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Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records — arXiv:2608.23263

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.23263
License (as archived): CC0-1.0
Archived: 2026-10-18T07:41:53.275Z
SHA-256 of the archived text: 0bcf3d4d78ac19d31e4eb34fd2fe7578c82394f5573a1fca99dd61a257e1a86e
Stable URL of this page: https://metraipolis.com/documento/dc_7a59ea2e7aec

How to cite

Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records — arXiv:2608.23263 — arXiv (en), https://arxiv.org/abs/2608.23263 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_7a59ea2e7aec (Metraipolis archive dc_7a59ea2e7aec, sha256 0bcf3d4d78ac19d31e4eb34fd2fe7578c82394f5573a1fca99dd61a257e1a86e)

BibTeX

@misc{dc7a59ea2e7aec,
  title = {Automated Construction of FAIR Digital Object Knowledge Graphs from Flat Cultural Heritage Records — arXiv:2608.23263},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.23263},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_7a59ea2e7aec; sha256 0bcf3d4d78ac19d31e4eb34fd2fe7578c82394f5573a1fca99dd61a257e1a86e},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.23263. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to produce a fully machine-actionable graph in which every reference is resolvable. The Europeana Data Model was designed long before the FDO specification, and it stores most metadata values as plain text. This serves human browsing well enough, but gives an automated agent nothing to follow across records or collections. We present a pipeline that transforms flat Europeana records into an FDO-compliant knowledge graph structured with CIDOC-CRM. Following the FDO specification, we model every heritage entity as a discrete FDO with its own PID, type, profile, and metadata layer. The core technical challenge is automating the FDO-prescribed distinction between values that must become PID references (resolvable entities) and those that may remain literals (terminal leaves such as notes, measurements, and dates). We address this with a large language model that classifies each metadata value, routes it to a controlled vocabulary (Getty AAT, Wikidata, VIAF, PeriodO), and links it to a shared entity FDO. We evaluate using 637 archaeological records from five Europeana providers, processing each with the LLM. The pipeline links 86% of metadata slots, resolving 58.5% of values Europeana had not already enriched. It also merges cross-lingual surface forms that byte-identical matching keeps apart, where 17 of 33 such merges are correct on manual review. Graph connectivity does not separate this from string matching; what distinguishes the FDO graph is that every node is typed and resolvable.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-25 in cs.AI).
Categorie arXiv: Artificial Intelligence (cs.AI) ; Computation and Language (cs.CL); Digital Libraries (cs.DL).
Pagina del lavoro: https://arxiv.org/abs/2608.23263 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-18T07:37:52.771Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-25?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).