Journal on Data Semantics

Aims & Scope

The Journal on Data Semantics (JoDS) provides an international high-quality publication venue for researchers whose themes cover issues related to information semantics.

Its target domain ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge, thus covering work done on conceptual modeling, databases, Semantic Web, information systems, workflow and process modeling, ontologies, business intelligence, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, and artificial intelligence.

Topics of relevance to this journal include (but are not limited to): Conceptualization, knowledge representation and reasoning, Conceptual data, process, workflow, and event modeling, Provenance, evolution and change management, Context and context-dependent representations and processing, Multi-model and multi-paradigm approaches, Mappings, transformations, reverse engineering and semantic elicitation, Semantic interoperability, semantic mediators and metadata management, Ontology models and languages, ontology-driven applications, Ontology, schema, data and process integration, reconciliation and alignment, Web semantics and semi-structured data, Integrity description and handling, Semantics in data mining and knowledge extraction, Semantics in business intelligence, analytics and data visualization, Spatial, temporal, multimedia and multimodal semantics, Semantic mobility data and services for mobile users, Supporting tools and applications of semantic-driven approaches.

View Aims & Scope

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Metrics & Ranking

Journal Rank

Year	Value
2024	15680

Journal Citation Indicator

Year	Value
2024	32

SJR (SCImago Journal Rank)

Year	Value
2024	0.332

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	21

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

  Citation: 228

  Authors: Claudio, Andrea, Alessandro

• Content-Based Video Recommendation System Based on Stylistic Visual Features

  Citation: 174

  Authors: Yashar, Mehdi, Paolo, Franca, Pietro, Massimo

• Multi-Dimensional Event Data in Graph Databases

  Citation: 70

  Authors: Stefan, Dirk

• Mapping between RDF and XML with XSPARQL

  Citation: 70

  Authors: Stefan, Stefan, Thomas, Nuno, Axel

• Big Data Semantics

  Citation: 51

  Authors: Paolo, Antonia, Marco, Tiziana, Philippe, Ernesto, Alexandra, Maurice, Mustafa, Giuseppe, Kai-Uwe, Monica, Manuel, Robert, Fadi

• Automated Planning for Business Process Management

  Citation: 51

  Authors: Andrea

• Ontology Integration for Linked Data

  Citation: 44

  Authors: Lihua, Ryutaro

• On Link Discovery using a Hybrid Approach

  Citation: 37

  Authors: Axel-Cyrille

• Declarative and Hybrid Process Discovery: Recent Advances and Open Challenges

  Citation: 32

  Authors: Tijs

• Assessing and Improving the Quality of SKOS Vocabularies

  Citation: 30

  Authors: Osma, Christian

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