Resources

• Gold, Green, Diamond: What You Should Know About Open Access Publishing Models

  EN

  This tutorial examines the evolution of Open Access by tracing its historical developments and unpacking the terminology and concepts that continue to shape the movement.

• Analyzing Multilingual French and Russian Text using NLTK, spaCy, and Stanza

  EN

  This lesson covers tokenization, part-of-speech tagging, and lemmatization, as well as automatic language detection, for non-English and multilingual text. You’ll learn how to use the Python packages NLTK, spaCy, and Stanza to analyze a multilingual Russian and French text.

• Text Mining YouTube Comment Data with Wordfish in R

  EN

  In this lesson, you will learn how to download YouTube video comments and use the R programming language to analyze the dataset with Wordfish, an algorithm designed to identify opposing ideological perspectives within a corpus.

• Facial Recognition in Historical Photographs with Artificial Intelligence in Python

  EN

  In this lesson, you’ll learn computer vision and machine learning principles for object recognition, and how to apply these principles using Python to recognize and classify smiling faces in historical photographs.

• Automatic Text Recognition (ATR) - Where and How to Get Images

  EN

  This tutorial explores where and how to find, create, and collect images of textual material, a crucial initial step in any process using Automatic Text Recognition (ATR).

• Data and Databases: From Source to Data

  EN

  Humanities and social scientific data is fundamentally different in type to a great deal of data available in the sciences. This resource will help you to understand your data, and therefore how to handle it. This resource looks at humanities data and its reliability, as well as different types of data you may encounter.

• Working with Named Places: How and Why to Build a Gazetteer

  EN

  A digital gazetteer records information associated with specific places. This lesson teaches you how to create a gazetteer from a historical text, using the Linked Places Delimited (LP-TSV) format.

• Designing a Deck of Timeline Cards for Tabletops and Tabletop Simulator

  EN

  This lesson demonstrates how to use nanDECK to design and publish your own deck of printed or digital playing cards, and use them to test a group's knowledge of historical events through a Timeline-like game mechanic. This lesson will also highlight best practices for handling digitized historical objects.

• Automatic Text Recognition (ATR) - Layout Analysis

  EN

  Discover the subtleties of region and line segmentation and learn about the purpose of layout analysis for Automatic Text Recognition!

• Automatic Text Recognition (ATR) - End Formats and Reusability

  EN

  Increase the visibility of your ATR output while fostering Open Science.

• Automatic Text Recognition (ATR) - Text Recognition and Post-ATR Correction

  EN

  Dive into the fine-tuning of Automatic Text Recognition outputs!

• Automatic Text Recognition (ATR)- Pre-Processing and Image Optimisation

  EN

  Get ready to improve the quality of your scanned images before moving to the processing phase of your ATR project.