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2020 | OriginalPaper | Chapter

An Ontology and Knowledge Graph Infrastructure for Digital Library Knowledge Representation

Authors : Stefano Ferilli, Domenico Redavid

Published in: Digital Libraries: The Era of Big Data and Data Science

Publisher: Springer International Publishing

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Abstract

New technologies for storing and handling knowledge provide unprecedented opportunities for enhanced fruition of digital libraries and archives. Going beyond document retrieval based on lexical content or metadata, using the context of documents, and/or of their content, may provide very new ways to put them in perspective and grasp a deeper understanding thereof, also for non-technical users.

Several components are needed to support this new perspective: suitable ontological resources to describe such variated knowledge, collaborative tools to collect the precious knowledge scattered across many scholars and practitioners spread all over the world, and to store it in a knowledge base, fruition tools to make the collected knowledge available to all interested stakeholders (scholars, researchers, but also common people).

This paper proposes the GraphBRAIN environment as a possible infrastructure. It is a general-purpose tool that allows its users to design and populate knowledge graphs, to collaboratively enrich them, and to exploit advanced fruition tools, consultation and analysis tools. Its functionality may also be provided as a set of Web services to end-user applications. An initial version of the ontology and knowledge graph for digital libraries and archives are also presented and discussed in the paper.

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A demo of the system can be found at http://193.204.187.73:8088/GraphBRAIN/.

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Title: An Ontology and Knowledge Graph Infrastructure for Digital Library Knowledge Representation
Authors: Stefano Ferilli
Domenico Redavid
Publisher: Springer International Publishing
Book: Digital Libraries: The Era of Big Data and Data Science
Print ISBN: 978-3-030-39904-7

Electronic ISBN: 978-3-030-39905-4

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-39905-4_6

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