Lost visions: retrieving the visual element of printed books from the nineteenth century

Thomas, J, Lloyd, N and Harvey, I (2014) Lost visions: retrieving the visual element of printed books from the nineteenth century. In: Digital Humanities Congress, 4 - 6 September 2014, University of Sheffield, Sheffield, UK.

Official URL: https://www.shef.ac.uk/hri/dhc/dhc2014


Despite the mass digitization of books, illustrations have remained more or less invisible. As an aesthetic form, illustration is conventionally positioned at the bottom of a hierarchy that places painting and sculpture at the top. The hybridity or bi-mediality of illustration is also problematic, the genre having fallen between the cracks of literary studies and art history. In a digital context, illustration has fared no better: new technologies can aid the editing of a literary text far more successfully than they can deal with the images that accompany it. This paper focuses on the challenges and the implications of an AHRC-funded Big Data project that will make searchable online over a million book illustrations from the British Library’s collections. The images span the late eighteenth to the early twentieth century, cover a variety of reproductive techniques (including etching, wood engraving, lithography and photography), and are taken from around 68,000 works of literature, history, geography and philosophy. The paper identifies the following issues, which impact on our understanding of ‘the image’ in Digital Humanities and the negotiation of Big Data more generally: 1. ADDING TO BIBLIOGRAPHIC METADATA Although the images are accompanied by the BL catalogue entry, this information is not always complete. Moreover, data from the title (e.g. the name of the illustrator/engraver) needs to be identified in order to make the archive searchable using these terms. We will discuss the algorithms that we have used to add to this metadata. 2. ANALYSING THE ICONOGRAPHIC FEATURES OF THE IMAGES This is a particular challenge because of the sheer number of images in the dataset. Our approach combines image recognition software, crowdsourced tagging and machine learning. 3. NEW RESEARCH QUESTIONS We will outline the ways in which this searchable illustration archive will offer new ways of ‘reading’ images, allowing for the further development of Illustration Studies.

Item Type: Conference or Workshop Item (Paper)
Subjects: P Language and Literature > PR English literature
T Technology > T Technology (General)
Divisions: School of Writing, Publishing and the Humanities
Date Deposited: 16 Jun 2016 15:13
Last Modified: 15 Aug 2021 09:42
URI / Page ID: https://researchspace.bathspa.ac.uk/id/eprint/7645
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