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Resources

  • Git: VS Code

    EN
    Getting access to the data on GitLab is different on all three operating systems. This post shows how to use the code editor VS Code with its graphical user interface for working collaboratively in Git with Windows, Mac and Linux.

  • Evaluation of Digital Heritage Experiences

    EN
    This resource discusses various approaches and methods to evaluate digital or hybrid interactive experiences, which support the interpretation of heritage assets. The resource also aims to support researchers’ and practitioners’ practical understanding of evaluation methods and tools to capture audiences’ engagement with media and explore technology impact.

  • Git Collaboration

    EN
    This short course will help learners understand how to work with Git in a collaborative setting such as teamwork or group projects, and how to make use of platforms like GitHub or GitLab to complete that work.

  • 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.

  • 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.

  • Corpus Analysis with spaCy

    EN
    This lesson demonstrates how to use the Python library spaCy for analysis of large collections of texts. This lesson details the process of using spaCy to enrich a corpus via lemmatization, part-of-speech tagging, dependency parsing, and named entity recognition. Readers will learn how the linguistic annotations produced by spaCy can be analyzed to help researchers explore meaningful trends in language patterns across a set of texts.