Cross-cultural encounters in the Survey of India in the mid-nineteenth century

Cross-cultural encounters in the Survey of India in the mid-nineteenth century

My aims with the Fellowship were to show the opportunities in the IOR Map Collection to identify surveyors in the Survey of India. I chose a series of printed reports covering Topographical Surveys from 1861 to 1877. These are bound in three volumes in the India Office Records Map Collection. I aimed to demonstrate the information that can be extracted from those reports, and to reveal its potential in understanding cross-cultural relationships in this context. Survey of India Maps from this period rarely show the names of the people who did the hardest work, least of all those referred to at the time as Native/Sub Surveyors. However, the printed reports provide important details of the staffing and work of the Topographical Surveys. A main aim of the research was to identify the names, roles and, if possible, the working relationships of the people who were on the ground working in very difficult conditions to survey the land and produce maps of it. A parallel core aim was to develop my understanding of and skills in digital research methods. This latter aim stems from both a personal interest and a recognition that there is a huge amount of untapped printed material, the contents of which can enhance our understanding of who made the maps in our collections and how they and their teams worked. So, I developed a list of research questions covering both content and method.
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Rowlands, Huw

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    Coleridge Fellowship 2025-26 Summary Report
    (2026-06-10)
    Rowlands, Huw
    This short report summarises the Coleridge Fellowship 2025-26. It describes the project’s aims and main findings. The research used digital methods to extract data from ten printed reports of the Topographical Survey from 1864 and 1873. The data included the names of survey staff, the Survey Parties they worked for, the places in which they worked, and the maps produced. It aimed to use the extracted data to examine cross-cultural relationships between ‘Native Surveyors’ and other staff in the Survey Parties.
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    Survey of India Topographical Survey Reports Complete Table-Only Extractions
    (2026-06-10)
    Rowlands, Huw
    This dataset contains a comparison of output data from The Coleridge Fellowship 2025-26. Python code was compiled to extract entities relating to people and places from xml files exported from the Transkribus Optical Character Recognition platform. The project as a whole covers the years 1864 to 1873. For one year, 1865, a subset of data was also extracted manually and using several online AI services. This dataset brings together the different outputs of people's names and of places from the Python, manual and AI extractions to facilitate comparison of the output data. It is an Excel file.
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    Survey of India Topographical Survey Reports 1864-1873 Extracted Entities
    (2026-06-10)
    Lloyd, Harry
    This dataset contains the output data from The Coleridge Fellowship 2025-26. Python code was compiled to extract entities relating to people and places from xml files exported from the Transkribus Optical Character Recognition platform. The data covers the years 1864 to 1873. It is in two formats - csv and gexf (for use with Gephi) - and includes the names, titles, years of service and survey parties of Survey of India surveyors, together with placenames relevant to their surveying work. A data dictionary is also provided.
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    Cross-cultural Encounters in the Survey of India in the Mid-nineteenth Century
    (2026-06-10)
    Rowlands, Huw
    This PowerPoint presentation describes the Coleridge Fellowship 2025-26. The research used digital methods to extract data from ten printed reports of the Survey of India’s Topographical Survey from 1864 and 1873. The data produced included the names of survey staff, the Survey Parties they worked for, the places in which they worked, and the maps produced. It aimed to use the extracted data to examine cross-cultural relationships between ‘Native Surveyors’ and other staff in the Survey Parties. This presentation describes all the stages of research, reflects on its success, and describes opportunities to build on it.
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    End of Project Release - Python Entity Extraction Code
    (2026-06-10)
    Rowlands, Huw
    This dataset is derived from The Coleridge Fellowship 2025-26. It comprises a link to the end of Coleridge Project Release of Python code The code was compiled to extract entities relating to people and places from xml files exported from the Transkribus Optical Character Recognition platform. The output of the code is the csv and gexf file stored in the 'Extracted Entities' Dataset part of this project.
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    Survey of India Topographical Survey Reports 1864-1873 Images, TXT, and XML:
    (2026-06-10)
    Hossen-Mamode, Effie
    This dataset contains the source data from the Coleridge Fellowship 2025-26. Digital images of printed reports from the Survey of India's Topographical Survey from 1864 to 1873 were uploaded to Optical Character Recognition platform Transkribus. The images were transcribed there and two files exported for each report, one as txt and one as xml. The dataset comprises one image and xml file per page of each report, and one txt file per report, identified by its year of publication. There are ten subfolders, one for each report from 1864 to 1873.
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    A Geographer's Initiation Digital Humanities - Part 1
    (2026-06-10)
    Rowlands, Huw
    This blog post is the first in a series of three written for the British Library’s Digital Research blog about the Coleridge Fellowship 2025-26. The research used digital methods to extract data from ten printed reports of the Survey of India’s Topographical Survey from 1864 and 1873. This post describes the background to the research, early team planning meetings, and the start of transcription work using Transkribus. All text is © British Library Board and is available under a CC-BY Licence except where otherwise stated. This license does not apply to images or other media. For any image without an explicit license notice, users are responsible for determining its copyright status before reuse.
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    Survey of India Topographical Survey Report 1865 Comparison of Extracted Entities
    (2026-06-10)
    Rowlands, Huw
    This dataset contains a compilation of the tables extracted by ChatGPT, in parallel to the Python extraction workflow. In this file, the tables have been analysed to identify the longest-serving survey staff, the proportions of Native to to other survey staff, and a comparison of the areas of land they surveyed. The longest-serving staff identified became targets for the biographical research undertaken towards the end of the project. The project as a whole covers the years 1864 to 1873. It is an Excel file.
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    Coleridge Fellowship 2025-26 Full Report
    (2026-06-10)
    Rowlands, Huw
    This full report describes the Coleridge Fellowship 2025-26. The research used digital methods to extract data from ten printed reports of the Survey of India’s Topographical Survey from 1864 and 1873. The data included the names of survey staff, the Survey Parties they worked for, the places in which they worked, and the maps produced. It aimed to use the extracted data to examine cross-cultural relationships between ‘Native Surveyors’ and other staff in the Survey Parties. This full report describes all the stages of research, reflects on its success, and describes opportunities to build on it.
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    A Geographer's Initiation Digital Humanities - Part 3
    (2026-06-10)
    Rowlands, Huw
    This blog post is the third in a series of three written for the British Library’s Digital Research blog about the Coleridge Fellowship 2025-26. The research used digital methods to extract data from ten printed reports of the Survey of India’s Topographical Survey from 1864 and 1873. This post describes the use of Large Language Models (AI) platforms to extract data from the transcribed reports. All text is © British Library Board and is available under a CC-BY Licence except where otherwise stated. This license does not apply to images or other media. For any image without an explicit license notice, users are responsible for determining its copyright status before reuse.
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