Legal Knowledge Graph Foundations, Part I: URI-Addressable Abstract Works (LRMoo F1 to schema.org)

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Main Author: de Martim, Hudson
Format: Preprint
Published: 2025
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author de Martim, Hudson
author_facet de Martim, Hudson
contents Building upon a formal, event-centric model for the diachronic evolution of legal norms grounded in the IFLA Library Reference Model (LRMoo), this paper addresses the essential first step of publishing this model's foundational entity-the abstract legal Work (F1)-on the Semantic Web. We propose a detailed, property-by-property mapping of the LRMoo F1 Work to the widely adopted schema.org/Legislation vocabulary. Using Brazilian federal legislation from the Normas.leg.br portal as a practical case study, we demonstrate how to create interoperable, machine-readable descriptions via JSON-LD, focusing on stable URN identifiers, core metadata, and norm relationships. This structured mapping establishes a stable, URI-addressable anchor for each legal norm, creating a verifiable "ground truth". It provides the essential, interoperable foundation upon which subsequent layers of the model, such as temporal versions (Expressions) and internal components, can be built. By bridging formal ontology with web-native standards, this work paves the way for building deterministic and reliable Legal Knowledge Graphs (LKGs), overcoming the limitations of purely probabilistic models.
format Preprint
id arxiv_https___arxiv_org_abs_2508_00827
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publishDate 2025
record_format arxiv
spellingShingle Legal Knowledge Graph Foundations, Part I: URI-Addressable Abstract Works (LRMoo F1 to schema.org)
de Martim, Hudson
Digital Libraries
Artificial Intelligence
Computers and Society
Information Retrieval
Building upon a formal, event-centric model for the diachronic evolution of legal norms grounded in the IFLA Library Reference Model (LRMoo), this paper addresses the essential first step of publishing this model's foundational entity-the abstract legal Work (F1)-on the Semantic Web. We propose a detailed, property-by-property mapping of the LRMoo F1 Work to the widely adopted schema.org/Legislation vocabulary. Using Brazilian federal legislation from the Normas.leg.br portal as a practical case study, we demonstrate how to create interoperable, machine-readable descriptions via JSON-LD, focusing on stable URN identifiers, core metadata, and norm relationships. This structured mapping establishes a stable, URI-addressable anchor for each legal norm, creating a verifiable "ground truth". It provides the essential, interoperable foundation upon which subsequent layers of the model, such as temporal versions (Expressions) and internal components, can be built. By bridging formal ontology with web-native standards, this work paves the way for building deterministic and reliable Legal Knowledge Graphs (LKGs), overcoming the limitations of purely probabilistic models.
title Legal Knowledge Graph Foundations, Part I: URI-Addressable Abstract Works (LRMoo F1 to schema.org)
topic Digital Libraries
Artificial Intelligence
Computers and Society
Information Retrieval
url https://arxiv.org/abs/2508.00827