Constructing and managing prosopographical data in the social sciences

Authors

Pedro Araujo, Anne-Sophie Delval

PDF
Publication

FORS Guide Nº 29

DOI
https://doi.org/10.24449/FG-2026-00029
How to cite

Araujo, P. & Delval, A.-S. (2026). Constructing and managing prosopographical data in the social sciences. FORS Guides, 29, Version 1.0, 1-23.

Keywords

Prosopography, Biographical data, Data collection, Data management, Database

Abstract

This guide provides practical guidance for constructing and managing prosopographical data in the social sciences. It addresses challenges in transforming biographical traces into structured data, with attention to population definition, source assessment, variable construction, database organisation, preservation and reuse, and conditions for sharing.

Recommendations

  • Define the study population explicitly. Prosopographical data should be constructed on the basis of a clearly delimited population. Inclusion criteria should be documented, since they shape the sources consulted, the variables collected, and the possible analyses.
  • Assess sources before extracting information. Sources should not be treated as neutral repositories of information. Their producers, purposes, coverage, biases, and limits should be assessed before information is extracted and transformed into data.
  • Standardise data collection without losing source granularity. A prosopographical questionnaire, codebook, and controlled vocabularies help ensure comparability. At the same time, precise dates, original formulations, titles, and contextual notes should be preserved when they may be useful for later interpretation or reuse.
  • Document coding decisions and uncertainties. Coding rules, source choices, contradictions, missing information, and degrees of certainty should be documented. This is essential for transparency, quality control, reuse, and later correction or extension of the database.
  • Choose a database structure adapted to the project. A spreadsheet may be sufficient for small projects, but relational structures are often more appropriate when individuals are linked to multiple positions, organisations, sources, events, or benchmark years.
  • Prepare sharing conditions carefully. Publicly available information is not automatically shareable. Before dissemination, researchers should assess the legal framework, source restrictions, sensitive variables, and disclosure risks, as well as whether anonymisation is possible or desirable.

    • Copyright

    © the authors 2026. This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0)

    Publication year

    2026

    Informed consent: Ethical and legal considerations