Introduction to Data Visualisation

Description:

Summary of Course:

This course will provide participants with an introduction to data visualisation. We will focus on making interactive charts and maps using freely available software, but will also introduce some advanced options to create visuals through coding. The course will also use R to make some charts and maps that go beyond the standard line or scatter plots academics usually use. We will use different sources of (open) data during course, focussing on health, geographic, and weather data. During the two days, we mix classroom tuition with practical exercises, giving participants the opportunity to try out the methods shown during the course. The course is aimed at academics from any discipline wanting to use these techniques either for public engagement or academic publication. We will be focussing on health and geographic census and transport data.

Although the course will involve some coding in HTML/JavaScript and R, the course material is suitable for participants who have not used or coded in these languages before.

Course Contents:

The course covers:

• Guiding principles & resources for visualising data

• How to make (interactive) charts

• How to make non-standard charts and maps with R

• Making zoomable maps

• Introduction to more advanced methods

Learning Outcomes:

By the end of the course participants will:

• Understand the basic principles of graphic design

• Be aware of different formats and tools to visualise data

• Be able to create some basic interactive charts and maps

• Know how to continue learning about data visualisation

Computer Software and Workshop:

The course will introduce participants to R-implement of the methods discussed.

Participants will need to bring their own laptops with R installed from here: https://www.r-project.org/ and Google Drive installed by creating a Google account here: https://accounts.google.com/signup

Presenter

Dr Linda Wijlaars is research associate in statistics at the Institute of Child Health and part of the Children’s Policy Research Unit. Her research interests are in the use of administrative databases, including hospital and primary care databases for child health and mental health research. Her particular research focus is on the epidemiology of healthcare use in childhood and across the transition to adulthood. She has an interest in data visualisation and holds a public engagement grant to explore this further. She holds a PhD in primary care epidemiology from University College London.

Other speakers TBC

Target Audience:

Researchers at all levels in academia, government and the private sector who are interested in using (interactive) data visualisation in research or public engagement.

Course Programme (subject to change):

Day 1

09.00-10.00 Registration and computer set up (with coffee)

10.00-10.30 Welcome and introductions

10.30-11.30 Lecture 1: General principles and resources

Intro session, explain general principles of data visualisation (how/why), introduce some resources that we will use throughout the course

11.30-12.00 Practical 1: Setting up a webpage

How to set up a web page / quick intro to HTML – necessary for interactive charts/maps

12.00-12.30 Demo 1: Making an interactive chart

Demo on how to make a simple interactive chart using Google Charts – intro to Google spreadsheets, as we will be using these in several practicals

Will also show less common graphs you can make with Google Charts, such as Hans Rosling’s moving bubble chart

12.30 -13.30 Lunch

13.30-14.00 Practical 2: Making an interactive chart

Practical of demo 1 – also, how to put resulting chart in webpage. We will make a chart on papers that use administrative data (how many per year, do they mention they use admin data in the title?). We will get the data from PubMed, format it, and make an interactive graph.

14.00-14.30 Lecture 2: Intro to maps: projections and colour schemes

Maps are a special type of chart, this session will introduce some topics to take into account, such as projections

Also: some guides on how to pick colours that make your map readable

14.30-15.00 Practical 3: Making a zoomable dot-map

How to make dot-map: practical will map data on English GP practices and link this to open data sources, such as the GP satisfaction survey or GP workforce census.

Session will also introduce geocoding location data.

We will use Google Fusion tables to make the maps.

15.00-15.30 Coffee

15.30-16.00 Lecture 3: Map example: DataShine (James Cheshire or Oliver O’Brien)

Example of more advanced map that shows census data at postcode level

16.00-16.30 Practical 3 cont’d - See above

16.30-17.00 Q&A - Optional

Day 2

10.00-10.30 Lecture 4: Infographics

Or: risk communication with visuals

Session on infographics using easel.ly

Something like Prof David Spiegelhalter’s work on using visual representations to explain things like 10-year risk of heart disease, if we can find someone to talk on this

10.30-12.30 Practical 5: Charts and maps with R

Session on how to make non-standard R charts and small multiple maps

Examples I have now are making a chart of the prices Damien Hirst artworks sold at (infection including small pictures of the actual artwork), a quilt plot of injecting drug users by hepatitis C, and a collection of maps showing how US droughts develop over several years – can perhaps replace the first one with something more relevant?

The US maps require linking to geographic shape data, KML files, which will be introduced in this session (US maps are a bit easier to introduce shapes with, as lots of states are just rectangles)

12.30-13.30 Lunch

13.30-14.30 Practical 6: Zoomable Choropleth maps

In the previous Google mapping tutorial, we made a dot-map, now we will make a shaded map or choropleth. We can map health data by UK region or CCG in this session, or proportion of cycling residents per ward, or use World Bank data (or maybe something with election data by then?)

14.30-14.45 Coffee

14.45-15.45 Demo 2: Advanced methods: intro to D3

Finally, we will give a quick introduction to D3, a Javascript library that allows users to link data to shapes within webpages. It’s very powerful and

15.45-16.30 Discussion and feedback

Pre-requisites:

Some programming experience in R and HTML/JavaScript will be helpful but is not a pre-requisite.

Course Materials:

Participants will receive written course notes.

Course places are limited and registration by 9 May 2016 is strongly recommended

Course No. ADRCE-Training021 Wijlaars

This course is organised by ADRC-E/University of Southampton

Cost:

The fee per day is:
1. £30 - For UK registered postgraduate students
2. £60 - For staff at UK academic institutions, Research Council UK funded researchers, UK public sector staff and staff at UK registered charity organisations
3. Free place for ADRC/ADRN/ADS staff
4. £220 - For all other participants
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.

Website and registration:

Region:

Greater London

Keywords:

Visual Methods, Spatial Data Analysis, Quantitative Software, Alternative Methods of Dissemination, Use of Administrative Sources

Related publications and presentations from our eprints archive:

Visual Methods
Spatial Data Analysis
Quantitative Software
Alternative Methods of Dissemination

Back to the training database