Tabular data is widely used. It is often entered and formatted in a way that makes it easy for the human eye to read. However, in order to perform simple and accurate analyses and visualizations of 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 using sample data from library and information science:

• Best practices for data entry and formatting
• Avoiding common formatting errors
• Handling dates in spreadsheets
• Basics of quality control and data manipulation in tables
• Exporting data from tables
• Reconciliation with external sources, e.g., authority files

The workshop is based on the curricula of The Carpentries.

• Instructors: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English

Tabular data is widely used. It is often entered and formatted in a way that makes it easy for the human eye to read. However, in order to perform simple and accurate analyses and visualizations of 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 using sample data from ecology:

• Best practices for data entry and formatting
• Avoiding common formatting errors
• Handling dates in spreadsheets
• Basics of quality control and data manipulation in tables
• Exporting data from tables

The workshop is based on the curricula of The Carpentries.

• Instructors: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English

Tabular data is widely used. It is often entered and formatted in a way that makes it easy for the human eye to read. However, in order to perform simple and accurate analyses and visualizations of 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 using sample data from the social sciences:

• Best practices for data entry and formatting
• Avoiding common formatting errors
• Handling dates in spreadsheets
• Basics of quality control and data manipulation in tables
• Exporting data from tables

The workshop is based on the curricula of The Carpentries.

• Instructors: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English

Data preparation is a crucial step in getting ready for data analysis. OpenRefine is an open-source tool for data cleaning and transformation.

It offers features such as faceting and clustering, which help identify and correct errors in the dataset. OpenRefine is a Java application that runs locally in the browser; therefore, the data never leaves your own computer. The half- to full-day hands-on workshop is based on the OpenRefine curricula from The Carpentries. Using sample data from library and information science, it covers the following topics:

• creating, exporting, and importing a project in OpenRefine
• Using facets and text filters to view and edit selected parts of the dataset
• Reducing variations using clustering, bulk editing, and transformations
• Undoing and redoing actions
• Exporting the history and applying it to similar projects

• Instructors: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English

Data preparation is a crucial step in getting ready for data analysis. OpenRefine is an open-source tool for data cleaning and transformation.

It offers features such as faceting and clustering, which help identify and correct errors in the dataset. OpenRefine is a Java application that runs locally in the browser; therefore, the data never leaves your own computer. The half- to full-day hands-on workshop is based on the OpenRefine curricula from The Carpentries. Using sample data from the field of ecology, it covers the following topics:

• creating, exporting, and importing a project in OpenRefine
• Using facets and text filters to view and edit selected parts of the dataset
• Reducing variations using clustering, bulk editing, and transformations
• Undoing and redoing actions
• Exporting the history and applying it to similar projects

• Instructors: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English

Data preparation is a crucial step in getting ready for data analysis. OpenRefine is an open-source tool for data cleaning and transformation.

It offers features such as faceting and clustering, which help identify and correct errors in the dataset. OpenRefine is a Java application that runs locally in the browser; therefore, the data never leaves your own computer. The half- to full-day hands-on workshop is based on the OpenRefine curricula from The Carpentries. Using sample data from the social sciences, it covers the following topics:

• creating, exporting, and importing a project in OpenRefine
• Using facets and text filters to view and edit selected parts of the dataset
• Reducing variations using clustering, bulk editing, and transformations
• Undoing and redoing actions
• Exporting the history and applying it to similar projects

• Instructors: Claudia Engelhardt (TU Dresden/Center for Interdisciplinary Digital Sciences)
• Format: Workshop (in-person, online)
• Target groups: Students (B.A., M.A.), researchers
• Languages: German, English

This workshop provides a practical introduction to FDM for linguistics.

The workshop offers a practical introduction to FDM for linguistics. It begins by reviewing key FDM fundamentals—including the data lifecycle, the FAIR principles, and the CARE principles.

Building on this, the workshop addresses the specific characteristics of linguistic research data:

the diversity of data types, such as audio and video recordings, transcripts, annotations, glossed examples, and corpora
different working methods: working with secondary data, corpus and experimental linguistics, NLP, and field research
typical challenges: handling personal data, ethical issues in working with indigenous language communities, complex data dependencies, and a lack of standardization or documentation.

We provide both general FDM tools (e.g., for documentation, versioning, and storage) as well as established domain-specific tools (e.g., ELAN, CLARIN) and infrastructures (Text+).

In doing so, we make it clear: Many FDM practices are already part of normal linguistic work—such as collecting metadata or using annotation guidelines.

In this way, participants come to view FDM not as an additional task, but as an integral part of good scientific practice.

• Instructors: Mike Berger (Generative Linguist, ScaDS.AI Leipzig), Kay-Michael Würzner (Computer Linguist & Subject Specialist for Computer Science, SLUB Dresden)
• Format: Workshop (in-person, online)
• Target Audience: Students (B.A., M.A.), Researchers
• Languages: German, English

This workshop offers a practical introduction to the fundamentals of the Text Encoding Initiative (TEI).

TEI is a specialized markup language for the structured and semantic description of texts. The focus is on TEI’s unique capabilities for precisely mapping complex textual traditions, editorial interventions, and textual structures, thereby making written sources accessible for analysis, exchange, and long-term reuse. Using practical examples, participants will learn key elements and principles and apply them directly.

The workshop covers the following topics in detail:

• Fundamentals of XML and TEI
• Structuring and annotating texts
• Representing editorial interventions
• References to the Gemeinsame Normdatei (GND)
• Practical coding exercises

The workshop provides participants with an understanding of key TEI concepts and enables them to independently mark up simple texts as well as assess the potential applications of TEI in the classical sciences.

• Instructor: Alexandra Krug (Knowledge Manager at Come2Data, ZIH at TU Dresden)
• Target Audience: Graduate students (M.A.), researchers
• Format: Workshop (in-person, online)
• Languages: German, English
• Number of Participants: 12

The ability to modify digital data without leaving a trace and the possibility of perfect duplication present researchers with unique challenges when analyzing genuinely digital sources. This workshop teaches participants how to critically analyze genuinely digital sources and evaluate them using the historical-critical method. The associated challenges will be discussed using the example of Wikipedia, and practical solutions will be explored. Participants will learn about the unique characteristics of digital data processing in contrast to physical materials and test practical strategies for reflective source analysis.

The workshop’s content in detail:

• Characteristics of genuinely digital and retro-digitized sources
• Analysis of conditions of origin and digital transformation processes
• Applying historical-critical methods to digital contexts

The workshop provides participants with an understanding of the specific characteristics of genuinely digital sources and enables them to apply the concept of the historical-critical method to genuinely digital data and to develop practical strategies.

• Instructor: Alexandra Krug (Knowledge Manager at Come2Data, ZIH at TU Dresden)
• Target groups: Students (M.A.), researchers
• Format: Workshop (in-person, online)
• Languages: German, English
• Number of participants: 12