Demo: CANFAR: Authentication, data access and computing interoperability of IVOA based cloud services integrated in EGI FedCloud
- sara bertocco (INAF)
Full title: Authentication, data access and computing interoperability of IVOA based cloud services integrated in EGI FedCloud.
The EGI-Engage H2020 European Project partially founded a joint project with the Canadian Advanced Network for Astronomical Research (CANFAR) to explore the authentication, data access and computing interoperability of cloud services based on tools and standards developed by the International Virtual Observatory Alliance.
IVOA is an organisation that debates and agrees the technical standards needed to realize the Virtual Observatory. A VO implementation allows astronomers to query multiple data centres in a seamless and transparent way, provides new powerful analysis and visualization tools within that system, and gives data centres a standard framework for publishing and delivering services using their data. In this project we work on the federation of CANFAR services and EGI Infrastructure, this includes the development of the overall set of IVOA standards based services and APIs to implement access control, data movement and computing interoperability in a geographically distributed cloud environment.
This activity is crucial to provide Astronomy and Astrophysics a cloud environment really suited for their requirements and it is actually under evaluation also in the framework of the ASTERICS project in particular for what regards the SKA project needs and requirements.
In this demo we describe the architectural overview of the federated infrastructure and the open source available libraries, we present the software documentation and the infrastructure setup built on top of a EGI Federated Cloud Site. We will present also a practical workflow example demonstrating a use case of data sharing between users working on the same project from both sides of the Ocean, i.e. transversally authenticated.
The work will continue integrating the virtual machine sharing to perform specific tasks like, for example, data reduction.