Chapter RDF
pages:- Semantic and Knowledge Engineering Using ENVRI RM
 - Semantic Data Integration of Big Biomedical Data for Supporting Personalised Medicine
 - Semantic Data Integration Techniques for Transforming Big Biomedical Data into Actionable Knowledge
 - Semantic Integration and Interoperability
 - Semantic Representation of Physics Research Data
 - Semantic Representation of Scientific Publications
 - Semantically Describing Predictive Models for Interpretable Insights into Lung Cancer Relapse
 - Semantische Mashups auf Basis Vernetzter Daten
 - SemEval-2021 Task 11: NLPContributionGraph - Structuring Scholarly NLP Contributions for a Research Knowledge Graph
 - Semi-supervised Human Pose Estimation in Art-historical Images
 - SemLAV: Local-As-View Mediation for SPARQL Queries
 - SemLAV: Querying Deep Web and Linked Open Data with SPARQL
 - SemMatch: Semantics-Aware Matching for Causal Inference over Knowledge Graphs
 - SEO: A Scientific Events Data Model
 - SerVCS: Serialization Agnostic Ontology Development in Distributed Settings
 - SHACL Constraint Validation during SPARQL Query Processing
 - SHACL-ACL: Access Control with SHACL
 - Simulation of the measurement of the impedance of aqueous droplets in segmented flow
 - SlideImages: A Dataset for Educational Image Classification
 - SlideWiki – Towards a Collaborative and Accessible Platform for Slide Presentations
 - SmartReviews: Towards Human- and Machine-Actionable Representation of Review Articles
 - SmartReviews: Towards Human- and Machine-Actionable Reviews
 - SMS question-answer system
 - SoccerNet 2022 Challenges Results
 - Software Citation Needed — Infrastructure Remixing
 - Software Professionals’ Attitudes Towards Video as a Medium in Requirements Engineering
 - Source selection and ranking in the websemantics architecture using quality of data metadata
 - SPaRKLE : Symbolic caPtuRing of knowledge for Knowledge graph enrichment with LEarning
 - Speicherung & Datenverwaltung in Produktion und Archiv
 - Squerall: Virtual Ontology-Based Access to Heterogeneous and Large Data Sources