Despite the growing interest in publishing linguistic data as Linked Open Data (LOD), the representation of ancient language corpora within the Semantic Web remains challenging. While LOD principles have been successfully applied to linguistic resources such as dictionaries, lexicons, and terminologies, their use for textual corpora — particularly those related to ancient languages — is still limited. Through a systematic literature review, we investigate how textual data has been represented as Linguistic Linked Open Data (LLOD), evaluating the potential and limitations of existing approaches and methodologies for enhancing data integration and interoperability in the Digital Humanities. This systematic literature review follows a rigorous methodology encompassing literature identification, screening for inclusion, and quality assessment. By classifying and analysing relevant studies, we provide a comprehensive overview of current practices and offer insights into their benefits and limitations.

A Systematic Literature Review on the Representation of Texts as Linguistic Linked Open Data

Bandini M.
Writing – Original Draft Preparation
;
Quochi V.
Writing – Review & Editing
2025

Abstract

Despite the growing interest in publishing linguistic data as Linked Open Data (LOD), the representation of ancient language corpora within the Semantic Web remains challenging. While LOD principles have been successfully applied to linguistic resources such as dictionaries, lexicons, and terminologies, their use for textual corpora — particularly those related to ancient languages — is still limited. Through a systematic literature review, we investigate how textual data has been represented as Linguistic Linked Open Data (LLOD), evaluating the potential and limitations of existing approaches and methodologies for enhancing data integration and interoperability in the Digital Humanities. This systematic literature review follows a rigorous methodology encompassing literature identification, screening for inclusion, and quality assessment. By classifying and analysing relevant studies, we provide a comprehensive overview of current practices and offer insights into their benefits and limitations.
2025
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Ancient languages
Ancient texts
DigitAnt
Linguistic Linked Open Data
Semantic Web
Systematic literature review
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/557403
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