Call for presentations: KGs operated by AI | DBpedia Day @ SEMANTiCS 2024

Dear all,

we are happy to announce that we will organize a DBpedia Meeting in Amsterdam, Netherlands. The DBpedia Day is part of the SEMANTiCS, Sep 17-19, and will be held on the first day of the conference on 17th of September 2024.

We invite the world’s leading Knowledge Engineering experts to gain insights on the topic “Knowledge Graphs operated by AI”. This event aims to explore how recent advances in AI can leverage and exploit structured knowledge, as well as address new challenges and necessary changes to advance the vision of “Knowledge Graphs operated by AI”.

DBpedia, as one of the first open knowledge graphs since 2007, has significantly influenced and shaped existing standards. As a community, we should now work together to reap the benefits of the available structured knowledge. New opportunities are developing via recent advances in AI, and we seek input on leveraging this technology, as well as an open discussion on the challenges and necessary changes to further the vision of AI-operated Knowledge Graphs.

Deadline for abstract submission (300 words): July 1st, 2024
Online Call:

Topics include (but are not limited to):

Standards and Best Practices

  • Streamlining consumption by AI: Proposing changes and frameworks to improve the current Linked Data and Knowledge Graph infrastructure.
  • Discovery, summarization, and efficient data retrieval methods.
  • REST/HATEAOS, Structured Data Islands/JSON-LD, 303-less Linked Data.
  • Metadata standards for better linking, integration, and interoperability.
  • Development and enhancement of Ontologies and Mappings to facilitate the integration of knowledge from distributed sources.

Exploration and Querying

  • Building novel AI-driven interfaces using natural language processing.
  • Automatically generating SPARQL queries from natural language inputs.
  • Integrating secure knowledge in Generative AI systems.

Acquiring Knowledge

  • Methods for AI to autonomously discover and integrate new data sources.
  • Leveraging machine learning techniques for the automated extraction of knowledge from unstructured data.
  • Enhancing knowledge bases with real-time data updates and corrections.

Coordinating Knowledge

  • Frameworks and protocols for the coordination of knowledge across distributed systems.
  • AI-driven methods for ensuring data consistency and integrity.
  • Utilizing blockchain and other technologies for secure and transparent knowledge coordination.

Managing Knowledge

  • Strategies for maintaining and updating knowledge graphs using AI.
  • AI-driven validation and verification of knowledge to ensure accuracy and relevance.
  • Techniques for scalable storage and retrieval of vast amounts of structured data.

Ethical and Societal Implications

  • Addressing privacy and security concerns in AI-operated knowledge graphs.
  • Ensuring transparency and explainability in AI’s use of knowledge graphs.
  • Understanding the societal impact of AI-driven knowledge management and dissemination.

Use Cases and Applications

  • Real-world examples of AI leveraging knowledge graphs for various applications.
  • Case studies on the success and challenges of implementing AI-driven knowledge management systems.
  • Innovative applications in healthcare, finance, education, and other sectors.

Submission Guidelines

Please submit your presentation proposals by Monday July 1st, 2024, (Anywhere On Earth; UTC-12) to Proposals should include a title, abstract (300 words max), and a brief biography of the presenter(s).

Abstracts will be evaluated based on establishing a strong relation to the call and its topics. While we generally welcome mature and well-engineered showcases and implementations, we will accept some talks with idea, position or impulse character. Additionally, we will positively evaluate industry talks that describe needs and requirements.

For further details, visit our website

We are looking forward to meeting you.

Kind regards,

Sebastian Hellmann

on behalf of the DBpedia Association