The Journal on Data Semantics focuses on the formal representation and semantic interpretation of data. It explores methods for generating queries based on ontologies and semantic coverage, and investigates challenges in transforming natural language to structured queries for knowledge graphs. The journal also examines the application of data-driven models and machine learning for automating business processes, managing complaints, and executing knowledge-intensive processes, often leveraging ontologies and formal semantics.
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Publication & Citation Trend
Articles published
Times cited
2014
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2021
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Artificial IntelligenceQ3
Computer Networks and CommunicationsQ3
Information SystemsQ3
Subject Classification
Scopus Categories
Information SystemsComputer Networks and CommunicationsArtificial Intelligence
Research Topics (OpenAlex)
Semantic Web and OntologiesService-Oriented Architecture and Web ServicesAdvanced Database Systems and QueriesBusiness Process Modeling and AnalysisData Quality and ManagementData Management and AlgorithmsBiomedical Text Mining and OntologiesWeb Data Mining and AnalysisNatural Language Processing TechniquesGeographic Information Systems Studies