Semantic Intelligence Against CSAM: The PreventCSA@EU Ontology Framework for Classification and Investigation

BZKO: An Ontology for the Card Index of German Post-War Compensation Records

The Central Federal Card Index (Bundeszentralkartei) of Germany is a key archival resource documenting compensation claims submitted by victims of National Socialist persecution and their relatives, within the German Wiedergutmachung process. To enable semantically enriched representation, integration, and reuse of this historically significant collection, we present the BZK Ontology (BZKO). We propose a two-layer ontology for historical archival data that separates ontologically grounded domain semantics from interoperability-oriented extension constructs. The approach combines BFO-based realism with archival standards (RiC-O, PROV-O, PiCo), enabling provenance-preserving semantic integration, while maintaining logical rigor, modularity, and reuse across digital humanities infrastructures. The proposed approach establishes a reusable semantic foundation for the integration of Wiedergutmachung archival materials into digital humanities infrastructures and lays the groundwork for future knowledge graph generation, ontology validation, and the incorporation of additional historical entities and uncertain temporal and spatial information. The ontology is available on https://github.com/ISE-FIZKarlsruhe/bzko.

Dx-Onto: A Core Ontology for a Semantic-Based Framework for Managing Digital Transformation Projects

The rapid growth of digital transformation (Dx) initiatives across sectors has created an urgent need for structured, scalable, and accurate management of project knowledge. Without effective organization, valuable insights from Dx projects remain fragmented, limiting their reuse and hindering informed decision-making. This research addresses the gap by designing, developing, and validating Dx-Onto, a domain-specific core ontology implemented in OWL and purpose-built for representing and managing knowledge about Dx projects. Dx-Onto models entities, relationships, and attributes from diverse project documentation into a unified knowledge graph, enabling semantic search, cross-project analysis, and context-aware retrieval. To assess performance, a two-pronged evaluation strategy was adopted: (1) scalability experiments using synthetic datasets measured query execution times across volumes ranging from 10 to 1000 projects, and (2) a comparative benchmark against the Core Ontology of Organisational Transformation (COOT) was conducted using a heterogeneous real-world corpus of Thai digital transformation documents. The results confirm Dx-Onto’s capacity to scale and demonstrate a higher domain fit (85.2% vs. 77.3%) and superior analytical utility—including transformation-phase and strategic-dimension diagnostics that are structurally impossible under a general-purpose baseline. By positioning Dx-Onto as the core semantic layer for a future Hybrid LLM-Ontology framework, this work lays the groundwork for intelligent, scalable, and reliable knowledge management solutions in the digital transformation domain.

From Text to Executable Semantics: A Modular Ontology and SHACL Controls for University Intellectual Property Non-Disclosure Agreements in Colombia

The management of intellectual property (IP) agreements in universities continues to rely on static legal documents that are signed, archived, and consulted when necessary, but whose content is rarely formalized to facilitate their operation and verification. Consequently, obligations, permissions, restrictions, deadlines, scopes, and exceptions often remain scattered across clauses drafted in natural language, annexes, emails, and different document versions, which hinders their monitoring and makes compliance review dependent on intensive legal and administrative work. In response to this limitation, this article proposes an ontology to formalize non-disclosure agreements (NDAs) at the University of Caldas, Colombia, understood as a specific case within the broader management of IP agreements. The proposal adopts a modular Semantic Web architecture composed of a reusable ontological core and a specialized profile for NDAs. Its construction followed the METHONTOLOGY methodology, and its specification was supported by Competency Questions (CQs), which were subsequently translated into SHACL constraints and SPARQL queries. In addition, a SKOS vocabulary is incorporated to normalize synonyms and terminological variants typical of legal drafting in Spanish, together with a lightweight weak supervision layer based on regular expressions, SKOS, and structural signals to support clause labeling and the batch generation of RDF instances. Thus, the proposal enables querying, traceability, and verification over NDA content, while offering a formal basis for progressing toward automatable controls and their eventual articulation with smart contracts.

Building interoperability across borders: a linked open metadata framework for an ASEAN GLAM aggregation platform

This study develops and evaluates an integrated Linked Open Metadata (LOM) framework for an ASEAN Galleries, Libraries, Archives, and Museums (GLAM) aggregation platform. Using a qualitative, exploratory design with a documented coding protocol, the study synthesises practices from Europeana, the Digital Public Library of America (DPLA), and Trove, and contextualises them within ASEAN’s socio-technical landscape. A hub-and-spoke prototype was built with a curated set of 100 records from ten ASEAN member states, aligned to Dublin Core, EDM and CIDOC CRM, exposed via OAI-PMH, and evaluated using a Normalised Open Access Performance Index. Results show functional OAI-PMH compliance, a 25 percentage-point improvement in metadata alignment accuracy after semantic enrichment, and demonstrable cross-border discoverability across four languages. Findings position aggregation as a socio-technical governance problem and provide a transferable framework for regions with heterogeneous institutional capacity and multilingual heritage descriptions.

Structural Digital Twin-Driven Conformance Assessment of LegalTech Governance Ontology: Reproducible Proof of Concept

The increasing convergence of enterprise architecture and IT governance frameworks, such as TOGAF 9.2, COBIT 5, and NIST CSF 1.1, with LegalTech regulations including GDPR 2016/679, eIDAS 910/2014, and NIS2 2022/2555, has created a growing need for rigorous and automated governance-validation mechanisms. However, to date, no formal approach exists to assess semantic conformance between a normative ontological model and its operational implementation in microservice-based systems, leaving critical governance gaps difficult to detect in legally sensitive environments. This paper proposes MALTG (Multidimensional Architecture for LegalTech Governance), a configurable and reusable formal framework that combines OWL 2 ontology engineering, a JSON-LD-based SDT (Structural Digital Twin), semantic conformance mapping, a hierarchical coverage function, and a conformance gap metric to support automated governance assessment and prioritised remediation. The framework accepts any organisational architecture as input, enabling application to arbitrary LegalTech case studies by replacing the reference SDT. The proposed framework models nine governance dimensions through an ontology of 59 classes and 15 properties and validates them against a semi-real, public-source SDT composed of 39 microservice components and 54 directed connections. The reference SDT was populated through an ontology-driven data-collectionprocess: a scraping campaign guided by the MALTG ontology (data/MALTG_Ontology.owl) harvested public information from the official portal of Ecuador’s Council of the Judiciary (Consejo de la Judicatura, CJ)—probing its technological-maturity level and digital-governance compliance—which was condensed into a single JSON-LD artefact, enforcing domain rigour and traceability on the search for LegalTech governance evidence. Experimental results demonstrated an overall ontological score of 82.6 and an SDT score of 73.7, with a mean conformance gap of 8.9. Five dimensions achieved full conformance, while the LegalTech dimension presented the largest gap. Graph-theoretic validation further confirmed monotonic improvement throughout the remediation sequence. Overall, the findings suggest that MALTG provides a formally grounded and reproducible approach for automating multi-framework LegalTech governance conformance assessment while maintaining semantic and structural traceability between normative models and operational architectures. As a proof of concept, this validation relies on a configurable, ontology-driven public-source (semi-real) SDT; external validity in real production LegalTech organisations remains untested and is left for future work.

Serving FAIR Semantic Artefacts: A Review of Semantic Artefact Catalogues