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Public defence in Computer Science, M.Sc. (Tech) Petri Leskinen

Artificial intelligence brings history to life and enables the production, publication, and utilization of biographical data for research.

Public defence from the Aalto University School of Science, Department of Computer Science.
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Title of the thesis: Modeling and Using Biographical Linked Data for Prosopographical Data Analysis

Doctoral student:  Petri Leskinen
Opponent: Associate Professor Antonis Bikakis, University College London, UK
Custos: Professor Eero Hyvönen, Aalto University School of Science, Department of Computer Science

Biographical data containing information about historical figures, groups, and organizations, offers valuable insights into history. This thesis tackles the practices of creating, modeling, and publishing Linked Open Data, as well as analyzing biographical and prosopographical data by the means of network and data analysis. By harmonizing the data and publishing it in a machine-readable format, the data can be analyzed to understand individuals' lives, actions, and their social connections. The goal in this thesis was to enhance the discoverability, accessibility, interoperability, and reusability of biographical data publications.

In this research, artificial intelligence, semantic web standards, and event-based modeling are employed to represent historical events and individuals in a machine-readable format. The event-based modeling enables depicting historical narratives as data, which can be further enriched with the events of individual people and organizations furthermore linked to, e.g., related occupations and places. The findings can be applied in various fields of research, including history, genealogy, literary studies, and social sciences. Potential applications include discovering new connections between people and events, analyzing societal changes, and developing new teaching methods.

This research has resulted in several data publications and portals, including WarSampo (2015–), Norssi High School Alumni (2017–), BiographySampo (2018–), AcademySampo (2019–), LetterSampo (2020–2), and ParliamentSampo (2021–). These databases have been enriched by providing a linkage to external resources like Wikidata, Union List of Artist Names of the Getty Research Institute, and the Finnish Finto ontology service. The research presents the underlying data publications and services, as well as analyses and visualizations based on the data. 

Key words: biographical data, data analysis, digital humanities, linked open data, network analysis, prosopography, semantic web

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/ 

Contact information:

Doctoral theses of the School of Science: https://aaltodoc.aalto.fi/handle/123456789/52 

Zoom Quick Guide: https://www.aalto.fi/en/services/zoom-quick-guide

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