Software and research: the Institute's Blog

Research Data Visualisation WorkshopBy Raniere Silva, Community Officer, Olivia Guest, University of Oxford, Vincent Knight,Cardiff University, Christina Bergmann, Ecole Normale Supérieure.

The Institute’s Research Data Visualisation Workshop took place on the 28th of July 2016 at the University of Manchester. Raniere Silva’s warm welcome was followed by Prof. Jessie Kennedy’s, from the Institute for Informatics and Digital Innovation at Edinburgh Napier University, keynote talk. Jessie spoke about the miscommunication of data due to poor visualisation techniques and how to avoid it. With over 50 attendees, the workshop provided an environment for learning and sharing. In the following sections, we will cover the events that took place during the workshop.

The Keynote

RDVW keynote

The Research Data Visualisation keynote talk was titled: ‘…

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BW1.jpgDr Becca Wilson, Software Sustainability Institute Fellow, Research Fellow, Data 2 Knowledge Research Group, University of Bristol

I attended the 2016 UseR conference at Stanford University 27th–30th June 2016. This year’s UseR Conference was of particular importance as it coincided with the 40th anniversary of the S statistical programming language (the precursor to R) and the 75th birthday of Professor John Chambers—a co-creator of S.  The conference was highly attended, with around 900 registered delegates split 50:50 across academia and industry.  Those unable to attend could follow #useR2016 on twitter and watch the stream from keynote talks live, all talks were recorded and are available online.

The opening keynote Forty years of S by Rick Becker, co-creator of S at Bell Labs in the 1970’s, was a nostalgic look back at the origins of the ‘S’ statistical language. Rick highlighted how far analytic processing has come—when in the 1970s batch computing was done via punch cards, processing for a regression analysis took two hours and then you had to wade through pages of print out to identify the solution. Ultimately R was released as an open source alternative to the licensed S, with much of its functionality retained from S including the use…

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recipy.jpg By Mike Jackson, Software Architect

A major challenge to reproducibility in computational science is the effort that is required to keep track of provenance and to make research that relies upon code more reproducible. recipy provides an almost effortless way to track provenance in Python. I am working with recipy’s developers—Software Sustainability Institute fellow Robin Wilson and Janneke van der Zwaan of Geography and Environment at the University of Southampton—to develop an automated test suite for recipy as a precursor to expanding the development of recipy and promoting recipy more widely.

recipy is an open source Python module package hosted on GitHub and released under the open source Apache License Version 2.0. It is available via this repository or as a Python package that can be installed via Python’s pip package manager. Once a researcher has installed recipy, all they have to do is add “import recipy” at the top of their Python scripts, and all of…

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A word cloud of the software used in researchBy Simon Hettrick, Deputy Director.

Over the last couple of years, we’ve had occasion to ask people about the software they use in their research. We’re about to start a long-running survey to collect this information properly, but I thought it might be fun to take a rough look at the data we’ve collected from a few different surveys.

It would be easy to survey people if there existed a super-list of all possible research software from which people could choose. But no such list exists. This raises the question of how many different types of software do we expect to see in research? Hundreds, thousands, more? The lack of this list is rather annoying, because it means we have to collect freeform text rather than ask people to choose from a drop-down list. Free-form text is the bane of anyone who collects survey data, because it takes so much effort to clean. It is truly amazing how many different ways people can find to say the same thing!

I collected together five of our surveys from 2014 to 2016, which relates to 1261 survey participants. From these, we collected 2958 different responses to the question “What software do you use in your research?”, but after a few hours of fairly laborious data cleaning (using Open Refine to make things easier) these were boiled…

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Cloud computing proposals wanted for Internet of Things research

By Kenji Takeda, Microsoft Research

We are in the midst of an invisible revolution with the promise of ubiquitous and pervasive computing; not a dream, but a newly emerging reality. The nexus of cheap and capable devices, connectivity and cloud computing is rapidly giving shape to the Internet of Things (IoT). Microsoft is delighted to offer cloud computing resources to IoT researchers around the world through a special Azure for Research IoT call for proposals — next deadline is 15th August 2016.

“To maximise the economic and societal benefits of IoT, Social and Physical Scientists, working together, must anticipate and remove barriers to adoption. It also raises the bar on addressing 21st century technological challenges using innovative, collaborative and interdisciplinary research methods. IoT works alongside technologies like cloud analytics, such as Microsoft’s Azure platform, to revolutionise the application of IoT data streams,” explains Professor Jeremy Watson, University College London, who leads the PETRAS Research Hub, launched earlier this year with the aim of developing and deploying a safe and secure IoT.

The Azure IoT Suite provides an easy-to-use platform to connect devices to the cloud, allowing…

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