Resources

• 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.

• Transcribing Handwritten Text with Python and Microsoft Azure Computer Vision

  EN

  Tools for machine transcription of handwriting are practical and labour-saving if you need to analyse or present text in digital form. This lesson will explain how to write a Python program to transcribe handwritten documents using Microsoft’s Azure Cognitive Services, a commercially available service that has a cost-free option for low volumes of use.

• Copyright of 3D Data

  EN

  This resource offers an introduction to copyright laws within the UK context when dealing with multidimensional media from repositories, archives and collections from that country.

• Automatic Text Recognition (ATR) - Getting Started

  EN

  Kick off your journey into Automatic Text Recognition (ATR) with our introductory tutorial video. This is the first video of a tutorial series dedicated to extracting full text from scanned images.

• Wikipedia as a source of historical knowledge

  EN

  A lesson on Wikipedia as a born-digital source of history and how to apply digital source criticism to it. The lesson invites historians to adapt their critical approach to Wikipedia as a born-digital source for historical research. More specifically, it suggests ways to apply digital source criticism to Wikipedia’s infrastructure and content and to explore potential uses of Wikipedia for historians. The lesson proposes a short introductory video and a set of five assignments. No specific technical skills are required to complete the assignments.

• Data and Databases: An Introduction

  EN

  In this resource students will learn what a database is and how it is used in humanities research, go through examples of Humanities Databases in use by researchers today, learn when a researcher would need to use a database and how to distinguish between different database technologies.

• Clustering and Visualising Documents Using Word Embeddings

  EN

  This lesson uses word embeddings and clustering algorithms in Python to identify groups of similar documents in a corpus of approximately 9,000 academic abstracts. It will teach you the basics of dimensionality reduction for extracting structure from a large corpus and how to evaluate your results.

• Langzeitarchivierung

  DE

  Dieser Kurs gibt einen Einblick in die langfristige Bewahrung digitaler Daten, d.h. die Archivierung digitaler Daten. Es werden praktische Tipps aus der Perspektive der Datenersteller gegeben.

• Photogrammetry 3D Digitisation

  EN

  This resource is an introduction to the photogrammetry technique to capture visual data about cultural heritage assets and produce associated 3D models.

• Sentiment Analysis with 'syuzhet' using R

  EN

  This lesson teaches you how to obtain and analyse narrative texts for patterns of sentiment and emotion. The 'syuzhet' sentiment analysis algorithm, along with the programming language R, will be used, demonstrating the techniques to allow learners to follow along.

• ENCODE open online course

  EN

  The ENCODE open online course 'Digital tools for the research and study of ancient writing cultures' is designed to introduce teaching staff, GLAM professionals, and graduates to ancient writing cultures and digital studies, exploring the digital transformations in the fields of Greek and Latin epigraphy, papyrology, and other aspects of ancient writing cultures.

• FAIR Multidimensional Data

  EN

  This resource offers a starting point to learn more about the different types of multidimensional media, as well as managing media in a way which promotes the FAIR principles. The resource also introduces the concept of a Virtual Research Environment to support retrieval and curation of multidimensional data for storytelling via interoperable frameworks.