect=on

Week 8 Lecture Pod

Summary

In this weeks lecture pod we go through a TedTalk on Art made of storms by Miebach (2011). During her talk she gives the audience a song which is made from the patterns of weather. Miebach (2011) transformed data into a physical model where she also translated into music and reports that visualisation of data is about the eye of the beholder and can have different meanings depending on the circumstance such as if the data was shown in gallery or science show.

Reflection

From what I got from the video is that data visualisation can be made to be anything however you make it as it all depends on the situation and how it is perceived.

Reference

Miebach, N. (2011). Art made from storms [Video File]. Retrieved from https://www.ted.com/talks/nathalie_miebach?referrer=playlist-art_from_data#t-236292

Week 7 Lecture Pod

Summary

In this weeks lecture pod we learn about the beauty of data visualization by McCandless (2010). According to McCandless (2010), there is no point of data if they are not given meaning such as giving them more visuals and patterns to better understand them as the eyes are very sensitive to them and only through close analysis of them can you find true stories. He also highlights that trends can also be a leading factor to data as the media likes to bring them forward more (McCandless, 2010).

Reflection

From what I got from the video, is that data visualisation can showcase can be conveyed in many different ways such as square charts or bell lines but they have to be made to make sense.

Reference

McCandless, D. (2010). The beauty of data visualization [Video file]. Retrieved from https://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization#t-235035

Week 6 Lecture Pod

Summary

In this weeks lecture pod, we go through three different videos which is what is data journalism, the history of data journalism and data journalism by The Guardian (2013). Data journalism is making stories out of data, it can be out of words or designing maps according to The Guardian (2013). At The Guardian (2013), they have been doing data in journalism since 1821 and on 1901 is when they represented data and on 1943 is better designed data for users to better understand and 2013 where a digital map is shown. Data journalism in action is to research check and compare statistics and see if there’s a story from it (The Guardian, 2013).

Reflection

What I got from the videos is that data journalism is all about the facts and when you want to convey your facts it has to be in a way that your audience can easily understand.

Reference

The Guardian. (2013). What is data journalism [Video file]. Retrieved from https://www.youtube.com/watch?v=IBOhZn28TsE

The Guardian. (2013). History of data journalism at The Guardian [Video file]. Retrieved from https://www.youtube.com/watch?v=iIa5EoxyvZI

The Guardian. (2013). Data Journalism in action: the London Olympics [Video file]. Retrieved from https://www.youtube.com/watch?v=WyjBJzigm0w

Week 5 Lecture Pod

Summary

In this weeks lecture pod we learn why graphs are used. Graphs are used to compare data but if done poorly can give off the wrong idea such as bubble graphs as shown below. The reason bubble charts are not that useful is because they are round and we are bad at perceiving areas.


Waterson, S. (2016). Data Presentation Styles: Why use charts. Retrieved from https://vimeo.com/177306425

A better chart can be seen using squares instead as it easier to understand.

Waterson, S. (2016). Data Presentation Styles: Why use charts. Retrieved from https://vimeo.com/177306425

There are different types of graphs which include:

  • Bar graphs
  • Line charts/graphs
  • Pie graphs

Reflection

What I got out of the lecture was that when making graphs, you have to think more about how your audience who is looking at them will perceive them so it doesn’t cause a misunderstanding and it doesn’t have to be overly designed as it can also make it harder to understand.

Design a site like this with WordPress.com
Get started