19th Century Digitised Books Collection

19th Century Digitised Books Collection

In partnership with Microsoft, the British Library has digitised, and made freely available under Public Domain Mark, over 60,000 volumes (around 25 million pages) of out of copyright 18th & 19th century texts. Items within this collection cover a wide range of subject areas including geography, philosophy, history, poetry and literature and are published in a variety of languages. This collection, sometimes referred to as the Microsoft Books/BL 19th Century collection, and its derived datasets have been made available on various platforms under an open license. All volumes are available for view, download and full-text search from the British Library Catalogue - https://explore.bl.uk - via the Library’s IIIF standard enabled Universal Viewer. Use the search term “blmsd” in Explore to limit results to this specific collection. Over 1 million images extracted from the book pages programmatically can be found on British Library’s Flickr: https://www.flickr.com/photos/britishlibrary/ The Flickr API can be used to directly download large sets of these images, and other metadata such as user-generated tag information: https://www.flickr.com/services/developer/ JISC Historic Texts holds a full copy of this collection: https://www.jisc.ac.uk/historical-texts Wikimedia Commons offers a useful introduction to the collection, including a Synoptic Index, as well as projects to georeference maps found in the texts: https://commons.wikimedia.org/wiki/Commons:British_Library/Mechanical_Curator_collection
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    Item type:Dataset,
    OCR text derived from digitised books published 1890 - 1899 in ALTO XML
    (2014)
    British Library
    ;
    British Library Labs
    This set consists 14847 volumes, published between 1890-1899. The dataset comprises text from the collection of digitised books created using Optical Character Recognition (OCR) technology. The books cover a wide range of subject areas including philosophy, history, poetry and literature. The dataset is in Analysed Layout and Text Object (ALTO) Extensible Markup Language (XML) format.
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