Digital Tools


The Digital Tools resource examines different tools that historians and other humanities researchers might come across and find useful to their research. The resource provides an introduction to each tool including an audit of existing tools, case studies, and training modules on semantic markup and text mining.

Tools included in this resource are:

  • Semantic Data
  • Text Mining
  • Visualisation
  • Linked Data
  • Cloud Computing

For each tool a series of case studies have been provided alongside a tool audit.

Semantic Markup Tutorial

This tutorial provides an introduction to marking up texts so that they are machine readable and therefore searchable in a digital format.

Learning outcomes include:

  • Understanding the basic principles of markup
  • Know some HTML elements and their use
  • Understand the need for entity references and how to create them
  • Be able to correct some errors in HTML markup
  • How to use XML and create well-formed XML

Text Mining Tutorial

The text mining tutorial introduces the idea of text mining (and why you might wish to use this tool in your research). It then gives an introduction to using Python. The tutorial includes advice, exercises, and information on creating and gathering data, regular expressions and scripting, natural language processing (NLP), Named Entity Recognition, and Topic Modelling.

Learning outcomes include:

  • An understanding of what text mining is and how it can be used
  • A working knowledge of Python
  • How to set up Python to undertake text mining operations
  • Using regular expressions and scripting
  • Using Natural Language Processing
  • Understanding Named Entry recognition
  • Understand topic modelling
  • Be able to start a simple text mining analysis

Category: Tutorial

Educator(s): Jonathan Blaney, Matteo Romanello, Matthew Phillpott, Mark Merry

Registration: No

Requirements: Python and additional downloadable components

Number of modules: 2

Cost: Free

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Last modified: Tuesday, 9 June 2020, 3:26 PM