Call for Papers

(Here we provide the Regular Call for Papers. See also a list of Special Issues open for submissions.)

Transactions on Graph Data and Knowledge is an Open Access journal that publishes research contributions relating to the use of graphs for data and knowledge management. Such contributions may be experimental or theoretical in nature, where submissions that combine both aspects are particularly welcome. The journal thus welcomes submissions from research communities – such as Graph Analytics and Algorithms, Graph Databases, Graph Representation Learning, Knowledge Graphs, Semantic Web – that provide novel insights into the use of graphs for generating, representing and managing data and knowledge. Likewise contributions relating to the use of graphs in the context of Big Data, Data Integration, Data Science, Information Extraction, Information Retrieval, Knowledge Representation, Machine Learning, Natural Language Processing, etc., are welcome.

Submissions will be judged based on novelty, technical correctness, technical depth, readability, reproducibility, relevance to the scope, and potential for impact and follow-up research.

Topics in-scope for the journal include, but are not limited to, research relating to graph data & knowledge in the context of:

• Graph Database Management Systems
  • Graph Storage & Indexing
  • Graph Query Processing & Query Optimizations
  • Graph Query Languages
  • Graph Database Theory
  • Graph Schema and Constraint Languages
  • Graph Database Security, Privacy & Access Control
  • Distributed/Federated Graph Queries
  • Evolution and Dynamics of Graph Databases
  • Analytics for Graph Databases
• Semantic Web
  • Web Data Integration
  • Linked Data & Vocabularies
  • RDF-based Data Management
  • Ontology & Rule Languages
  • Ontology Engineering
  • Ontology & Entity Alignment
  • Validating Graph Data
  • Data Interoperability
  • Web Services
• Graph-based Learning
  • Graph Representation Learning
  • Knowledge Graph Embeddings
  • Generative Graph Models
  • Learning in Graph Databases
  • Neuro–Symbolic Models
  • Natural Language Processing & Generation
  • Large Language Models meet Graphs
  • Multi-Modal Representations
  • Agent-based Systems
  • Graph-based Explainable AI
  • Theory of Graph-based Learning & AI
• Knowledge Graphs
  • Knowledge Graph Construction
  • Knowledge Graph Completion & Curation
  • Knowledge Graph Management
  • Knowledge Graph Summarisation
  • Knowledge Graph Interfaces
  • Knowledge Graph Exploration
  • Knowledge Graph Question Answering
  • Personal Knowledge Graphs
  • Contextual Knowledge Graphs
  • Knowledge Graph Interoperability & Alignment
  • Access, Privacy, Security
  • Graph Algorithms & Theory for Knowledge Graphs
• Knowledge Representation
  • Formal Logics & Languages
  • Reasoning Algorithms
  • Contextual Semantics
  • Uncertain or Conflicting Knowledge
  • Evolving & Dynamic Knowledge
  • Stream Reasoning
  • Theory of Knowledge Representation
• Ordinal Structures
  • Ontologies & Taxonomies
  • Ontology Learning
  • Mining Directed Acyclic Graphs
  • Knowledge Discovery & Machine Learning on Ordinal Data
  • Formal Concept Analysis
  • Graph-based Conceptual Modelling
• Applications of Graph Data & Knowledge
  • Bibliometrics & Libraries
  • Big Data
  • Commerce & Manufacturing
  • Cultural Heritage
  • Data Integration & Enrichment
  • Data Science
  • Education
  • FAIR & Open Science
  • Finance
  • Geospatial Systems
  • Government
  • Information Extraction & Retrieval
  • Law & Compliance
  • Life Sciences
  • Mobile & Personal Technologies
  • Multimedia & Multi-modal Data
  • Network Analysis
  • Social Sciences & Media
  • Streams, Sensors & Internet of Things
  • User Interfaces and Accessibility
  • The Web

Submissions on other research topics where graphs play a central role as a representation for data or knowledge are also welcome. The journal also welcomes submission of high-quality survey papers on the aforementioned topics.

As a Diamond Open Access journal, official versions of accepted papers (as accessible via DOI) are published and made available for free online without fees for authors nor readers.