RSE Case Studies

Research Software Engineers combine expertise in programming with an intricate understanding of academic research.

These case studies offer an insight in to how RSEs work with researchers to overcome challenges and accelerate discovery. If you are a researcher and would like to discuss how your local RSE group could support and accelerate your work please visit:

Digital Health

Chris Jewell

Digital Health - Lancaster University
Dr Chris Jewell is a computational epidemiologist. Much of his work is based on using epidemic models to predict the spread of infectious diseases amongst human, animal or plant populations. His current project, GEM: Generalised Epidemic Modelling, is intended to bridge a skills gap between epidemiology, statistics and computationally intensive statistics.

It will make it easier for epidemiologists to access cutting edge statistical tools for modelling epidemics during new disease outbreaks. Methods developers will also benefit as it will be easier and quicker to integrate new statistical innovations and approaches into the investigation of those outbreaks.

  GEM: Generalised Epidemic Modelling

Helena Tendedez

Digital Health - Lancaster University
Respire is a data dashboard that brings together data about patients who have about Chronic Obstructive Pulmonary Disorder from two collaborating NHS trusts. The information is presented to clinicians in a way that ensures that care decisions are based on reliable data, saving time and improving patient care. In this project RSEs helped to develop visual prototypes of the app to help increase user engagement with the project.

  Respire Dashboard for COPD

Richard Williams

Digital Health - University of Manchester is a web app that enables researchers to construct sets of these clinical codes for their research. Once created they can be saved, validated and reused by other researchers.

  GetSet - Clinical Codes for Research

Peter-John Mäntylä Noble

Digital Health - University of Liverpool
SAVSNET collects clinical notes and questionnaire data from UK veterinary practices alongside results from the UK’s larger veterinary laboratories.

This data is analysed to help monitor disease trends, identify at risk animal populations, provide data to academics, improve public awareness of small animal diseases and provide a route to clinical benchmarking. In this project RSEs help to manage the software and server architecture required for data collection and added a data dashboard to make it easier to analyse the results.

  Small Animal Veterinary Surveillance Network (SAVSNET)

Digital Humanities

Mark Turner and Stephen Downsland

Digital Humanities - Newcastle University

Caring for pre-historic rock art can be incredibly challenging as the rocks are often in remote places.

In this project RSEs developed a mobile app that enabled the general public and and specialists to provide photographs and condition reports about the rocks. These reports could then be used by those responsible for caring for the rocks to ensure their conservation and preservation.

  Condition and Risk Assessment Portal (CARE)

Susan Fitzmaurice and Seth Mell

Digital Humanities - University of Sheffield
Professor Susan Fitzmaurice and Dr. Seth Mell's project is called 'The Linguistic DNA'. It has analysed more than 1 billion words from 60,000 printed English documents from the 16th and 17th centuries in the search for patterns of words and meaning.

In this project the RSEs developed a bespoke computational linguistics tool to perform computational tasks; something that was impossible to achieve with existing software.

  The Linguistic DNA (LDNA)

Michael Richardson and Kate Court

Digital Humanities - Newcastle University
Dr Michael Richardson's project was a proof of concept application to create a mobile web app to help young dads connect with their children. This pilot project will provide evidence to support future funding bids.

  Using 3D Augmented Reality for Virtual Storytelling

Dan Birks and Alex Coleman

Digital Humanities - University of Leeds

This project aimed to build a proof-of-concept that would utilise data collected by public sector agencies to model and forecast rates of crime on a daily basis within a specific geographic area.

  Demand and Supply Modelling for Modern Policing

General Case Studies

Ed Ruck-Keene

Durham University
Since the summer of 2017 Advanced Research Computing at Durham University have been working to create a central research software engineering team to support researchers across the institution.

In this case study Ed Ruck-Keene talks about the process of undertaking this work and introduces the RSEs who are already part of the team.

  Growth of an RSE Team in Durham

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