ETH Research Data Management Summer School 2024

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 pageopenBIScall_made 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 Swiss academic institutions (https://openbis.ch/index.php/openrdm-swiss/).

Learning objectives

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

At the end of the course, 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 do not 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 easy knowing that someone else (or even yourself six months down the line) could find, understand and reuse your research. Renku ensures traceability by tracking when, how and by whom results were produced. Renku provides single-click access to containerised, interactive computational environments without prior knowledge of underlying technologies. These ready-to-use environments are available in different forms, ranging from Jupyter notebooks and RStudio to fully-fledged desktop sessions running in the browser. Additionally, all of your project metadata is indexed in a searchable knowledge graph.

Focus of the workshop

In this workshop, you will learn how to use Renku to make your research output more Findable, Accessible, Interoperable and Reusable (FAIR).

Learning objectives

Participants will learn:

• how to set up and use Renku to manage data, code, workflows and computational environments;
• how to use containerisation to define and distribute computational environments;
• how to use a reproducibility platform to seamlessly share computational workflows 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.