Introduction to Data Visualisation
|University of Southampton/ADRC-E|
Dr Linda Wijlaars
16/05/2016 - 17/05/2016
Farr Institute, 222 Euston Road, London
View in Google Maps (NW1 2DA)
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.
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
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
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
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):
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.
15.30-16.00 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
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)
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?)
14.45-15.45 Demo 2: Advanced methods: intro to D3
15.45-16.30 Discussion and feedback
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
Intermediate (some prior knowledge)
The fee per day is:
Website and registration
Visual Methods, Spatial Data Analysis, Quantitative Software, Alternative Methods of Dissemination, Use of Administrative Sources
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