This guide will help you to find out how copyright affects your work, research and study here at the University of Manchester.
Copyright is legal protection for an author/creator which restricts the copying of an original work they have created. The University is committed to acknowledging and protecting the copyright of rights holders and adhering fully to the terms and conditions of the licences it holds.
The University of Manchester Library holds one of the finest collections of rare books, manuscripts and archives in the world. Both The John Rylands Library and Victoria University of Manchester Library had built up outstanding Special Collections. After their merger in 1972, these collections were concentrated in the magnificent Deansgate Building of the John Rylands Research Institute and Library, in the centre of Manchester.
The DiRT Directory is a registry of digital research tools for scholarly use. DiRT makes it easy for digital humanists and others conducting digital research to find and compare resources ranging from content management systems to music OCR, statistical analysis packages to mindmapping software.
The LADAL offers introductions to quantitative reasoning, research designs, and computational methods including data visualisation and statistics. It uses the R programming language and is aimed at complete novices as well as expert users.
Hosted by N8 CIR, join Melodee Beals as she introduces and explores how to use Python in the humanities. Learning basic python programming skills can open new and interesting avenues for your research, allowing you to interrogate sources at scale or zoom into finer details than are visible to the human eye!
This two-part course took place in May and June 2020 and was hosted by Melodee Beals of Loughborough University and saw participants learn the basics of the Python language before using these skills on Humanities projects rather than more generic programming examples.
WRDS is a collection of business and financial databases. It includes training toolkits on text analysis, sentiment analysis, named-entity recognition, machine learning and topic modelling. Requires registration.
The University of Manchester Digital Humanities partners with the Library