Letting researchers focus on research

Researchers need academic cloud services that are easy to use. This is where the SCALE-UP project comes in.

Text: Patrik Schnellmann, published on 23.02.2016

SWITCHengines was launched for the SWITCH community in 2015 as a fast and flexible way to set up virtual machines and use storage space. It can be used for a wide range of applications from simple project information websites to complex analyses of urban shadow patterns with 3D modelling.

After SCALE comes SCALE-UP

SWITCHengines, with its scalable infrastructure, was implemented as part of swissuniversities' P-2 project SCALE in 2014 and 2015.
SCALE-UP is now going a step further than SCALE. Its aim is to offer specific services for academic use. SWITCH is building up these services between 2015 and 2017 together with project partners from the academic community, making sure that universities' requirements flow into the development process. SCALE-UP comprises individual work packages that are being tackled on a staggered schedule. As of the start of 2016, all of the packages are in the design phase, where the focus is on collecting requirements and know-how from the community.

The work packages are as follows:

Big Data Analysis

Aim: an easy-to-use, scalable environment for analysing complex data. Standard tools such as Hadoop and Apache Spark are integrated, so researchers do not need to spend time installing and configuring them. In addition, students can learn how to deal with big data analysis tools in this environment (see box).

Scientific Data Pools

Aim: a service for storing large quantities of data. This goes together with Big Data Analysis and provides a place for researchers to store their data sets and make them available to others.


Collaborative Applications

Aim: a self-service environment that provides a digital home for researchers’, professors’ and students’ projects, e.g. a a simple website, an archive for project documents or a shared means of working on program code. Popular programming languages such as Python and R are supported.

Virtual Private Cloud (VPC)

Aim: to complement the existing infrastructure, SWITCHengines resources are used to increase redundancy. Virtual machines can be integrated into the campus network, and internal services can be accessed easily behind the firewall (see also "Virtual machines for central IT").

Container Technology

Aim: feasibility study and documentation of best practices for this next-generation technology following widespread virtualisation in the cloud. This makes it possible to use infrastructures more efficiently and to provide and operate services in an agile manner


Aim: feasibility study for a marketplace for academic cloud services from the academic community. This will help researchers and teaching staff to find or post offers easily.

Rating Charging Billing / VM Migration Strategy

Aim: a generic framework for reporting access and billing services offered via the marketplace. In a next step, tools that make it easy to move and back up virtual machines (VMs) will be produced. Moving locally produced VMs to the cloud will thus be a simple task.

Research in the Cloud / Classroom in the Cloud

Aim: best practice documentation for the practical use of cloud infrastructure for research and teaching. The findings will flow into existing and future services across the whole SCALE-UP project.

Statistical Workbench

Aim: To make the statistical analysis software that is popular among academics available on SWITCHengines. Procuring commercial software for cloud services is a challenge, which is why this work package has also produced its own process and operating model.


This article appeared in the SWITCH Journal March 2016.
About the author
Patrik   Schnellmann

Patrik Schnellmann

Patrik Schnellmann is Cloud Project Manager at SWITCH. He holds an MSc in Computer Science and a Master of Advanced Studies in Management, Technology and Economics from the Federal Institute of Technology in Zurich. Before joining SWITCH in 2004, he acquired experience in the finance industry and the Swiss government.



"Without tools, you're lost in a vast heap of data."

Markus Handke from the Institute of Information Management at the University of St. Gallen is in charge of the Big Data Analysis work package:
"Big data is a key topic at the Institute of Information Management. Students take courses in which they learn how to use analysis tools and derive valuable findings from their analyses. Big data is also important in research. Scientific questions include, for example, how to extract company-relevant information from social media. This can be done by analysing thousands of Twitter posts to gain a better understanding of or even predict consumers' behaviour. Without the right infrastructure and tools, you're lost in a vast heap of data. This is where a big data analysis service can help. It gives researchers a simple interface that allows them to carry out analyses of scientific data without having to install an entire system first."

The SCALE-UP project partners

  • Federal Institute of Technology Lausanne
  • University of St. Gallen, Institute of Information Management
  • University of Bern, Digital Humanities
  • University of Applied Sciences and Arts Northwestern Switzerland
  • University of Basel
  • FHS St. Gallen, University of Applied Sciences
  • Zurich University of Applied Sciences, ICCLab
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