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Data analysis in CloudStor
29 August, 2019

Data analysis in CloudStor: SWAN is ready for researchers

In the sciences, humanities and the arts researchers are increasingly performing data analysis in the cloud. However, some of the biggest challenges researchers still face (and have shared with us) are with moving research data, particularly large and complex datasets, between storage facilities and the research cloud computing facilities or virtual laboratories where analysis can be performed.

Research CloudStor News

AARNet has stepped in to help a wide range of researchers by adding SWAN, a Service for Web-based Analysis, to the AARNet CloudStor platform.

SWAN has been available on CloudStor for a few months, in beta phase for testing the service with early adopters. After taking feedback on board and making some performance and interface improvements, we are pleased to announce that SWAN is now ready for all researchers at AARNet-connected institutions to utilise.

SWAN was developed by CERN, the European Organization for Nuclear Research, one of the world’s largest and most respected centres for scientific research and an AARNet partner in the development of CloudStor. SWAN provides Jupyter Notebooks to allow researchers to perform interactive data analysis in CloudStor using a web browser and without the need to install any software. Jupyter Notebooks can be launched through SWAN to process research data using cloud computing services operated by AARNet.

The Jupyter Notebook is an open-source web application that allows researchers to create, execute and share documents containing code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning and much more.

SWAN comes with a default set of code libraries for R and Python programming languages. Our latest release expands these default libraries, and additional code libraries can be imported and installed in a notebook to meet different research needs.

Researchers can easily share their Jupyter Notebook files and data with collaborators within and between institutions through CloudStor’s file sharing capabilities.

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