Data science

By Alex Morley, Institute Fellow & Mozilla Fellow It’s not a new concept. But when people talk to me about improving the scientific process it really resonates with me when they talk about feedback loops. This framework is broad enough to encompass most ways in which we can think about improving science, but also makes explicit what actions need to be taken, and where bottlenecks are likely to arise. Here are a few examples of how people have used these cycles to make/explain progress/problems in scientific processes.
By Danny Wong, NIAA-HSRC & UCL-DAHR. I’ve recently had the great fortune of publishing a paper which had significant interest from the general news media. It even managed to get picked up by the BBC, The Guardian and all the major newspapers in the UK! As per usual, I’ve shared the source code for the analysis publicly, this time electing to serve it up on GitHub as a repository. I have included the manuscript as an .Rmd file, and the wrangling data wrangling and modelling code as a chunk located at the start of the .Rmd file.

By Matt Archer, Paul Brown, Stephen Dowsland, David Mawdsley, Amy Krause, Mark Turner (order is alphabetical).

So… you’ve just started on an exciting new data science project, but you know nothing about the domain you’re working on. Besides briefly panicking, how do you get up to speed on the area you’re working on?

By Matthew Archer, Stephen Dowsland, Rosa Filgueira, R. Stuart Geiger, Alejandra Gonzalez-Beltran, Robert Haines, James Hetherington, Christopher Holdgraf, Sanaz Jabbari Bayandor, David Mawdsley, Heiko Mueller, Tom Redfern, Martin O'Reilly, Valentina Staneva, Mark Turner, Jake VanderPlas, Kirstie Whitaker (authors in alphabetical order)

By R. Stuart Geiger, Alejandra Gonzalez-Beltran, Robert Haines, James Hetherington, Chris Holdgraf, Heiko Mueller, Martin O'Reilly, Tomas Petricek, Jake VanderPlas (authors in alphabetical order)

Steve Harris' article "Data Science for Docs" was recently published as the guest editorial in Bulletin, July 2017, the magazine for members of The Royal College of Anaesthetists, which reaches every anaesthetist in the UK (it's the largest hospital speciality). 

You can find the article on pages 12 and 13 of Bulletin, Issue 104.

By Raniere Silva, Software Sustainability Institute.

By Steve Harris, University College London Hospital, and Software Sustainability Institute Fellow.

This article was first published at Data Science Breakfast Club.

By Raniere Silva, Community Officer, Software Sustainability Institute.

With more than 48,000 job listings for data scientists on LinkedIn right now, but with fewer than 20,000 people registered with that title, the growing skills shortage in big data analytics has never been more evident.

In an increasingly digital world, computing and data interpretation have become fundamental to our way of life, from the way we interact with the world and develop new ideas, to the way we conduct research and do business across all sectors.

To enhance early career researchers’ job prospects and upskill high-tech workforces, the Hartree Centre Summer Schools…

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