British Library Labs Competition (2016)

The annual Competition looks for transformative project ideas which use the British Library’s digital collections and data in new and exciting ways.

After much deliberation and a strong number of entries this year, BL Labs is excited to introduce the BL Labs Competition (2016) finalists and their two projects:

Black Abolitionist Performances and their Presence in Britain
By Hannah-Rose Murray, PhD student with the Department of American and Canadian Studies, University of Nottingham.

This project will create an original and exciting window into Victorian society by analysing the African American presence in Britain and how their performances and lectures reached nearly every corner of the country. It asks, how can we uncover hidden black voices in the archive?

Mapping the movements of the Black Abolitionists in Britain has never been done before and such visual representations can be used to gather an estimate of how many lectures they gave and, most importantly, allow their hidden voices to be heard. It will enable the exploration of their performances through their own words and follow how they interacted with British audiences to win support for abolition and combat the deeply entrenched racism of the period.

SherlockNet: Using Convolutional Neural Networks (CNNs) to automatically tag and caption the British Library Flickr collection
By Brian Do (MD student at Harvard University/MIT, Massachusetts), Luda Zhao and Karen Wang (Masters students in Computer Science at Stanford University, California).

Book illustrations, such as those in the British Library's Flickr Commons 1 million collection, provide valuable insights into the cultural fabric of their time. However, large image collections are only useful and discoverable by researchers if they can be deeply explored, and the process can often be time-consuming, requires expertise and relies on humans to recognise patterns.

Through the use of deep learning methods such as convolutional neural networks (CNNs), SherlockNet will provide computational automatic pattern recognition that will produce tags and captions for the Flickr collection. The tags and captions will be made publicly accessible and searchable through a web-based interface. This will allow the wealth of images, maps and illustrations in the Flickr collection to be more readily available to the researcher and members of the public alike.


Labs Competition winners from previous years have produced an amazing range of creative and innovative projects:

A further range of inspiring and creative ideas have been submitted in previous years and some have been developed further.