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Scholarship in three dimensions can transcend the limitations of traditional two-dimensional representations of objects that exist in the physical world in three dimensions. This presentation showcases the scholarly potential of 3D digital scholarly editions, advocating for their adoption as a new tool in the DH toolkit for new formats for the dissemination and interrogation of knowledge.

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.

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.

In this podcast, produced by virturalculture.ch, Jane Haller, a sociologist, digital project manager, and president of the Digitales Schaudepot, is in conversation with Esaù Dozio, a curator at the Antikenmuseum Basel. Within their chat, they discuss the process of selecting items for special exhibitions, and the mistakes and challenges that can arise.

This lesson demonstrates how to create interactive data visualizations in Python with Plotly's open-source graphing libraries using materials from the Historical Violence Database.

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.

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.

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

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.

This resource is an introduction to 360 degrees panorama photography. It explores different types of panoramic representations and examples of 360 degree panoramas in the cultural heritage domain. Practical advice and step by step guidance on how to capture data and process them is also included in order to produce and publish 360 degrees panorama images.

This pathfinder provides an introduction to Geographic Information Systems (GIS), covering analysis and visualization. It explains various spatial methods and each method is explained with a definition, practical examples and links to free resources online for further reading and exploration.

This resource provides guidance on digital practices to curate interactive experiences through a set of practical exercises. The resource aims to support GLAM's researchers and practitioners to engage with their audiences through the design of multimedia applications, while making use of appropriate frameworks and tools.

This resource provides guidance on how to use digital storytelling, deploying 3D data, annotations and combining media to enable users to access and explore information about digital heritage assets over the web.

This resource is an introduction to Digitisation Methods for Material Culture. The resource explores basic topics with regards to the study of material culture, while also looking at types of media as means to communicate and share information about it, as well as digitisation methods to capture material culture data.

This presentation outlines the aim and scope of the Historical Farm and People Registry project, explains the development process and problems encountered on the way, and demonstrates a use case for the 'final' product.

This lesson demonstrates how to build a basic interactive web application using Shiny, a library (a set of additional functions) for the programming language R. In the lesson, you will design and implement a simple application, consisting of a slider which allows a user to select a date range, which will then trigger some code in R, and display a set of corresponding points on an interactive map.

This lesson from Programming Historian introduces basic use of Map Warper for historical maps. It guides you from upload to export, demonstrating methods for georeferencing and producing visualizations.

This lesson is the second in a two-part lesson focusing on regression analysis. It provides an overview of logistic regression, how to use Python (Scikit-learn) to make a logistic regression model, and a discussion of interpreting the results of such analysis.

This three-day international training school in Knowledge Extraction from Text from the CLS Infra project offered a crash course in how to “Dig for Gold” in a corpus of texts. From Stylometry to Natural Language Processing, learners will be able to follow along using 'plug and play' tools, while also getting a brief introduction to Python and R.

This lesson is the first of a two-part lesson focusing on an indispensable set of data analysis methods, logistic and linear regression. It provides an overview of linear regression and walks through running both algorithms in Python (using Scikit-learn). The lesson also discusses interpreting the results of a regression model and some common pitfalls to avoid.

Since their beginnings in the 17th century, newspapers have recorded billions of events, stories and personal names in almost every language and every country daily. This course from DariahTeach provides an introduction to digitised historical newspaper analysis, incorporating methods of Natural Language Processing for discovering, exploiting and visualising newspapers.

This course from dariahTeach introduces learners to the theoretical and practical foundations of an analysis of socio-cultural objects using Python through theoretical grounding and hands-on case studies. Students will work through several research use cases using basic machine learning, and employ network analysis to split a small community network into groups and clusters before finally learning more about visualisation and image analysis.

The aim of this virtual course is to offer basic knowledge and skills in programming in Python. Target audiences are undergraduate and graduate students in the Humanities and Social Sciences who want to acquire hands-on knowledge and skills in working with textual data or quantitative data in language and humanities research.

Tableau is a powerful digital tool for analysing data that can help with mapping and interrogating data. In this short guide we will focus on an aspect of data analysis using mapping that has particular application for Holocaust and refugee studies.

EHRI (European Holocaust Research Infrastructure) supports the use of digital tools that can assist in the research of Holocaust and refugee related topics. In a continued effort to make these tools as accessible as possible so that researchers who have no experience with digital tools will consider trying new ways of using their data, this GitHub-based lesson showcases the use of entity match tools when dealing with geographic data.