Balazs Laurenczy (ETH Zürich)
Alexander Kashev (University of Bern)
Title: Practices for reproducible data analytics through container technologies
Thursday, 28 June 2018 | Full day tutorial
Abstract: Being able to provide means to reproduce scientific results is becoming a strong imperative for ever more scientific disciplines. Research in personalized health, as an example, has stringent requirements on data confidentiality, reproducibility and interoperability between different institutions, e.g. universities, hospitals and academic compute centers. Container technologies like Docker and Singularity provide efficient, yet flexible, means of abstraction to accommodate data analytics under such requirements within existing IT compute and data infrastructures. In this full day tutorial, we will cover a technical overview of container technologies focusing on Singularity, as well as on how this technology can be used in real-world examples.
Balazs Laurenczy short bio
Balazs comes from a biology / bioinformatics background with a PhD in Neuroscience. He is working since 2016 as a Scientific Software Specialist at the Scientific IT Services of the ETHZ, where he develops reproducible workflows using containers for biomedical use cases.
Alexander Kashev short bio
Alexander Kashev studied mathematics and mathematical logic at Moscow State University, Russia, followed by a computer science PhD at the University of Bern, Switzerland in 2012–2016. Since 2017, he has been part of the Science IT Support (ScITS) team of the University of Bern, responsible for helping local researchers with their specific science IT needs. He also participates in solving national science IT challenges through the EnhanceR project.