Data-driven discovery, interdisciplinary collaboration, and digital twins are transforming research and practice. The ability to semantically organize, integrate, and consume metadata of Digital Twin Objects (DTOs) is a critical skill for researchers, academics, and professionals.
The overall learning goal of this course is to develop the skills and understanding necessary to enhance the (meta)data of DTO datasets for downstream enrichment, such as advanced analytics, inter-linkage, and consumption through semantically-enabled tools and services provided by SemFlow.The semantic uplift of DTO metadata will unlock new downstream functionalities, enabling users to explore and discover datasets via a faceted, semantic search interface that guides compliance with any metadata standard, including INSPIRE.
This course leverages SemFlow (SemanticFlow Knowledge Hub) and its companion browser extension, SemLinked, to guide participants through principles and practices of building, managing, and consuming an online Body of Knowledge (BoK) tailored to DTO metadata enrichment. Through a blend of conceptual foundations, hands-on tool demonstrations, and real-world case studies, learners will gain practical experience in generating domain-specific corpora, defining and mapping concepts using ontological approaches, and creating interconnected knowledge graphs. Advanced topics include fine-tuning language models with BoK-derived corpora, integrating semantic models into data-processing workflows for DTO analytics, and developing downstream semantic services that expose enriched metadata for discovery and interoperability.
The course is intended for:
Researchers and Academics: Seeking to organize and interlink literature, methodologies, and datasets across emerging or interdisciplinary fields.
Professionals and Practitioners: Engaged in domains where data integration, knowledge management, or policy impact analysis is critical (e.g., environmental sciences, maritime management, digital humanities, health informatics).
Knowledge Engineers and Data Scientists: Interested in ontologies, knowledge graphs, semantic web technologies, and applying Large Language Models (LLMs) for corpus-driven model fine-tuning.
Technology Leads and Project Managers: Responsible for guiding teams toward interoperable data architectures, semantic standards compliance, and efficient knowledge reuse.
Keywords: knowledge management, visual “mind-mapping canvas”, NLP, LLM, interoperability-by-design, cross-domain, Marine Management and Innovation
Author(s): V. Venus, F. Wahyudi, P. Muchada, F. Kurniawan
Affiliation: RAMANI, ILIAD-project