eBook, PDF

Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing (eBook, PDF)

Beschreibung

In scholarly digital editing, the established practice for semantically enriching digital texts is to add markup to a linear string of characters. Graph data-models provide an alternative approach, which is increasingly being given serious consideration. Labelled-property-graph databases, and the W3c's semantic web recommendation and associated standards (RDF and OWL) are powerful and flexible solutions to many of the problems that come with embedded markup. This volume explores the combination of scholarly digital editions, the graph data-model, and the semantic web from three perspectives: infrastructures and technologies, formal models, and projects and editions.

Technische Details

• Geräte: PC
• ohne Kopierschutz
• Größe: 38.95MB
• FamilySharing(5)

Autor

Elena Spadini: Elena Spadini is a postdoctoral researcher at the University of Lausanne (Switzerland). She holds a Ph.D. in Romance Philology from the University of Rome Sapienza (2016) and a M.A. in Digital Humanities from the École nationale des chartes (2014). Francesca Tomasi: Francesca Tomasi is associate professor in Archival Science, Bibliography and Librarianship at the University of Bologna (Italy), President of the Library of the School of Humanities in the University of Bologna (BDU - Biblioteca di Discipline Umanistiche), Director of the international second cycle degree in Digital Humanities and Digital Knowledge (DHDK), President of the Italian Association of Digital Humanities (AIUCD - Associazione per l'Informatica Umanistica e la Cultura Digitale), and co-head of the Digital Humanities Advanced Research Center (/DH.ARC). Georg Vogeler: Georg Vogeler is professor for Digital Humanities at the University of Graz and scientific director of the Austrian Center for Digital Humanities and Cultural Heritage at the Austrian Academy of Sciences.

Produktdetails

• Verlag: BoD - Books on Demand
• Seitenzahl: 224
• Erscheinungstermin: 18. November 2021
• Englisch
• ISBN-13: 9783754358764
• Artikelnr.: 62942102