Individual Portfolio - John Burn-Murdoch

Individual Portfolio - John Burn-Murdoch

Organisation: Financial Times (United Kingdom)

Publication Date: 04/10/2016

Applicant(s)

Size of team/newsroom:small

Description

As a senior data-visualisation journalist at the Financial Times I have worked on a number of solo projects over the last year across a range of subject matter: from climate change to government spending cuts, via global energy markets and a wide range of sports including football, cricket, motorsport, tennis and athletics. In these projects I have put into action a wide range of journalistic, analytical and design skills: generating ideas, scraping data, cleaning and analysing it, writing the story and producing a mix of static, animated and interactive visualisations. The following are ten examples of my work to be considered for the Individual Portfolio category. In each case I was responsible for all elements of the story unless otherwise stated. 1) Explore the changing tides of European footballing power http://blogs.ft.com/ftdata/2016/03/28/football-premier-league-decline-la-liga/ 2) Climate Change Calculator http://ig.ft.com/sites/climate-change-calculator/ -- I designed and built the interactive graphic, but was not involved in writing the accompanying story 3) Djokovic’s 2015 was the greatest ever men's tennis season http://ig.ft.com/sites/novak-djokovic-the-best-tennis-season-ever/ 4) Austerity State: how has your council’s budget changed? http://ig.ft.com/sites/2015/local-cuts-checker/ -- I designed and built the interactive tool, but all data was gathered by a colleague 5) The stain of doping on athletics http://blogs.ft.com/ftdata/2015/11/16/doping-in-athletics/ 6) The fastest and longest goalscoring streaks in world football http://blogs.ft.com/ftdata/2015/12/07/fastest-longest-goalscoring-streaks-world-football/ (with accompanying video https://www.youtube.com/watch?v=UjfGOiZve9A) 7) Who are the best ever Formula One drivers? http://ig.ft.com/sites/the-best-f1-drivers-ever/ 8) The fastest men in the world http://ig.ft.com/sites/2015/the-fastest-men-in-the-world/ 9) Oil and gas: Debt fears flare up https://next.ft.com/content/d48b1922-eadd-11e5-bb79-2303682345c8 -- I was responsible for the graphics only 10) Virat Kohli’s T20 international batting is simply outstanding http://blogs.ft.com/ftdata/2016/03/31/virat-kohli-best-twenty20-batsman/

What makes this project innovative? What was its impact?

In producing more than 60 data- and visual-led stories over the past year, I have had to develop a wide range of tools to speed up the processes with which I find, clean, analyse and visualise data. To that end I have written more than 50 different web scraping scripts in the last year, allowing me to develop large and rich datasets around certain topics, often combining multiple different sources to create richer datasets than those available anywhere else. This innovation allows me to spend the majority of my time writing stories and crafting visuals, instead of spending hours on the data-gathering phase. I have also implemented new technologies in the production of graphics and interactive tools. For my piece on Novak Djokovic's outstanding 2015 season (http://ig.ft.com/sites/novak-djokovic-the-best-tennis-season-ever/), I developed my own scroll-driven-animation functionality, allowing users to move seamlessly and effortlessly through a series of charts. I also dealt wth the difficulties mobile browsers have in dealing with scroll-driven animations by presenting a 'step through' alternative of the desktop graphic for users on mobile devices. Elsewhere I have been a heavy user of Adam Pearce's new 'Swoopy Drag' plug-in for d3.js, allowing me to add carefully crafted annotations to my graphics, highlighting interesting points or core themes. I have also extended the plug-in to allow me to programatically annotate specific charts in arrays of small multiples (e.g: http://blogs.ft.com/ftdata/2016/04/10/is-the-masters-golf-won-on-the-back-nine/). In the government spending cuts piece, I wrote a script to automatically ask for the user's location and serve up a series of charts specific to spending cuts in their local area. Finally, I have used animation to create social-media-only versions of many of my graphics (e.g: https://twitter.com/jburnmurdoch/status/714500467657740290) to promote the more detailed static and interactive iterations.

Technologies used for this project:

For scraping data I have used the R statistical programming language and phantom.js To clean and analyse data I have used R To visualise and animate data I have used d3.js, R and pure javascript

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