Knowledge Graphs and Data Services for Studying Historical Epistolary Data in Network Science on the Semantic Web

Tracking #: 3236-4450

This paper is currently under review
Petri Leskinen
Javier Ureña-Carrion
Jouni Tuominen
Mikko Kivelä
Eero Hyvonen

Responsible editor: 
Guest Editors Tools Systems 2022

Submission type: 
Tool/System Report
Communication data between people is a rich source for insights into societies and organizations in areas ranging from research on history to investigations on fraudulent behavior. These data are typically heterogeneous datasets where communication networks between people and the times and geographical locations they take place are important aspects. We argue that these features make the area of temporal communications a promising application case for Linked Data (LD) -based methods combined with temporal network analyses. A key result of this paper is to show how to create and publish a global Linked Open dataset and data service about historical epistolary data, based on distributed data from several international heterogeneous data sources, that can be enriched by data linking and reasoning, and that can be served back for the research community as an open infrastructure, a data service, and a semantic portal for further study in Digital Humanities (DH). A framework for this purpose is presented for publishing and analyzing communication network data, based on recent advances in analysis of temporal communication networks and the behavioral patterns commonly found in them. The framework was applied to two created and published open LD services (CC BY 4.0): (1) the data schema, dataset, and data service of the Dutch CKCC corpus (of ca. 20 000 letters) and (2) the pan-European correspSearch corpus (of ca. 135 000 letters) related to the Republic of Letters (1500--1800). To evaluate and demonstrate the usability of the new data services in DH research, a semantic portal was implemented on top of their SPARQL endpoint demonstrating re-usability, flexibility, and feasibility of the Linked Data approach from a DH research perspective.
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