ETH Research Data Management Summer School 2023

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 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.

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.

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.

Research with sensitive personal data (strictly confidential and confidential data) requires special cybersecurity and data protection measures to ensure the confidentiality of data and to protect the privacy of individuals.

What constitutes strictly confidential and confidential data in a research context? Which laws and regulations must be complied with? What are the implications of non-compliance? I am a researcher – how do I translate and integrate laws, regulations and cybersecurity into my day-to-day research practice?

Let’s try to shine a light on to these questions. Workshop 4 builds on and extends concepts presented in these RDM Summer School sessions and workshops and will specifically address research data management for strictly confidential and confidential data.

Focus of the workshop

The workshop will be focused on:

• Research on strictly confidential and confidential data
• Data privacy and protection: legislation and cybersecurity awareness
• Data classification: Strictly Confidential, Confidential, Internal and Public classification levels
• Leonhard Med, ETH Zurich: a secure, powerful and versatile Swiss scientific data and IT platform for research on strictly confidential and confidential data
• “Best practices” for secure handling of strictly confidential and confidential data for research along the entire data lifecycle, from data collection, data management and analysis to publication in repositories and long-term preservation

Learning objectives

At the end of the workshop, you will:

• have a good understanding of data protection and privacy issues when dealing with strictly confidential and confidential data in research projects;
• have the necessary knowledge to conduct research respecting both legislation as well as information security requirements;
• be able to identify if your research data classifies as strictly confidential or confidential;
• be able to apply “best practices” for secure handling of strictly confidential and confidential data for research;
• be aware of how to use secure scientific Data and IT infrastructures for strictly confidential and confidential data for research at ETH;
• have the information needed for writing a data management plan for strictly confidential and confidential data for research.

Target audience

Researchers working with sensitive data (strictly confidential and confidential data), e.g. personal data such as health-related data or survey data.

Prerequisites

No previous knowledge required. However, participants might profit from attending the workshops 1 to 4 of the RDM workshop series offered in spring before attending this workshop at the Summer School.