CloudStor’s SWAN (Service for Web-based Analysis), a service for running data analysis in CloudStor, has recently been updated to add new features.

Using only a web browser, users can perform interactive data analysis in Jupyter Notebooks through SWAN and AARNet’s shared cloud computing services.

After listening to user feedback, we have updated to JupyterLab 3.2.8 and added:

• Julia Kernel
• Java Kernel
• OpenRefine
• RStudio

Julia is the language of choice for data scientists and has become increasingly popular in many fields of research, especially those that need large-scale numerical work such as machine learning and climate modelling.

Java, one of the most popular computer programming languages in the world, is now also available in SWAN. Java is a general-purpose programming language that is often used for client–server web applications.

Additionally, we now offer OpenRefine, a popular application for data clean-up and transformation. Used in Library Carpentry, it is a powerful tool for information management professionals and anyone needing to clean up their datasets to make them machine readable.

RStudio is an environment made for R; a programming language that specialises in statistical computing and graphics. SWAN already includes the R kernel for Jupyter Notebooks, but this is the first time we are offering the full benefit of RStudio for those who prefer working in that environment.

Dr Martin Schweinberger, researcher and lecturer in Applied Linguistics at the University of Queensland and Director of the Language Technology and Data Analysis Laboratory (LADAL), has found R and RStudio greatly beneficial in his research.

"R and RStudio are really flexible tools for working on language data. Being able to use RStudio in the cloud allows me to free up my laptop and perform analyses on big data that my computer cannot handle, and to easily share notebooks and scripts with students and other researchers," he said.

"The integration of RStudio and SWAN has the potential to really enhance the sharing of resources and the interactivity of the resources offered by LADAL.”

LADAL is part of the Australian Text Analytics Platform (ATAP, supported by the Australian Research data Commons [ARDC]), of which AARNet is a partner organisation, working to provide researchers with tools and training for analysing, processing, and exploring text.

These new options in SWAN are available now in the launcher. If you would like to try them out, log into CloudStor and click on the SWAN logo.

SIGnet community

AARNet has a CloudStor SWAN special interest group called the SIGnet community. This forum is for researchers to help each other use SWAN efficiently to accelerate quality research in Australia by building knowledge and expertise in handling research data using Jupyter Notebooks. You can find answers to frequently asked questions about SWAN and a community of users to collaborate with to solve shared or unique data handling problems.