Osiris-AI partnered with Humap to create a customised crowd-sourced campaign based around an innovative website that allows volunteers to map 17th century fire insurance policy registers covering London addresses. We provided the underlying data using our bespoke handwritten text recognition service and additionally we created historical map overlays to work with modern digital mapping software. We also consulted on the digitisation of the original documents.
We built an interface for Aviva to help map entries from historical policy registers. It provides extracts of digitised policy entries with automatic transcriptions, helping users identify, and then map, policy details. The original documents date back to the Hand in Hand Fire and Life Insurance Society, the oldest of Aviva’s heritage companies, with policy registers dating back to 1696. Mapping these historical policies will help Aviva’s specialist archive team learn more about their earliest customers, as well as providing information for family historians and adding to our understanding of how London looked hundreds of years ago. Aviva hopes to make the completed maps publicly available in the future.
The tool works by randomly allocating users one of the first 3,240 policies, which relate to addresses in London. The first postcodes were not introduced until 1959 and many houses in the registers did not have numbers, so using details of the parish, road names and other geographical markers (such as ‘west of the Tower’) extracted from the policy entry, users can navigate a historical map of London and mark the exact or approximate location of the policy, as well as amending an automated transcription of the policy wording. Once entries are validated, Aviva’s archive team extracts the corrected transcriptions together with the coordinates for the location of the property, providing a picture of the inhabitants and insurance of historical London. This follows more than two years of work to digitise 150 volumes of historical Hand in Hand policies, covering around 550,000 entries. The details required for working out the insurance premium and identifying the individual property provide a unique window onto London in this period.
The tool can be found here: Amicable Contributors
Many of our clients need precise line-level data extraction from non-digital sources. Like the example image shown, we can identify rows within non-digital tables and extract lines of data into a spreadsheet or any other data file type.