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Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing

Über Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing

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.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783754343692
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 224
  • Veröffentlicht:
  • 6 Oktober 2021
  • Abmessungen:
  • 160x19x226 mm.
  • Gewicht:
  • 513 g.
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Beschreibung von Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing

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.

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