# Overview of software and infrastructure for research data at ETH Zurich

- Institution: CERN
- Taught by: Caterina Barillari, Jarunan Panyasantisuk
- Year: 2026
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3025441)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

In this talk we will present the options available to researchers at ETH Zurich for managing, storing, analyzing and sharing research data. Since 2022, guidelines for research data management are in place at ETH Zurich. These state that all processes around research data must be documented according to the FAIR data principles and recommend the use of Electronic Laboratory Notebooks (ELN). At ETH Zurich we develop a combined data management, inventory management system and digital notebook for experimental scientists across several disciplines (openBIS). This is provided as a Research Data Management (RDM) service inside ETH Zurich, to all interested groups. The software runs on ETH infrastructure and relies on Network Attached Storage (NAS), Cost Defined Storage (CDS) and Long Term Storage (LTS) for data storage. Moreover, data can be easily directly transferred to the Zenodo and ETH Research Collections data repositories for data publication and sharing. In addition to this resource for data management, we provide solutions for collaborative work within ETH Zurich and with external partners. These include Microsoft Teams, Sharepoint and OneDrive, Google Workspace and polybox (based on Nextcloud). For data processing and analysis, we maintain 2 cluster infrastructures: Euler (for research data with no specific restrictions) and Leonhard Med (for strictly confidential research data). In addition, we also provide access to external cloud resources such as Azure, GCP, AWS and CSCS. A cloud assessment process is in place.

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## Lectures

1. [Overview of software and infrastructure for research data at ETH Zurich](https://invisiblenetwork.ai/learn/cern/3025441/545019935623), 15 min (CERN's player)