collage_fellowsphotos_landingpage.jpgThe Software Sustainability Institute is very pleased to announce that “Raising the status of software in research: A survey-based evaluation of the Software Sustainability Institute Fellowship Programme” by Shoaib Sufi and Caroline Jay is now available as a PeerJ Preprint at

We have been running the Software Sustainability Institute Fellowship Programme since 2012. Up to now, we have recruited 112 Fellows.

In 2017, the Institute ran a research survey asking Fellows from the 2012–2016 cohorts  to report the effect that the programme has had on them, their institutions, their research domains and their careers. The results show that the fellowship plays a wide-ranging role in supporting communities of best practice and skills transfer, and that a significant benefit is the way it has raised the profile of software in research, and those people who develop and advocate for it. Highlights from the survey include:

96% of Fellows say they have benefitted from being a Fellow.

72% of Fellows say being a Fellow has helped advance their careers.


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8572856136_f746c2dfa3_o.jpgBy Cyril Pernet, University of Edinburgh.

This blog post was first published at

Feedback from reproducible science workshops

Only a minority of scientists think there is no 'reproducibility crisis' (Nature 533, 452–454), yet many are not engaging in reproducible practices. Results from a recent survey among psychology researchers suggest that discussion and education about the utility and feasibility of practices like data sharing are needed if we want the community to adopt those standards. In short, people don't know those practices and don't want to journey there.

One of the things I did during my Software Sustainability Institute Fellowship, was to run a series of small group workshops for post-graduate students and principal investigators, on data sharing, code sharing, and good practices around code. This took place the last of September 2018 in Oxford the 25th, Birmingham the 27th and Glasgow the 29th, and in…

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By Peter Murray-Rust, ContentMine Ltd; Rachel Spicer, EMBL-EBI, University of Cambridge; Josh Heimbach InterMine, University of Cambridge; Yo Yehudi, InterMine, University of Cambridge and Code is Science; Naomi Penfold, eLife

Image to the right: Bike thefts in Cambridge over 2017. Rendered by Rachel Spicer, using R (ggmap) + Google Maps + Open police data

Open Data Day (ODD) is an international event that runs on the first Saturday of March, started in 2010 and supported by Open Knowledge International. It aims to raise the profile of all types of open data, from government to research.

Creating our own ODD

The Open Data Day organiser’s guide recommended picking a focus. We didn’t have a huge amount of time to organise, and we knew this wasn’t going to be a large event but mainly a motivation to meet some busy…

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16121281031_5b58dfc131_z.jpgBy Laura Fortunato, University of Oxford

Reproducible Research Oxford is a project based at the University of Oxford, launched in October 2016. The project aims to lay the groundwork for a culture of research reproducibility across the University, focusing on training in the effective use of computational tools in research. These tools are widely used in some disciplines, and they can enable researchers to easily track the process leading from data to results, so that it is fully reproducible. However, researchers often lack the opportunities, incentives and confidence to make best use of these tools.

As part of the project, we have set up a partnership between the University and Software and Data Carpentry, non-profit volunteer organisations focused on teaching researchers across disciplines the computing and data skills they need for effective and reproducible research. Since the start of the project, we have ran four Software Carpentry workshops, one Data Carpentry workshop—the first to be held in Oxford!—and we have hosted the first Oxford-based Software/Data Carpentry instructor training. So far, we have provided training to upwards of 100 learners from across the University who attended our workshops, in addition…

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8419988105_367cb3d1f8_z.jpgBy 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?

First thing's's good to meet the researchers you'll be working with as quickly as possible. Most researchers are excited about their research; this enthusiasm is infectious. Ask questions. Be interested.

To get a basic grounding in your new area, YouTube is an invaluable source of quick bursts of domain knowledge for both a general subject area or the detailed specifics and intricacies of a niche within that subject area. Video tutorials can take many forms but the useful ones to look for are short explainers on concepts or tooling, as well as longer form recordings of things like lectures, workshops and panel discussions. YouTube has become a primary method of user training materials for large software vendors, there are thousands of video tutorials on how to use tools or perform specific actions for things like Jupyter Notebooks, Excel and Adobe Photoshop. If there are large commonly used pieces of software in the domain you’re trying to learn, there may be similar videos available to help get started with that software platform.

It can be useful to ask for a background reading list from the researchers you're working with. Selectively…

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8236647979_efbfd1d409_z.jpgBy 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)

In our institutions, we employ multidisciplinary research staff who work with colleagues across many research fields to use and create software to understand and exploit research data. These researchers collaborate with others across the academy to create software and models to understand, predict and classify data not just as a service to advance the research of others, but also as scholars with opinions about computational research as a field, making supportive interventions to advance the practice of science.

Some of us use the term "data scientist" to refer to our team members, in others we use "research software engineer" (RSE), and in some both. Where both terms are used, the difference seems to be that data scientists in an academic context focus more on using software to understand data, while research software engineers more often make software libraries for others to use. However, in some places, one or other term is used to cover both, according to local tradition.

What we have in common

Regardless of job title, we hold in common many of the skills involved and the goal of driving the use of open and reproducible…

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253580496_491d04cc53_z.jpgBy 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)

Data and software have enmeshed themselves in the academic world, and are a growing force in most academic disciplines (many of which are not traditionally seen as "data-intensive"). Many universities wish to improve their ability to create software tools, enable efficient data-intensive collaborations, and spread the use of "data science" methods in the academic community.

The fundamentally cross-disciplinary nature of such activities has led to a common model: the creation of institutes or organisations not bound to a particular department or discipline, focusing on the skills and tools that are common across the academic world. However, creating institutes with a cross-university mandate and non-standard academic practices is challenging. These organisations often do not fit into the "traditional" academic model of institutes or departments, and involve work that is not incentivised or rewarded under traditional academic metrics. To add to this challenge, the combination of quantitative and qualitative skills needed is also highly in-demand in non-academic sectors. This raises the question: how do you create such institutes so that they attract top-notch candidates, sustain themselves over time, and provide value both to members of the group as well as the broader university community?…

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The Workshop on Debugging Numerical Software will take place at the University of Bath (UK) on 4th & 5th June 2018. The goal of the workshop is to bring together research software engineers from industry and academia to talk about this important but often neglected topic. A lot of time “writing” code is actually spent hunting for (sometimes very elusive) bugs, yet there seems to be limited general advise or consensus on how to make this often arduous task easier.

Instead of concentrating on the technicalities, specific debuggers or particular programs, the workshop aims to explore common themes, discuss general strategies and share experiences. Although the focus will be on numerical software, developers from other disciplines are very welcome.

To express your interest in the workshop, please fill out this google form by Tuesday 1st May 2018.

Please note that the number of spaces is limited and filling out the form will NOT confirm your place yet. We will get in touch with you as soon as possible to confirm your attendance.

Do not make any travel or accommodation arrangement before you receive an email from the organisers confirming your attendance.

The workshop is organised by James Grant as local RSE in Bath and Eike Mueller as a new Fellow of the Software Sustainability Institute. It has been made possible through generous financial support from the Software Sustainability Institute and the I…

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The Exascale Applications and Software Conference 2018 (EASC18) will take place on 17th to 19th April 2018 in Edinburgh, Scotland, in the John McIntyre Conference Centre (JMCC). The general early-bird registration fee is £325, and early-bird student registration fee: £250. Early-bird registrations are open until the 28th March 2018.

The conference will cover diverse topics associated with applications, tools, software programming models and libraries, and other technologies necessary to exploit future exascale systems, including:

  • enabling and optimising applications for exascale;
  • developing and enhancing algorithms for exascale systems;
  • aiding the exploitation of massively parallel systems through tools, e.g. performance analysis, debugging, development environments;
  • programming models and libraries for exascale;
  • exascale runtimes and system software;
  • evaluating best practice in HPC concerning large-scale facilities and application execution;
  • novel uses of current generation and future exascale systems;
  • new hardware technologies and their exploitation to solve exascale challenges.

For full details and registration, please visit the EASC18 page.

Exascale Applications Workshop

EASC attendees are also invited to register for a free Exascale Applications Workshop on 19 April (p.m.) – 20 April (a.m.) at Pollock Halls, Edinburgh.

This workshop will focus on communication models and their use in applications. The aim is to…

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30625118805_850c6840e2_z.jpgCollaborations Workshop 2018 (CW18) will start next Monday 26th of March at The School of Mathematics, Cardiff University. We are looking forward to meeting everyone in person and have a great time. The final agenda is available at the workshop page.

To make the best of Collaborations Workshop, don't forget to sign up to present a lightning talk and to take part in the social activities.

The Software Sustainability Institute staff will be attending this event. We will aim to answer all emails but might take us while to get back to you. You can also contact us on Twitter @SoftwareSaved.

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