The 'Living with machines' project is a collaboration between the British Library and the Alan Turing Institute for Data Science and Artificial Intelligence. This presentation introduces the project and highlights some early explorations and work.
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Living with Machines: one year in
1. Our Partners Our Funders
Living with Machines
AKA what a difference a year makes!
Mia Ridge, Co-Investigator/Digital Curator, British Library @mia_out
For the project team and associates: Adam Farquhar, Alan Wilson, Amy Krause,
André Piza, Barbara McGillivray, Claire Austin, Daniel Van Strien, Daniel Wilson,
David Beavan, Emma Griffin, Federico Nanni, Giorgia Tolfo, Giovanni Colavizza,
James Hetherington, Joel Dearden, Jon Lawrence, Kaspar Beelen, Kasra
Hosseini, Katie McDonough, Maja Maricevic, Mariona Coll Ardanuy, Mia Ridge,
Michael Jackson, Olivia Vane, Rosa Filgueira, Ruth Ahnert, Timothy Hobson,
Yann Ryan
2. Overview
• About the project
• A selection of early work
But – there’s way too much to cover!
• Find out more: http://livingwithmachines.ac.uk
• Subscribe to our newsletter for updates:
http://bit.ly/LwMnewsletter
3. Living with Machines: the headline figures
• Funded by Arts and Humanities Research Council (AHRC) and UK Research
and Innovation (UKRI)
• £9.2 million (overall) from September 2018 to March 2023
• Aims to ‘rethink the impact of technology on the lives of ordinary people during
the Industrial Revolution’. Focusing on Britain c.1780-1918
• Sources include digitised newspapers (British Newspaper Archive); Ordnance
Survey maps (National Library of Scotland); census, birth, death and marriage
records; digitised books; other digitised sources (got an idea? Get in touch!)
4. “Living with Machines represents a hugely exciting and innovative development
in arts and humanities research. The collaboration between historians and data
scientists, exploiting the remarkable growth of digital archives, will open up
dramatic new perspectives on the well-known story of the industrial revolution
and the history of society’s relationship with machines and technology since the
eighteenth century.”
Prof Roey Sweet
Former Director of Partnerships and Engagement
Arts and Humanities Research Council
5. Living with Machines aims to:
• Generate new historical perspectives on the effects of the mechanisation of
labour on the lives of ordinary people during the long nineteenth century.
• Develop new computational techniques for working with historical research
questions.
• Create new tools and code that can be reused and built upon
• Support the wider academic and cultural heritage sector in using digital
methods to answer historical questions.
• Enrich the British Library’s data holdings for the benefit of all.
• Advance public awareness of data science methods and how digital research
in the humanities can enhance understandings of history.
6. Benefits for the cultural heritage sector
• Provide models for research collaboration and partnership
• Enhance GLAMs reputation for leading digital innovation
• Improve working with large scale digitisation, digital content, and data:
digitisation workflows, data processing for analysis, ingesting enhanced
metadata
• Better incorporate learnings and outcomes of research projects
• Grow digital collections
• Increase understanding of and ability to apply advanced methods
• Increase awareness of data science and digital history
• Develop a coherent, user-friendly model for mixed-rights access to items and
datasets
• Incorporate digital content and data in the exhibition programme
7. This time a year ago…
Details of the project were still under embargo, waiting for a
governmental press release
We were recruiting via vague descriptions like ‘Seeking researchers
to work on an ambitious data science and digital humanities project
at the British Library and Alan Turing Institute (London)’
But now...
10. Work so far… exploring biases in
digitisation
Newspaper titles
metadata: place of
publication or coverage
Newspaper press
directories: circulation of
newspapers
12. • People, Organisations, Places, Events, Artefacts
• Re-purposing of the PREMIS Agent-Event model
• Extended Date Time Format for expressing temporal uncertainty
• Proposal: model places as 2D probability distributions over geographical
coordinate system to capture two types of uncertainty
Work so far... modelling key concepts e.g.
named entities
13. Work so far… public participation
Launched a crowdsourcing task to find industrial accidents in
Victorian newspapers
14. But wait! There's more...
• Using computer vision to analyse historical maps
• Lexicon expansion: automatically generating lists of terms from a
small seed list (e.g. words about machinery)
• Work on toponym resolution, disambiguating place names
• Questions of agency: were machines assigned agency over human
affairs in the language used about them?
• Structural and semantic parsing of historical text
• Using active learning to match historical newspaper titles
• Modelling growth of regional cities based on census data
• ...and lots of reflective work on tackling a project of this size and
complexity
15. Thank you! Questions?
Dr Mia Ridge, Digital Curator, British Library
Email: digitalresearch@bl.uk
Twitter: @LivingWMachines
Crowdsourcing site: http://bit.ly/LivingWithMachines
• The first year was about getting up and running.
Follow our progress towards public outputs:
https://livingwithmachines.ac.uk
Editor's Notes
How representative is the digitised press of the 19C press as a whole? Contextual information can create confidence in the claims we make.
Newspaper Picker tool was designed to help the historians pick newspapers to digitise; needed to get from 2500 newspaper titles to about 50. Visualisation weights longer runs of newspapers (more sustained readership), under-represented areas and audiences
One approach to understanding the impact of mechanisation while providing data for other processes. Asking the public to help classify articles and record details of accidents on the Zooniverse crowdsourcing site.