Within the Data Science Institute, we aim to improve research's reproducibility and replicability by improving the reusability, sustainability and quality of research software developed across the University. We are currently funded by the N8CIR and work closely with our partner institutions
Research Software Engineering combines academic research with good software engineering principles.
Combining good software engineering principles with high academic standards allows us to create the best quality open, reproducible, and replicable research. However, a lack of appreciation for software as a research output results in software being a secondary concern. This leads to lower quality code that is not reproducible, or even shareable.
Research Software Engineering and Research Software Engineers (RSEs) combine the skills needed, which allows them to work with researchers to develop software and research of the highest qualities.
We are no longer able to offer in-person training. Many of the resources we use can be used as self-teaching guides and links to them are provided below.
Introduction to Linux - An introductory course on using Linux and the command line.
Version Control with Git - Using version control to track (and undo) changes to your code with Git.
Plotting and Programming in Python - How to load in data, analyse, and plot it in Python.
R for Reproducible Scientific Analysis - How to load in data, analyse, and plot it in R.
Automation and Make - How to automate tasks using Make
Additionally the N8 CIR offers several courses and some online resources here: N8 CIR - Training and Events
Various types of infrastructure are available to researchers at Lancaster to support them in computationally intensive research or to meet their data needs.
The High-End Computing (HEC) Cluster is a centrally-run service to support researchers and research students at Lancaster who require high-performance and high-throughput computing. This includes computing workloads with requirements that can’t be met by the Interactive Unix Service (IUS), desktop PCs or Virtual Desktops (mydesktop and mylab).
The Interactive UNIX Service (IUS) provides a UNIX facility in the areas of study, research, development, and teaching for researchers whose needs are not best served by the University's Microsoft Windows-based services.
The research filestore is available for projects with specific requirements for large amounts of local, high speed storage.
A SafePod is a standardised safe setting that provides the necessary security for a researcher to access sensitive datasets from participating Data Centres across the UK. The SafePod at Lancaster University is part of the SafePod Network (SPN). A total of 25 SafePods will make up the SafePod Network, spread geographically across the UK. This network will remove the need for long distance travel to a dedicated safe setting provided by a data centre.
Bede is the N8 GPU-accelerated Supercomputer. It is housed at Durham University and accessible by any members of the N8 - which includes Lancaster University.
Many researchers use software heavily as part of their research, and many of the problems we need to solve with software can be common across disciplines. By bringing researchers together we can create a collaborative community to share tools and libraries that we use and provide support in writing code.
To do this we have a Microsoft Teams group where researchers can ask for help and advice, or post useful tools and information related to research software. Follow this link to join the Research Software Network Teams Group.
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