CS3 2019 - Cloud Storage Synchronization and Sharing Services

Session

Data science: applications and infrastructure

Jan 29, 2019, 9:30 AM

CNR

7. Exploring Callysto

Joe Topjian

1/29/19, 9:30 AM

Cloud infrastructure and software stacks for data science

Presentation

In 2017, Cybera began a joint collaboration with the Pacific Institute for the Mathematical Sciences (PIMS) called Callysto: a free, multimodal learning program for grades 5-12 students in Canada. The goal of this project is to use open source tools to enhance the computational thinking, coding, and data skills of teachers and students. At its core, Callysto uses JupyterHub to provide easy...

43. Image and data analytic pipeline for studying single-cell signaling dynamics in cancer

Maciej Dobrzynski (University of Bern)

1/29/19, 9:50 AM

Cloud infrastructure and software stacks for data science

Presentation

Signaling pathways are an important part of cellular machinery responsible for processing biochemical signals and translating them into fate decisions such as proliferation, migration, or programmed cell death. Aberrant signal processing due to mutations leads to errors in fate determination, such as an increased rate of proliferation which is one of the hallmarks of cancer. The process of...

38. Advanced geo-spatial data analysis with Jupyter

Mr Paul Hasenohr (European Commission - Joint Research Centre)

1/29/19, 10:10 AM

Cloud infrastructure and software stacks for data science

Presentation

The JRC Earth Observation Data and Processing Platform (JEODPP) is serving JRC projects and their partners for big data applications with emphasis on geospatial data. It has evolved into a multi-petabyte scale platform, offering advanced Web-enabled services for container-based batch processing, remote desktop, as well as interactive analysis and visualization through the JEO-lab service.

The...

14. DLCM: A Swiss solution for preserving research data on the long term

Dr Pierre-Yves Burgi (Université de Genève)

1/29/19, 11:00 AM

Cloud infrastructure and software stacks for data science

Presentation

Developed in the context of the 2017-2020 Swiss national program "Scientific information: Access, processing and safeguarding", the DLCM solution (dlcm.ch) consists of an open and modular architecture for long-term preservation of research data, compliant with the OAIS standard (ISO 14721). The independent modules, once deployed in the cloud, offer a range of services that allow researchers to...

26. SURF Reseach Drive - JupyterHub integration within OwnCloud

Tom Wezepoel (SURFsara)

1/29/19, 11:20 AM

Cloud infrastructure and software stacks for data science

Presentation

In addition to our SURFdrive ownCloud environment, where we support today more than 40,000 users from Dutch higher education and science with their need for personal data storage.
We have set up last year SURF Research Drive, where researchers are able to share more and larger datasets with a group of researchers from home or abroad and third party.

SURF Research Drive is an ownCloud based...

51. SWAN and its analysis ecosystem

Diogo Castro (CERN)

1/29/19, 11:35 AM

Cloud infrastructure and software stacks for data science

Presentation

CERN, and High Energy Physics (HEP) in general, face unprecedented challenges in data storage, processing and analysis. With the planned improvements to the Large Hadron Collider (LHC), including the High-Luminosity LHC, there is an expected increase of data in one order of magnitude. After processing and filtering these data, new tools and solutions, capable of dealing with such large...

12. CloudStor SWAN: Data Processing and Analysis Challenges in the Cloud

Mr Michael D'Silva (AARNet)

1/29/19, 11:55 AM

Cloud infrastructure and software stacks for data science

Presentation

CloudStor SWAN (Service for Web based ANalysis) is AARNet’s first attempt at providing data processing and analysis in the cloud to the research community in Australia. This presentation will discuss AARNet’s experiences, challenges and tools used to provide research data computing in the cloud.

SWAN (Service for Web based ANalysis) helps users run scientific data processing and data analysis...

19. Application store for data analytics

Gurvinder Singh Dahiya

1/29/19, 12:15 PM

Cloud infrastructure and software stacks for data science

Presentation

At Uninett, we have chosen Kubernetes as a platform to provide various
services. We have currently two production clusters serving different
communities. In addition we have used public cloud resources through kubernetes
for some use cases as well.

To make use of platform easier by end users, we have made an application
store where users have commonly used tools such as Jupyter Notebook,...