Bridging the Disciplines for Cultural Heritage? Case studies on how to align Linked Open Data and FAIR Digital Objects in Federated Knowledge Graphs

Bridging the Disciplines for Cultural Heritage? Case studies on how to align Linked Open Data and FAIR Digital Objects in Federated Knowledge Graphs Andreas Noback | Florian Thiery | Thorsten Schrade TU Darmstadt | Leibniz-Zentrum für Archäologie | Academy of Sciences and Literature ᚛ᚇᚓᚌᚑᚄ ᚋᚐᚊᚔ ᚋᚑᚉᚑᚔ ᚈᚑᚔᚉᚐᚕᚔ᚜ DEGOS MAQI MOCOI TOICAKI Daig son of the descendant of Toicacas Data Metadata PID I0I0 0I0I Resource Description Framework (RDF) graphs express information as subject– predicate–object triples, enabling semantic linking between datasets across the web. As Linked Open Data, they provide machineactionable, interoperable representations of knowledge that can be queried and reused through open standards. The open-source platform Wikibase allow communities to collaboratively curate structured knowledge in graph form. They serve as decentralised, human-and machineactionable hubs that bridge distributed databases and Linked Open Data ecosystems. Prominent examples are Wikidata, FactGrid and the wikibase.cloud. FAIR Digital Objects combine data, metadata, and persistent identifiers to ensure that (binary) digital resources are FAIR. They form the backbone of interoperable research infrastructures, providing a stable reference layer that connects datasets, software, and publications within federated knowledge graphs. The “Federated Knowledge Graph Ecosystem” Use Cases from Engineering and the Humanities The Linked Open Ogham dataset is modelled in RDF using the Squirrel Ontology (SquirrelO) aligned with CIDOC CRM, and is accessible, e.g., via the NFDI4Objects Knowledge Graph as part of a federated archaeological Linked Open Data environment within the NFDI ecosystem. Ogham Stone data are represented across multiple Wikibase instances —including Wikidata (serving as a data hub for external identifiers such as OSM), Semantic Kompakkt (3D models and annotations), FactGrid (inscriptions, persons, and words), and the fuzzy-sl Wikibase (geospatial coordinates and uncertainty modelling). Although FDO implementation for Ogham is still in development, existing components — such as 3D models derived from Structurefrom-Motion (SfM) workflows and Research & FAIRification software —form the basis for future FDOs integrating data, metadata, and provenance information. I0I0 0I0I & Remaining Challenges Within the Humanities, RDF and Linked Open Data rely on community standards such as CIDOC CRM and its extensions to achieve semantic interoperability across collections. The remaining challenge lies in harmonising heterogeneous domain ontologies and ensuring that mappings remain maintainable and transparent over time. For engineering sciences, NFDI4ING is developing the m4i metadata standard, which will serve as the basis for the knowledge graph currently under construction. Wikibase platforms like Wikidata, FactGrid, and Semantic Kompakkt foster open collaboration but differ in data models, property schemas, and community practices within the Humanities. Aligning these graphs into a shared semantic framework remains a challenge, particularly when balancing scholarly precision with user-driven flexibility. In the Humanities, the integration of FAIR Digital Objects is still emerging and requires consensus on metadata granularity, persistent identifiers, and provenance standards. The key challenge is connecting FDO frameworks with existing Linked Open Data infrastructures without duplicating effort or fragmenting communities. Similarly, the process of standardisation and typification of FDO in engineering sciences is still in its infancy. Furthermore, there is a lack of digital tools to generate these during the research process without creating additional hurdles for researchers. I0I0 0I0I Community Standards Roman glass find BSDF measurement (scattering properties) Analytic model (fitted) Daylight simulation GIS analysis Geometric model Laser scan & room book Ostia (heritage site) Engineering and scientific methods applied in archaeology and cultural studies inherit the research data management requirements of all scientific fields involved. The source objects and results of the research are linked in archaeology and cultural studies through metadata and authority data, for example in the knowledge graphs of NFDI4Culture and NFDI4Objects. The data generated and the code used follow the rules of engineering and scientific research data management and are incorporated, for example, into the knowledge graph of NFDI4ING. The documentation of the process chain, as exemplified here by a daylight simulation in a Roman building in Ostia, is of particular importance. Data and code must be stored as FAIR digital objects, which means, among other things, that they must be available in open file formats or OSS software and described in sufficient detail by metadata to enable reuse. I0I0 0I0I