Nov 04, 2019 to Nov 08, 2019
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Conferences & Events
ESCAPE - The European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no. 824064.
Location:
Adelaide, Australia
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10,387
04 November 2019 to 08 November 2019
The 24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019) took place between 4th and 8th November, in Adelaite (Australia). The CHEP conferences address the computing, networking and software issues for the world’s leading data‐intensive science experiments that currently analyse hundreds of petabytes of data using worldwide computing resources. The Conference is a major event in the area (~500 participants), featuring plenary sessions, parallel sections and poster presentations; it publishes peer-reviewed proceedings.
ESCAPE was invited to CHEP 2019 to do a presentation on how is prototyping a Data Infrastructure for Open Science
Open Science will make science more reproducible and transparent and it is a necessary tool to begin answering immensely complex questions that are too complex to be carried out by any one individual.
Simone Campana (senior staff member at CERN and an ESCAPE partner) demonstrated how ESCAPE is prototyping an infrastructure adapted to the Exabyte-scale needs of the large science projects, that ensures the sciences drive the development of the European Open Science Cloud (EOSC), while addressing FAIRdata management procedures.
The ESCAPE Data Lake Cloud Services (DLCS) is a federated data infrastructure of open access data that enables large national research data centres to work together and build a robust cloud-like service to curate and scale up to multi-Exabyte needs. The ESCAPE DLCS is a cloud of data services that follows FAIR data management principles at the bases level while serving global user communities in a scalable and performing way. In particular, CHEP's audience became very interested on how ESCAPE will address FAIR data challenges and how those functionalities will be implemented into ESCAPE DLCS.
