Data Visualisation & Infographics


  • M: am –  Critiquing and reviewing advanced video assignments

  • M: pm Introduction to Infographics 1 & In-Class Assignment

  • T: am Introduction to Infographics 2 & In-Class Assignment 

  • T: pm Introduction to Infographics 2 Lecture by Wei Meng

  • T: pm Setting Assignment + Questions + Resources

  • T: eve Theory Lecture:

  • Wed – Fri. Assignment, Edit, and Upload Assignment, Reading & Self Study

Assignment 1 – Deadline: SUNDAY 18th NOVEMBER at midnight.

Create a single journalistic Data Visualization or a series of Data Visualisations that effectively communicate a clear message to your audience using key data and/or information about one of the set topics: CLIMATE CHANGE or SINGLES DAY. Sometimes data visualizations supplement or enhance a multimedia story, sometimes they can tell an entire story themselves. For your assignment this week — you should think about telling a complete story with your graphics, in other words, data visualization should be the central media – whether animated or static. Very often, graphics need some context, so don’t hesitate to include a paragraph or two of text or a voiceover to an animation if you think suitable, however, there is no requirement for text. So it’s your choice. Please make an assignment page on your digital platform and embed your graphic(s) as suitable.

Your target publication is the South China Morning Post. You will create a data visualization(s) for their Infographics Section.

This week there are no time or length limits because data visualizations are so varied – it could take hours to create something quite simple, or you could knock up something quite complex in a short time, depending on the data, research, and tools involved. Therefore this week we simply ask that you spend 2 x 6-8 hour days working on your assignment and do the best you can in the given time.

You must plan your time to include research time for reading and researching the issue, locating reliable data sources and verifying data.

There are a number of tools and methods you can use. We are looking for quality rather than quality – well-sourced data and a relevant, effective and visualization. Pick your topic and explore some data and tools demonstrated in class – and within these reading notes – to select the best data, tools, and method. You will need to source credible data and convert it to an appropriate chart or graphic, please consider good design principles and color to make your visualizations clear and engaging. You may if needed add a sentence or paragraph of context.

Your Data Visualisation MUST have the following: a title, subtitle, clear and visualized message or story, visible statistics and referenced, attributed source(s). Embed your work on your digital platform. (Do not posts links).

Session Preparation – Pre-reading / watching – You do not need to do any pre-reading for this week’s Practical Module, as the video week is quite a challenging week, leaving you little time for pre-reading. You will, however, need to review the class notes and explore the tools demonstrated in class and in the notes after class.

Assignment Guidelines – First off, spend a few hours playing with 3 or 4 of the tools in class. Then think about the story you want to tell. Research, (this should take 3 to 4 hours minimum). Find credible data and think about the best way to visualize it. Make sure you choose a suitable form – sometimes simple is best! Spend the second day visualizing the data and perfecting things.

Be sure to look at a number of the SCMP Infographic stories. You could also try the Guardian’s Datablog, most news organizations have a dedicated space for data journalism these days, however, you are most likely to see data visualizations as integrated parts of general digital reporting. Do you want to see some Chinese examples of data visualization – see the links here: Data journalism in China

Infographics & Data Visualisation – NOTE: This is not a comprehensive software tutorial, but we will take a peek at some of the simple tools and software you might use to create some simple data visualizationsns. More importantly, we’ll think about when, why and how you might incorporate and visualize data to better tell your story. There are a ton of simple online tools you can try out on this page along with lot’s of inspirations, so read through and try some out if you want more options than those given in class.

What is Data Visualization? – It’s information encoded and interpreted into charts, maps and illustrations to help communication, analysis, and understanding. Visualizations allow people to explore and comprehend datasets, geographies, demographics and more. Data visualization isn’t just an act of journalism, but also of design. Fundamentals of journalism apply: graphics should be clear, concise, appealing and above all accurate. If you read through these notes and watch some of the videos and the examples, you’ll have a good grounding in data visualization as well as plenty of inspiration and ideas to try out your own.

3. Maps

6. Plugins

Plugins are another option too. I inserted some Free Infographics for Final Cut Pro X – from Data Pop into this explainer video.

7. Illustrated Graphics

This isn’t data visualisation, but we didn’t want to skip the way that illustration and journalism can be combined. See this example from Carrie Ching

News organizations using infographics, data visualization and data-driven journalism

  • Odyssey.js — — I am yet to try this, it doesn’t look as easy as some others, but also not rocket science — would be a great one to try out over Christmas holidays!
  • You can’t get more comprehensive than the journalist’s toolbox – It’s a long long list but great to poke around and see what takes your interest.
  • Here’s another collection of resources from charting and graphing to data handling, mapping, and even programming tools. resources for
  • If you want to take things further I’d recommend this online book: Welcome — The Data Journalism Handbook Using data to improve the

Infographics & Data Visualisation gone bad part 2

  • If numbers are used poorly they do more harm than good — creating more confusion than clarity. There has been an explosion of data journalism and while much of it is good there has also been some very poor examples too. We’ll view some examples of good and bad practice in class, but here are some to get you going by ALBERTO CAIRO, a fantastic data journalist. To do data-driven journalism well, you need solid math and statistics knowledge. If data-driven journalism really appeals to you, and want to try a data-driven story — please do negotiate with us and we’ll try to support you. Bear in mind few journalism schools teach comprehensive data journalism, and it is a skill that’s highly in demand – so you’ll be investing in learning by doing. 
  • Here is a brilliant podcast about statistics that went viral in 2013 — the stats reported that almost a quarter of men in some Asian countries admit rape — figures from the UN and published in the Lancet, should mean highly reliable statistics, but things still go wrong. Are the numbers of rapists really this high? Tim Harford and Ruth Alexander look into the detail of the study. And, “Africa has a drinking problem” — so says Time Magazine. More or Less discovers a more mixed picture. This programme was first broadcast on the BBC World Service.

Learning Outcomes

  • *NOTE, this class is not about teaching you the intricacies of each and every data tool. That’s something students will need to explore independently. Rather we guide you to a variety of the ones we think are useful and easy to grasp with some practice. You will need to use the google to find tutorials.