This workshop aims at addressing challenges and issues on managing Knowledge Graph evolution and preservation by providing a forum for researchers and practitioners to discuss, exchange and disseminate their ideas and work, to network and cross-fertilise new ideas.


Topics of interest include, but are not limited to themes related to the evolution and preservation of Knowledge Graphs:

    •   Management and Governance of Evolution in Knowledge Graphs
        • Representation and maintenance of versions and changes (change representation, change detection)
        • Efficient indexing and update of Knowledge Graphs
        • Synchronization of distributed versions
      • Federated Knowledge Graph governance
    • Reasoning and Prediction over Evolving Knowledge Graphs
        • Techniques for extracting and predicting evolving patterns
        • Maintenance of explicit and implicit knowledge
        • Trend analysis of evolving knowledge graphs
      • Concept drift detection and prediction over knowledge graphs
    • Visualization and Exploration of Evolving Knowledge Graphs
        • Visualizing trends
        • Visual summarization of evolving knowledge
        • User interfaces for exploring evolving knowledge graphs
      • Visualisation of quality in knowledge graphs 
    • Preservation of Evolving Knowledge Graphs
        • Digital preservation
        • Preservation of context, provenance and background knowledge
        • Efficient and effective solutions for preserving evolving knowledge graphs
      • Models for representing provenance and evolution
  • Quality of Evolving Knowledge Graphs
    • Quality assessment and validation
    • Machine Learning based quality assessment
    • Quality trends and prediction in evolving knowledge graphs
    • Hybrid approaches for knowledge graph curation
  • Evaluation of Knowledge Graph Evolution
      • Benchmarks for managing, predicting, and curating evolution
      • Real-world applications of evolving knowledge graphs
      • Automatic and human-based techniques for evaluating evolving knowledge graph
    • Creation of training datasets for evaluation of evolving knowledge graphs

Submission guideline

We envision four types of submissions in order to cover the entire spectrum from mature research papers to novel ideas/datasets and industry technical talks:

  1. Research Papers (max 10 pages), presenting novel scientific research addressing the topics of the workshop.
  2. Resource Papers (max 10 pages), presenting functional systems or datasets relevant to the community.
  3. Position Papers, Demo papers and System and Dataset descriptions (max 5 pages), encouraging papers describing significant work in progress, late breaking results or ideas of the domain, as well as functional systems or datasets relevant to the community.
  4. Industry & Use Case Presentations (max 5 pages), in which industry experts can present and discuss practical solutions, use case prototypes, best practices, etc., in any stage of implementation.
  5. (NEW!) Expression of Interest (max 2 pages), presenting a research topic, a work in progress, practical applications or needs, etc.

The proceedings of the workshops will be published jointly with the conference proceedings. Papers must be submitted in PDF according to the ACM format published in the ACM guidelines (, selecting the generic “sigconf” sample. The PDF files must have all non-standard fonts embedded. Workshop papers must be self-contained and in English.

All papers should be submitted to

Best paper award

We will provide an award for the best research paper submitted. Selection criteria include the innovative nature of work, the importance and timeliness of the topic, and the overall readiness and quality of the writing.