ETH Research Data Management Summer School 2025

Git is a version control system for managing changes in code over time and coordinating software development within teams. It is a fundamental tool in modern software development.

If your answer to any of the following questions is “yes”, then working with Git may be of interest to you:

• Some of my code files have dates or versions encoded, like “script_abc_from_july_2020.py”.
• I want to undo some change in my code I did e.g. weeks ago.
• I want to compare my current code with a previous version because it stopped working.
• I work on the same code with others.
• I want to publish code on public code repositories, such as github.com or gitlab.com.

Focus of the workshop

The workshop will introduce basic principles, the most useful commands and best practices for working with Git and GitLab/GitHub. It also includes an introduction to working with your computer’s command line/terminal.

Learning objectives

Understanding Git basic principles, what it does, and how and when to use it.

How to publish work on public repositories such as gitlab.com or github.com

Target audience

Researchers who work with programming code or text files.

Prerequisites

No previous knowledge required.

external page openBIS is a combined data management platform, electronic laboratory notebook, and inventory management system. openBIS helps scientists to meet requirements from of funding agencies, journals, and academic institutions for publishing data in line with the FAIR data principles. Scientists can use openBIS to document their daily experimental or computational work, store any related experimental raw and derived data, and link everything to materials, samples and protocols stored in the lab inventory. The system ensures safe data storage and provenance tracking.

openBIS is an open source software distributed under the Apache v2.0 licence, developed by ETH Zurich Scientific IT Services (ETH SIS). ETH SIS provides services based on openBIS to research groups at ETH Zurich (https://ethz.ch/staffnet/en/it-services/catalogue/software-business-applications/research-data-management.html) and at other external page Swiss academic institutions.

Learning objectives

In this workshop, we will provide a general overview of openBIS followed by a practical training session.

At the end of the workshop, the participants are expected to be able to:

• use the openBIS inventory of materials and samples;
• use the openBIS inventory of laboratory protocols;
• document projects and experiments in the openBIS lab notebook and enter data.

Target audience

Experimental scientists working in research labs.

Prerequisites

• Knowledge/competencies
  This workshop is designed for beginners and does not require any previous knowledge.
• Technical equipment
  Participants are required to have their own laptop. An openBIS test server will be made available to participants on the day of the workshop. Recommended web browsers are Firefox, Safari or Chrome.

The course material will be provided a few days before the workshop and participants will be required to download the material onto their laptops and have it ready for use on the day of the workshop.

Want to follow best practices in data management but don’t know where to start? Renku’s data management toolkit helps you manage every aspect of your project - data, code, workflows and computational environments, so you can rest assured that someone else (or even yourself six months down the line) will be able to find, understand and reuse your research. Renku is a platform for reproducible and collaborative data analysis. It provides single-click access to containerised, interactive computational environments without prior knowledge of underlying technologies. Renku is based on modular project configurations for bootstrapping your project with a mix of code repositories, data sources, and computational environments and evolve them as the project matures. For example, in an early stage of a project, you may simply require a quick way to open a dataset in a small compute environment for some basic data exploration; as the analysis of the data deepens, you may need to add a code repository to start versioning the code and collaborate with others in a more structured way. Later on, someone else on the project might build a containerised app or dashboard to demonstrate the data properties and model results more easily with non-experts. Renku allows you to select the components that you need for your project to work.

In addition to connecting all the required resources under one roof, Renku makes these elements searchable, encourages their reuse between projects, and illuminates connections between them, even across projects.

Focus of the workshop

In this workshop, you will learn how to use Renku to take advantage of Open Science best practices from the start.

Learning objectives

At the end of the workshop, the participants are expected to be able to:

• set up and use Renku to manage data, code and computational environments in a reusable fashion,
• use the platform to seamlessly share data, code, and computational environments with others.

Target audience

Researchers that develop and run, or want to develop and run, computational workflows for simulations, processing and analysing their data.

Prerequisites

No previous knowledge required.