Research data serves as a crucial foundation not only for research projects but also for writing bachelor’s and master’s theses. Whether the data is newly collected or reused, in our workshop you will learn techniques to help you avoid data chaos, comply with the requirements of good scientific practice and other regulations, and manage data effectively.

In addition to the topics listed, we will address the following questions in the workshop:

What is a good backup strategy?

How can data from your own research projects be made interpretable and comprehensible to outsiders?

Where can research data be published and made available long-term?

How can third-party research data be found, used, and cited?

• Instructors: Pia Voigt (Data Science Centre ScaDS.AI Leipzig), Franziska Korb-King and Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences), Arne Rümmler and Kay-Michael Würzner (SLUB Dresden)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.)
• Languages: German, English
• Number of participants: up to 20 people

In many research projects, code and software are generated in addition to data.

These form the basis of research results and are, in some cases, also the result of scientific processes. In accordance with regulations for ensuring good scientific practice, the handling of research software and code should be documented and verifiable. If software and code are made available for reuse, they can also be used and further developed in other research contexts. We will teach you the fundamentals of effectively handling research software and code.

• Instructors: Arne Rümmler and Kay-Michael Würzner (SLUB Dresden), Pia Voigt (Data Science Center ScaDS.AI Leipzig)
• Format: Workshop (in-person, online)
• Target groups: Students (M.A.), researchers
• Languages: German, English
• Number of participants: up to 20 people

Traceability, transparency, and reusability are core objectives associated with open methods in research.

This is not just about sharing results and data. Open Science begins with the research design and extends throughout the entire process, from planning to publication. In addition to the theoretical foundations and motivations associated with open science, this workshop will focus on practical implementation strategies and test them using numerous examples.

• Instructors: Arne Rümmler and Kay-Michael Würzner (SLUB Dresden), Franziska Korb-King (ZIH Dresden), Pia Voigt (Data Science Center ScaDS.AI Leipzig)
• Format: Workshop (in-person, online)
• Target groups: Graduate students (M.A.), researchers
• Languages: German, English
• Number of participants: up to 20 people

The workshop teaches fundamental programming concepts using the Python programming language, such as variables, data types, control structures, functions, and simple data structures.

In hands-on exercises, participants apply their newly acquired knowledge directly by writing their own small programs and learning to tackle typical tasks independently. Basic principles such as clean code, debugging, and the use of development tools are also covered. The workshop is aimed at participants with little or no prior programming experience. The goal is to establish a solid foundation upon which further programming and data analysis skills can be built.

• Instructors: Cristoph Göpfert and Lucas Schröder (Chemnitz University of Technology, Faculty of Computer Science, Chair of Distributed and Self-Organizing Computer Systems)
• Format: Workshop (in-person)
• Target groups: Undergraduate (B.A.), graduate (M.A.) students, doctoral candidates
• Languages: German, English
• Number of participants: up to 20 people

This workshop covers the fundamentals of (semi-)structured data and its core technologies, such as XML, JSON, and RDF.

These technologies play a key role in modern web, software, and data infrastructures, particularly in the integration and structuring of data. Using practical examples, the workshop introduces relevant tools and techniques for creating, validating, and processing (semi-)structured data, and explores these in detail through specific application scenarios. Another component of the workshop is an introduction to the fundamentals of the Semantic Web. It explains how data can be semantically enriched, unambiguously described, and linked across system boundaries using the Resource Description Framework (RDF). The goal of the workshop is to develop a solid foundational understanding of (semi-)structured and semantic data formats.

• Instructors: Christoph Göpfert and Lucas Schröder (Chemnitz University of Technology, Faculty of Computer Science, Professorship of Distributed and Self-Organizing Systems)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), Researchers
• Languages: German, English
• Number of participants: 20 people
• Other: Basic programming skills are required

This workshop provides an introduction to academic writing with LaTeX—designed for beginners with no prior experience. Participants will learn how to professionally format academic texts—including references, figures, equations, and cross-references—directly for their own writing projects.

This workshop offers an introduction to academic writing with LaTeX—from the basics to typical applications in undergraduate and graduate studies. The workshop begins by covering key concepts: the structure of a LaTeX document, the separation of content and layout, working with templates, and the basic workflow.

Participants will learn to implement typical elements of academic texts: structuring longer documents, managing references with BibTeX, figures and tables, equations, as well as cross-references and indexes. The workshop will also address modular document structure and collaborative writing.

The workshop is aimed at beginners with no prior knowledge. The goal is to get to know LaTeX as a robust tool for consistent and professionally typeset texts and to use it directly for your own writing projects.

• Instructor: Mike Berger (Data Science Center ScaDS.AI Leipzig)
• Format: Workshop (in-person/online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English
• Number of participants: 20

This half- to full-day hands-on workshop uses practical examples to demonstrate how tabular data can be effectively prepared for data analysis using Tidy Data principles.

Data in tabular formats is widely used. It is often entered and formatted in a way that makes it easy for the human eye to read. However, to perform simple and accurate analyses and visualizations with tabular data or to process it further using programming languages such as R or Python, the dataset should first be cleaned and organized according to the principles of Tidy Data. Specifically, the following topics will be covered and practiced:

Best practices for data entry and formatting, avoiding common formatting errors
Fundamentals of quality control and data manipulation in spreadsheets
Data export from spreadsheets and handling dates in spreadsheets

The workshop is based on the curricula of The Carpentries.

Upon request, the workshop can be tailored to specific disciplines with a focus on ecology, social sciences, or library and information science. In such cases, datasets from the relevant academic fields will be used for the practical exercises.

• Instructor: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (In-person, Online)
• Target groups: Students, researchers, and other interested individuals
• Languages: German, English
• Number of Participants: 16

Our scientific computing workshop will equip you with the skills to perform complex scientific calculations independently.

We offer a wide range of topics covering the application of mathematical modeling, simulation and optimization calculations, intelligent data analysis, and AI methods. The workshop is designed for beginners and provides an overview of the various tools and their application scenarios. Courses on specific topics can be offered upon request.

• Instructors: Scientific Computing Team (Leipzig University Computer Center)
• Format: Workshop (in-person, online)
• Target groups: Researchers, students
• Languages: German, English
• Number of participants: open
• Additional information: A Leipzig University login is required to participate

In this workshop, we’ll use practical examples to show you how to create interactive visualizations for small datasets (< 1 GB) using JavaScript.

Software repositories such as GitHub or GitLab allow for the free hosting of static websites. We can use this functionality to create interactive visualizations of small datasets with the help of JavaScript visualization libraries such as P5.js or d3.js.

• Instructor: Arne Rümmler (SLUB Dresden, Research Support Services; Leipzig University Computer Center)
• Format: Workshop (in-person)
• Target groups: Students, Researchers
• Language: German
• Number of Participants: 10
• Additional Information: Knowledge of JavaScript or other programming experience is beneficial

In this workshop, you will learn practical techniques for managing and publishing data on Zenodo.

To comply with good scientific practice, research data and all associated information that enables the reproducibility of the research must be securely archived for at least 10 years. In addition, many research funders now require mandatory information regarding the reuse of data after a project’s completion (data reuse and publication). The interdisciplinary repository Zenodo provides a suitable platform for this purpose. Zenodo is provided by CERN and is an open repository for the publication and archiving of datasets, documents, and other research materials. Zenodo enables the long-term storage, discoverability, accessibility, and reusability of research data, thereby meeting the requirements of good scientific practice and funding agencies. This workshop will cover the registration, functionality, and use of Zenodo using an example dataset. It will also address the assignment of meaningful metadata, which is crucial for the discoverability of research data. Practical exercises will illustrate the importance of good documentation and metadata.

• Instructor: Arne Rümmler (SLUB Dresden, Research Support Services Department; Leipzig University Computer Center)
• Format: Workshop (in-person, online)
• Target groups: Students, researchers
• Languages: German, English
• Number of participants: Open

This hands-on workshop addresses aspects that should be considered when reusing data in an academic context.

Through practical exercises, the following topics will be explored in depth and discussed:

• Various sources of data
• Plausibility and quality checks
• Licensing issues

The workshop is based on materials developed by the DINI/nestor-UAG Training and Continuing Education team.

• Instructor: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students, researchers, faculty, and trainers in the fields of FDM and data literacy
• Languages: German, English
• Number of participants: 20

Data protection concerns everyone, and handling personal data presents challenges for all employees—especially researchers: What role does data protection play in day-to-day work and in research projects? Under what conditions may personal data be processed? What requirements must be met, and what strategies can be used to securely store, process, share, and retain personal data? In this workshop, we will introduce you to the basics of data protection and use practical examples to show you how to integrate data protection considerations into your daily and academic work.

• Instructors: Pia Voigt (Data Science Center ScaDS.AI Leipzig), Lina Höck (Chair of Civil Law, Intellectual Property Law, in particular Copyright Law, as well as Media and Data Protection Law, TU Dresden)
• Format: Workshop (In-person, Online)
• Target groups: Students (B.A., M.A.), researchers, administrative staff
• Languages: German, English
• Number of participants: open

This workshop provides a practical introduction to the fundamentals of data-related copyright law in an academic context.

Participants will first receive an overview of the fundamentals of copyright law, including the definition of a work, requirements for protection, and exceptions. Subsequently, the workshop will address practical topics such as the right to quote, the use of images and illustrations in academic works, and open-access licenses (particularly Creative Commons). Another focus is on copyright issues in the context of digital teaching, such as the provision of materials on learning platforms in accordance with Section 60a of the German Copyright Act (UrhG). In addition, the handling of AI-generated content will be examined from a copyright perspective. The workshop combines theoretical instruction with case studies and discussion sessions. It is aimed at anyone who must make copyright-related decisions in an academic or professional context.

• Instructor: Lina Höck (Chair of Civil Law, Intellectual Property Law, in particular Copyright Law, as well as Media and Data Protection Law, TU Dresden)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers, faculty, administrative staff
• Languages: German, English
• Number of participants: 30
• Additional information: The duration and thematic focus of the workshop can be customized.

This interdisciplinary workshop provides comprehensive AI expertise in accordance with Article 4 of the EU AI Regulation. Participants will gain both foundational technical knowledge and insights into the ethical and practical implications, as well as in-depth knowledge of the relevant legal areas surrounding the use of artificial intelligence.

In six thematically interconnected modules, participants gain in-depth knowledge of the technical foundations of AI systems, including machine learning and generative AI. In addition, key issues in AI ethics are addressed, including fairness, transparency, and bias mitigation. A key focus is on an introduction to the AI Regulation, including its risk categories, obligations, and prohibitions. In addition, the copyright and data protection frameworks governing the use of AI are examined. Finally, other related legal areas such as university guidelines, good scientific practice, and labor law aspects are addressed. The workshop combines theoretical instruction with practical examples and discussions. It is aimed at individuals who work with AI in a professional or academic context or who are responsible for its implementation.

• Instructor: Lina Höck (Chair of Civil Law, Intellectual Property Law—particularly Copyright Law—as well as Media and Data Protection Law, TU Dresden)
• Format: Workshop (In-person, Online)
• Target groups: Students (B.A., M.A.), researchers, faculty, administrative staff
• Languages: German, English
• Number of participants: 30
• Additional information: The duration and thematic focus of the workshop can be customized.