# From Data To Knowledge: Computing For High-Energy Physics Experiments

- Institution: CERN
- Department: HEP Computing
- Speaker: Mario Lassnig
- Year: 2024
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3013819)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Modern large-scale sciences have become increasingly complex and face unprecedented data & compute challenges. The number of data-intensive instruments generating substantial volumes of data is growing and their accompanying internal and external workflows are becoming more complex every day. Their storage and computing resources are usually heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organisations. In this presentation, we will try to give an insight how we solved these problems in High Energy Physics: from data taking, distributed processing, infrastructure, and user analyses, with specific examples from the ATLAS Experiment..

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## Lectures

1. [From Data To Knowledge: Computing For High-Energy Physics Experiments](https://invisiblenetwork.ai/learn/cern/3013819/ee5973e7e479), 1 h (CERN's player)