We introduce CHeCLOUD-the Cultural Heritage Linked Open Data (LOD) Clouda topical sub-cloud within the broader LOD Cloud, designed to improve the FAIRness (Findability, Accessibility, Interoperability, Reusability) of Cultural Heritage datasets. The goal is to provide a sustainable, centralized reference for Cultural Heritage LOD datasets and assess their quality through a FAIR-aligned lens. The selection of the datasets to be included in CHeCLOUD followed a three-phase methodology inspired by systematic literature review guidelines, adapted for dataset discovery. It includes (1) structured identification of Cultural Heritage datasets from the LOD Cloud and external sources; (2) FAIRness evaluation using a mapping framework between data quality and linked data principles as well as the KGHeartBeat quality assessment tool; and (3) maintenance, via continuous updates and a feedback mechanism. The methodology ensures transparency, reproducibility, and domain-specific relevance. Besides detailing the proposed resource, datasets are assessed in terms of FAIRness by aligning FAIR principles and linked data quality dimensions. As a result, Reusability emerges as the strongest dimension, primarily due to consistent licensing and provenance metadata. Accessibility also scores relatively high, while Find ability and Interoperability reveal notable gaps. CHeCLOUD fills a critical gap in the LOD ecosystem by offering, for the first time, a structured, FAIR-aligned index of Cultural Heritage datasets. The findings highlight both the current strengths and areas needing improvement in Cultural Heritage data publication practices. The proposed methodology and assessment framework can be generalized to other domains, supporting broader efforts to enhance data FAIRness across Linked Data ecosystems.

The FAIRness of CHeCLOUD, the Cultural Heritage Linked Open Data Cloud

Lieto A.;
2026

Abstract

We introduce CHeCLOUD-the Cultural Heritage Linked Open Data (LOD) Clouda topical sub-cloud within the broader LOD Cloud, designed to improve the FAIRness (Findability, Accessibility, Interoperability, Reusability) of Cultural Heritage datasets. The goal is to provide a sustainable, centralized reference for Cultural Heritage LOD datasets and assess their quality through a FAIR-aligned lens. The selection of the datasets to be included in CHeCLOUD followed a three-phase methodology inspired by systematic literature review guidelines, adapted for dataset discovery. It includes (1) structured identification of Cultural Heritage datasets from the LOD Cloud and external sources; (2) FAIRness evaluation using a mapping framework between data quality and linked data principles as well as the KGHeartBeat quality assessment tool; and (3) maintenance, via continuous updates and a feedback mechanism. The methodology ensures transparency, reproducibility, and domain-specific relevance. Besides detailing the proposed resource, datasets are assessed in terms of FAIRness by aligning FAIR principles and linked data quality dimensions. As a result, Reusability emerges as the strongest dimension, primarily due to consistent licensing and provenance metadata. Accessibility also scores relatively high, while Find ability and Interoperability reveal notable gaps. CHeCLOUD fills a critical gap in the LOD ecosystem by offering, for the first time, a structured, FAIR-aligned index of Cultural Heritage datasets. The findings highlight both the current strengths and areas needing improvement in Cultural Heritage data publication practices. The proposed methodology and assessment framework can be generalized to other domains, supporting broader efforts to enhance data FAIRness across Linked Data ecosystems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4963655
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