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Basic OCR (optical character recognition)

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The first step in many digital humanities projects is to digitize whatever corpus is being used. In order to use digitized text without having to manually transcribe it or laboriously cut and paste it, Optical Character Recognition (OCR) is often used. Using two scanned pages from Virginia Woolf’s novel The Waves, the following screencast offers some basic instruction on how to OCR scanned pages. A few choices of OCR software are also briefly evaluated. A free, community version of a popular OCR software is tested as well as a free, web-based version and the quality of these is examined. Finally a trial version of a moderately expensive software is tested and evaluated. By the end of the screencast, viewers should have information that will give them a head start when it comes to undertaking a small scanning/OCR project.

Material Type: Lecture

Author: Pratt Institute School of Information and Library Science

The Programming Historian 2: Viewing HTML Files

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When you are working with online sources, much of the time you will be using files that have been marked up with HTML (Hyper Text Markup Language). Your browser already knows how to interpret HTML, which is handy for human readers. Most browsers also let you see the HTML source code for any page that you visit. The two images below show a typical web page (from the Old Bailey Online) and the HTML source used to generate that page, which you can see with the Tools -> Web Developer -> Page Source command in Firefox.

Material Type: Diagram/Illustration

Authors: Adam Crymble, William J. Turkel

Python Programming for the Humanities -- A Python Course for the Humanities

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The programming language Python is widely used within many scientific domains nowadays and the language is readily accessible to scholars from the Humanities. Python is an excellent choice for dealing with (linguistic as well as literary) textual data, which is so typical of the Humanities. In this book you will be thoroughly introduced to the language and be taught to program basic algorithmic procedures. The book expects no prior experience with programming, although we hope to provide some interesting insights and skills for more advanced programmers as well. The book consists of 10 chapters. Chapter 5 and Chapter 6 are still in draft status and not ready for use.

Material Type: Data Set, Full Course, Primary Source, Textbook

Authors: Folgert Karsdorp and Maarten van Gompel, modifications by Mike Kestemont and Lars Wieneke

The Programming Historian 2: Transliterating non-ASCII characters with Python

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This lesson shows how to use Python to transliterate automatically a list of words from a language with a non-Latin alphabet to a standardized format using the American Standard Code for Information Interchange (ASCII) characters. It builds on readers’ understanding of Python from the lessons “Viewing HTML Files,” “Working with Web Pages,” “From HTML to List of Words (part 1)” and “Intro to Beautiful Soup.” At the end of the lesson, we will use the transliteration dictionary to convert the names from a database of the Russian organization Memorial from Cyrillic into Latin characters. Although the example uses Cyrillic characters, the technique can be reproduced with other alphabets using Unicode.

Material Type: Diagram/Illustration

Author: Seth Bernstein

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