Develop your research skills: data management and research software

How can you maintain control over your research data during and after your project? In this 90-minute workshop, you will learn how to properly organise and manage your data at project, collection, and dataset levels. Through practical examples strategies such as the use of metadata, file naming conventions, and documentation are discussed. There is also room for personal preferences and working methods, allowing you to develop an approach that suits your research. 

Although recording audio or video has become easier than ever thanks to smartphones and online meetings, doing so in a professional manner — and in a way that produces high-quality research data — is a very different matter. This introductory workshop aims to address this by providing practical guidelines for researchers who wish to collect and process audio or video data, covering the entire workflow from project preparation to data processing. 

An introductory course for all Radboud University researchers who are required to write a Data Management Plan (DMP). During this one-hour workshop, you will receive all the information you need to get started on writing a data management plan for your research project. 

An introductory course for first-time users of the Radboud Data Repository (RDR). During this 75-minute course, you will actively participate and learn the core functionalities needed to work with your own collections. These include requesting a collection, adding metadata, uploading and downloading data, and inviting colleagues.

How do you publish or archive a collection in the Radboud Data Repository (RDR)? In this 90-minute workshop, you will learn about the steps and best practices involved in archiving and publishing research data. You will discover how to prepare your collection, navigate the different review phases, and make publication or archiving choices. The workshop also provides insight into access levels, licenses, and how to enhance the visibility, accessibility, and reusability of your data.  

Researchers in a range of fields (e.g. digital humanities or linguistics) commonly seek to quantify and understand features of a text which are not apparent without access to digital methods. This might include performing a word frequency analysis, examining co-occurrence statistics, or more broadly analysing the context in which words appear in a given text. In this module, participants will learn to perform these types of analysis using graphical tools that do not require programming knowledge. 

This module consists of two stand-alone workshops. In the first workshop, you will learn a workflow for extracting full text from PDF files in EndNote or Zotero and using it for, among other things, literature reviews with tools such as ASReview. You will learn how to extract specific sections (such as the introduction or methods) and how to classify documents. 

The second workshop focuses on mapping bibliometric relationships within a reference library, for example to model academic developments or networks of researchers. 

This module of two workshops introduces the text transcription tool Transkribus. During the first workshop you wil learn about the basic use and work flows. During the second workshop you will learn about advanced facilities such as training custom models to identify and transcribe text from tables, various page layouts, and unconventional or historical writing-styles.

This workshop covers the installation, use, and several applications of locally installed large language models (LLMs). Basic semantic search within a document library is also covered. 

UNIX-like systems such as Linux and macOS provide text-based facilities (command-line interfaces or shells) to interact with files and programs on these systems. Users enter commands via a shell scripting language. Knowledge of this is essential for programmatic interaction with the system and is often required when working with high-performance computing clusters. In this workshop, participants learn to use the Bash shell, understand shell scripts, and navigate and work in a text-based environment. This knowledge is also applicable on Windows through UNIX-like tools such as WSL, MSYS2, or Cygwin.