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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/09/recap-earl-london-2017.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>The <a rel="nofollow" href="https://earlconf.com/london/" target="_blank">fourth EARL London conference</a> took place last week, and once again it was an enjoyable and informative showcase of practical applications of R. Kudos to the team from Mango for hosting a great event featuring interesting talks and a friendly crowd. </p>
<p>As always, there were more talks on offer than I was able to attend (most of the event was in three parallel tracks), but here are a few highlights that I was able to catch:</p>
<p><strong>Jenny Bryan from RStudio</strong> gave an outstanding keynote: &quot;<a rel="nofollow" href="http://bit.ly/jenny-earl%20" target="_blank">Workflows: You Should Have One</a>&quot;. The talk was a really useful collection of good practices for data analysis with R. Note I didn't say &quot;best practices&quot; there, and that's something that resonated with me from Jenny's talk: sometimes the best practices are the ones that are &quot;good enough&quot; and don't add unnecessary complexity or fragility. Software Carpentry's &quot;<a rel="nofollow" href="http://swcarpentry.github.io/good-enough-practices-in-scientific-computing/" target="_blank">Good Enough Practices for Scientific Computing</a>&quot;is a great read that I hadn't come across before this talk.</p>
<p><strong>Rachel Kirkham from the National Audit Office</strong> uses R and Shiny to scrutinize public spending on behalf of taxpayers in the UK. (<a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_Rachel_Kirkham_-_Using_R_and_Shiny_to_automate_audit.pdf" target="_blank">View the slides here</a>.) One interesting beneficial aspect of R for this application is the ability to <em>bring R to the data</em>, thereby sidestepping regulations that forbid the data being exported from the NAO data center.</p>
<p><strong>Joy McKenney from Northumbrian Water</strong> gave a truly fascinating talk on using R to monitor and predict flows in a sewer system. (<a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_Joy%20McKenny_-_Using_R_to_monitor_sewer_network_performance.pdf" target="_blank">View the slides here</a>.) One surprising application from this talk was being able to model whether an overflowing sewer line is due to rainfall or because of a blockage in the system — a tool that can be used to detect &quot;fatbergs&quot; clogging up the system.</p>
<p><strong>Pieter Vos from Philips Research</strong> showed how they deploy applications to doctors to evaluate things like cancer risk. (<a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_Pieter_Vos_-_Getting_predictive_analytics_in_the_clinical_workflow_of_doctors.pdf" target="_blank">View the slides here</a>.) The applications call out to R to make the underlying statistical calculations.</p>
<p><strong>Joe Cheng from RStudio</strong> gave a remarkable talk on a major concept for the R language itself: &quot;promises&quot;. (<a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_Pieter_Vos_-_Getting_predictive_analytics_in_the_clinical_workflow_of_doctors.pdf" target="_blank">View the slides here</a>.) With promises, you can ask for the results of a long-running computation, but get back to the R command line instantaneously. The results will be available to you, well, when they're ready. It sounds like magic, but it's already working (in beta) with the <a rel="nofollow" href="https://github.com/rstudio/promises" target="_blank">promises package</a> and promises (pun intended) to bring more responsiveness to Shiny applications.</p>
<p><strong>Ashley Turner from Transport for London</strong> gave a talk that I was very sad I couldn't see (it conflicted with my own session), but fortunately <a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_Ashley_Turner_-_Every_journey_matters.pdf" target="_blank">the slides are available</a>. R has been used for over 2 years to model how Londoners get about via car, bus and Tube. It was used for <a rel="nofollow" href="http://www.gizmodo.co.uk/2017/09/london-underground-wifi-tracking-heres-everything-we-learned-from-tfls-official-report/" target="_blank">official report on London transportation</a>, which included some fascinating data on the routes certain commuters prefer for getting from (say) Kings Cross to Waterloo. </p>
<p><strong>Matthew Upson from the Government Digital Service</strong> reported on the ongoing program to implement a reproducible data science workflow for creating official reports. (<a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_Matthew_Upson_-_Reproducible_analysis_for_government.pdf" target="_blank">View the slides here</a>.) He says that this process has reduced production time for some official reports by 75%, and you can <a rel="nofollow" href="http://blog.revolutionanalytics.com/2017/03/uk-statistics.html" target="_blank">learn more about the program here</a>.</p>
<p>I was also informed by the organizers that my own talk on <strong>Reproducible Data Science with R</strong> (<a rel="nofollow" href="https://earlconf.com/downloads/london/presentations/EARL2017_-_London_-_David_Smith_-_Reproducible_data_science_with_R.pdf" target="_blank">slides here</a>) won the &quot;award&quot; for loudest presentation at the conference. I think the audio desk had the volume up a little too high for <a rel="nofollow" href="https://youtu.be/s3JldKoA0zw" target="_blank">this video</a>! </p>
<p>As I said, there are many more excellent talks beyond those listed above. You can explore the other talks by <a rel="nofollow" href="https://earlconf.com/london/#speakersAnchor" target="_blank">clicking here</a> and then clicking through each speaker portrait — slides, where available, are linked at the bottom of each abstract.</p>
<p>The next EARL conference will take place in <a rel="nofollow" href="https://earlconf.com/boston/" target="_blank">Boston, November 1-3</a> and promises to include even more practical applications of R. I hope to see you there!</p>
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