Call for Papers

Note: We are aiming to start to accept submissions in mid-2023.

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:

• Knowledge Graphs
  • KG construction
  • KG completion & curation
  • KG management
• Semantic Web
  • RDF-based data management
  • Ontologies for graphs
  • Rules for graphs
  • Validating graph data
  • Linked Data
• Knowledge Representation
  • Formal logics and languages
  • Reasoning and inference
  • Representing context and its semantics
  • Numeric vs. symbolic representations
• Graph Databases
  • Graph query languages
  • Indexing graphs
  • Optimizations for graph queries
• Graph Representation Learning
  • Knowledge graph embeddings
  • Graph neural networks
  • Generative graph models
• Graph Analytics and Algorithms
  • Centrality measures
  • Community detection
  • Frameworks and languages for graph analytics
• Graphs for:
  • Big Data
  • Data Integration
  • Data Science
  • Information Extraction
  • Information Retrieval
  • Machine Learning
  • Natural Language Processing
  • 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.