A few of the featured training sessions for the upcoming period:
Git wise! An introduction to version control with Git
The best time to plant a tree (or initialise a Git repository) was twenty years ago. The second-best time is today.
— An ancient proverb.
Are you about to start working on your code for data accumulation? Do you want to test a new algorithm for your analysis script while being able to switch back to the original state? Or do you want to share your code with a colleague for a friendly peer review? A version control system like Git can help you in each of these situations and many more! After a successful pilot, the DCC will teach an updated pair of workshops (and here) this 17 & 22 September to help you get going with Git. The first will focus on the basics needed to work on a solo project. The second will dive into branching, remote repos and workflows for team collaboration.
So join up and Git wise!
Shell scripting basics
UNIX-like systems such as Linux and macOS provide text-based facilities (command-line interfaces, shells) to interact with files and programs on these systems. Knowledge of these interfaces is critical to interacting with the system programmatically, and is often required to properly use version control workflows (e.g. work with git), create analysis pipelines, or perform work on high-performance computer clusters. This workshop will teach participants the Bash shell-scripting language, how to understand shell-scripts, how to navigate the system and perform work in a text-based environment. Nearly all of this material is applicable to Windows systems as well, when they are equipped with UNIX-like tools (e.g., git for Windows, MSYS2, Cygwin, Windows Subsystem for Linux). This workshop is on 14 September.
Workshop Shell scripting basics
Learning Python for text-mining and the analysis of natural language
Text-mining refers to techniques which can involve the collection, processing and parsing of text derived from a range of sources (e.g., corpora, digital libraries, web forums). Text-mining is often performed with the goal of analyzing text to gain insights not readily available without the use of digital methods. It is useful to or shares methods with fields which seek to understand words and their context using computer friendly representations (e.g., word embeddings, or word vectors) such as natural language processing (NLP), computational models of language, psycholinguistcs, or digital humanities. In this hands-on course, students and researchers will learn text-mining and NLP techniques using the Python programming language for a range of use-cases. Six sessions are currently available. Participants may choose to attend whichever of these self-contained sessions they find useful, but it is recommended that participants who are new to this topic attend at least Session 3. This course starts on 12 October
Automatic multi-language text transcription for hand-written or typeset documents (Transkribus)
Transkribus is a suite of tools which facilitate the automatic transcription of documents. The software is maintained by a European cooperative (READ-COOP), with access to computational resources provided through an RU subscription. Although originally designed to provide an environment to facilitate the manual transcription of documents, the software now supports automatic transcription in large number of languages, both hand-written and typeset text, and can provide competent transcriptions in these languages at different stages of their evolution (e.g. Old English). In addition to its ability to process non-modern languages, Transkribus can also process text on discolored or otherwise degraded pages. It is hence suitable for transcription projects featuring historical documents. An additional key benefit of this software is the capability it provides to users to easily train custom models that can automatically identify complex layouts and fine-tune the text recognition process. This is helpful when transcribing difficult documents (e.g. historical diaries).
This workshop series consists of two sessions. The first session covers introductory material and introduces participants to common Transkribus workflows and document management. The second provides an in-depth overview of the model training system for a diverse set of documents provided for the session. Participants are free to attend one or both sessions depending on their background and interest. This workshop series is perhaps most useful to humanities researchers, but is likely interesting to anyone interested in text transcription.
This workshop will take place on 9 and 10 November.
Network data (graph) analysis and visualization
The ability to analyze, inspect and visualize networked data is essential in many academic disciplines. In this module participants can find courses and workshops which teach network analysis, visualization, and the tools to accomplish this. Sessions in this module are predominantly stand-alone, and participants may pick and choose which sessions are right for them. The target group is researchers (PhD candidates and above), but advanced students may also benefit.
The module includes an introductory course on network analysis using the software tool Gephi, which provides a user-friendly interface to interrogate and visualize networked data and which is suitable for non-programmers.
The DCC also offer workshops which teach the basics of R, igraph, ggplot2 and ggraph packages. The package igraph is commonly used to create and analyze graphs from networked data, and ggplot2/ggraph are standard tools for visualizing statistical (ggplot2) and graph (ggraph) data. This module also covers the tool nodegoat, which can be used to create, manipulate and publish relational databases.
This workshop will take place on 23 and 24 November.
Workshop Network (graph) analysis with Gephi
Text-mining for literature review and bibliometric analysis
When performing a literature review, whether to better understand a topic or for the purpose of writing a systematic or scoping review, researchers are often faced with the task of synthesizing information from a daunting number of articles. In this workshop series, participants will learn a range of computer tools and methods to approach this problem. Several of these involve the use a software workflow developed at the RU Library to extract and analyze text from PDFs contained in a reference manager library (e.g. zotero or endnote). Article text can furthermore be extracted based on section (e.g. introduction, methods), which allows for the use of tools or methods conventionally applied only to article abstracts. For example, this might include preparation of the extracted text to be used as input to ASReview, analysis with natural language processing tools, or summarization.
This multi-session workshop starts on 14 December.
Workshop Large-scale text extraction
Other training courses
In addition to the above courses and workshops, the Digital Competence Centre offers more training courses for researchers in the coming months. Check out the channel on gROW or the overview on the courses and workshops on the Radboud University website.