Craig MacLachlan

Fellows RSE conferenceBy Craig MacLachlan, Met Office; Mark Stillwell, Cisco Meraki; Caroline Jay, University of Manchester.

Software has been an important part of research for several decades, and ensuring that research software is of high quality is essential to ensuring the accuracy of scientific results. Unfortunately, many people who work on source code used on research projects have lost themselves in the gap between IT professional and researcher, lacking a distinct professional identity, at least until relatively recently. It was four years ago that the term Research Software Engineer was born at the Collaborations Workshop 2012. In this short time, many researchers have heard this term and experienced an epiphany: they found an identity.

Now they have more than an identity; they have a community. On Thursday 15 September and Friday 16 September 2016, the first ever Research Software Engineer Conference was held in Manchester at the Museum of Science and Industry. More than two hundred people attended from across the globe. Not all of the attendees were Research Software Engineers; some came to learn about building communities for analogous roles…

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By Oliva Guest, University of Oxford, Robin Wilson, University of Southampton, Martin Jones, Python for biologists and Craig MacLachlan, Met Office Hadley Centre.

A speed blog from the Collaborations Workshop 2016 (CW16).

Why are sustainable software practices difficult to teach?

Programming is a difficult thing to learn for students who have not been exposed to it before. However, for general programming there are at least some factors that help to make it easier. Feedback is generally very rapid; after writing and running a piece of code, students can see the result straight away. This isn't true for e.g. automated testing; the payoff for writing a test suite comes long after the fact, when it helps to catch a bug. The same goes for version control — until students have encountered one of the problems that version control is designed to solve, it seems like an unnecessary extra step in development.

Increasingly, programming is becoming a necessary tool for students who don't have a computer science background (represented in this discussion group: meteorologists, biologists, psychologists and physicists). Students coming to programming for the first time are often lacking in computer…

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A fast speed blog from the Fellows 2016 inaugural meeting.

by Craig MacLachlan (Met Office), Terhi Nurmikko-Fuller (University of Oxford), David Pérez-Suárez (University College London), Heather Ford (University of Leeds)

How do researchers in an interdisciplinary environment, with different skills and experiences pick collaborative tools that best fit their needs? There are literally hundred's of choices[1], thus we set out a list of 5 considerations to help you.


Documentation. High quality documentation and tutorials can really improve user experience and buy-in from users. Nobody wants to use a tool that is poorly documented or spend time trawling for answers to problems.

Data restrictions and security. Groups or institutes involved in the collaboration may have existing data storage rules, for example prohibiting data storage on cloud platforms. The sensitivity of the data may also…

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Manager of Monthly to Decadal Operational Systems, Met Office Hadley Centre


My aim is to predict the climate for the months ahead, it’s a very challenging area of weather forecasting. I’m interested in writing robust and high quality software and encouraging others to do the same. I work with people from scientific and technological backgrounds on both research and operational projects. 

My work

I lead a team of software engineers and scientists responsible for the monthly to seasonal forecast system at the Met Office. We try to predict the climate for the weeks and months ahead.
My team and I tackle a wide range of activities, from model development to data dissemination. The key part of our work sits right in the middle: an ensemble prediction system called GloSea5. This system is a complicated workflow including numerical simulations and data processing and it runs on our supercomputer. This means we have to be experts on a variety of software and hardware platforms. The system runs every day of the year, making predictions of the future climate. Our system is part of the operational work the Met Office does, this means it needs to be robust and reliable.
We help to improve and evaluate the latest Met Office numerical models used for weather and climate prediction. Our forecast system has been designed so that we can include these easily in our operational forecasting work. This means we can use the best available model to make our monthly and…
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