KG4SDSE Workshop Description
The goal of this workshop is to stimulate research and experience reports on how Knowledge Graphs can add context and flexibility to information systems, compensating for the semantic loss of system design methods or for the logical flaws of large language models, ultimately enabling semantic enrichment and reasoning capabilities in information systems operation or engineering processes.
Knowledge Graphs have been primarily investigated as engineered artifacts by themselves – from their underlying formalisms (e.g. description logics), enabling technologies (e.g. RDF, LPG) to their knowledge management capabilities. With this workshop we aim to shift focus from what Knowledge Graphs are, or how they can be built, towards how they can be relevant to Information Systems engineering. We also aim to investigate their place in the Conceptual Modeling paradigm - specifically how Knowledge Graphs enable new flavors of model-driven engineering or low-code engineering -, as well as their interplay with Large Language Models or Machine Learning for systems engineering purposes.
Various stages of research progress can be reported in the workshop contributions - from position and vision papers to experience reports and full research papers.
- Systems Engineering benefits of the interplay between Knowledge Graphs and Large Language Models
- Knowledge Graphs for enhancing Large Language Models or their prompting
- Large Language Models for populating or refining Knowledge Graphs
- Information Systems engineering methods based on Knowledge Graphs
- Application scenarios for Knowledge Graphs
- Knowledge Graphs as mediators between data, stakeholders and software
- Knowledge Graphs for model-driven engineering
- Linking, transforming or augmenting domain-specific models with Knowledge Graphs
- Knowledge Graphs informed by system theories and system engineering conceptualizations
- Knowledge Graph embeddings and graph neural networks
- Requirements engineering based on Knowledge Graphs
- System design and analysis augmented by Knowledge Graphs
- Knowledge Graphs for Digital Twins and digital-first artifacts
- Human-oriented low-code Knowledge Graph building
- Empirical studies and experience reports on Knowledge Graph-based information systems
Web Presence Chair
Iulia Vaidian (email@example.com), OMiLAB NPO/University of Vienna, Austria
Workshop Program Committee
To be announced soon.
Submission link (pick the KG4SDSE workshop from the tracks listed there): https://easychair.org/conferences/?conf=caise2024
We invite two types of paper contributions:
- Full papers which can be regular research or experience papers (10-12 pages)
- Short papers which can be position or vision papers (6-9 pages)
Since we plan have the accepted papers in CAiSE’s LNBIP volume for workshops, formatting must comply with the Springer proceedings guidelines available at https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
(both Word and Latex templates are available there).
All accepted papers will have to be presented in person by one registered author. Accepted papers that will not presented will be removed from the workshop proceedings.