Temporal Knowledge Representation for Historical Corpora: Application to the Henri Poincaré Correspondence Corpus

Tracking #: 2774-3988

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Authors: 
Nicolas Lasolle
Olivier Bruneau
Jean Lieber
Laurent Rollet

Responsible editor: 
Special Issue Cultural Heritage 2021

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Full Paper
Abstract: 
The study of Henri Poincaré's life and works (1854-1912) has led to the constitution of a corpus which includes various document types (articles, books, reports, letters, etc.). There is a keen interest in his correspondence, which gathers scientific, administrative and private exchanges. Semantic Web technologies have been chosen to represent and to exploit corpus data: the RDF model, the RDFS knowledge representation language and the SPARQL query language. The existing representation does not include temporal knowledge, yet it is an important aspect when studying historical corpora. Different methods have been proposed by the Semantic Web community to include temporal knowledge in RDF databases. This article presents the temporal knowledge representation issues encountered in the exploitation of the Henri Poincaré correspondence corpus. Through examples, it compares existing methods and ontologies and details the implementation of the approach chosen for this corpus. A form-based interface has been developed to assist users in corpus data querying. The system relies on the use of a transformation rule mechanism to address two issues faced when dealing with temporal graphs: simplifying SPARQL query generation and reasoning with temporal data.
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