> For the complete documentation index, see [llms.txt](https://openscholarship.gitbook.io/chosn/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://openscholarship.gitbook.io/chosn/working-groups/use-case-data-driven-history.-living-with-machines.md).

# Use Case: Data-Driven History. “Living with Machines”

The British Library, in partnership with the Alan Turing Institute, led the Living with Machines project (funded by UKRI/AHRC) to analyse the social impact of industrialisation in 19th-century Britain ([Living with Machines, n.d](https://www.turing.ac.uk/research/research-projects/living-machines).; [Ahnert et al., 2023](https://doi.org/10.1017/9781009175548); [The Living with Machines Team, 2025](https://doi.org/10.14296/xdyp6338). The project combined digitised maps, newspapers, books, journals and census records from library and cultural heritage collections to develop new computational methods for historical research. It also generated new digitised resources and enriched datasets, which were deposited in the [British Library’s Research Repository](https://bl.iro.bl.uk/collections/1ecde964-4860-4f66-af33-e2b8ba487bf9?locale=en\&page=2) to support future research and reuse.

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Digital collections and repositories enable entirely new research paradigms, positioning institutions as leaders in data-driven humanities and unlocking major funding opportunities.
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## What the repository and digital collections enabled

* Large-scale access to digitised newspapers, maps, census data, books and journals
* Integration of multiple heterogeneous datasets into a single research environment
* Application of AI, NLP, and data science methods to historical sources

## Research value

* Produced new forms of “computational history”, combining qualitative and quantitative analysis
* Generated new datasets, tools, and models for reuse by other researchers
* Revealed new insights into how industrialisation affected everyday life

## Institutional value

* Positioned the library strongly in digital humanities and AI-driven research
* Attracted major external funding (UKRI Strategic Priorities Fund)
* Built long-term research infrastructure and reusable datasets

## Why this matters

* Transformed existing collections into high-value research data at national scale
* Enabled new research methods and collaborations across disciplines
* Produced outputs (datasets, tools, publications) that continue to be reused

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