2nd Workshop KG4SDSE at CAiSE2024
Knowledge Graphs for Semantics-driven Systems Engineering (Workshop@CAiSE24)
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.
Relevant Topics
- 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
Workshop Chairs
- Robert Buchmann (robert.buchmann@ubbcluj.ro), Babeș-Bolyai University, Romania
- Dimitris Karagiannis (dk@dke.univie.ac.at), University of Vienna, Austria
- Dimitris Plexousakis (dp@ics.forth.gr), Institute of Computer Science, FORTH and University of Crete, Greece
Web Presence Chair
Iulia Vaidian (iulia.vaidian@omilab.org), OMiLAB NPO/University of Vienna, Austria
Workshop Program Committee
- Nick Bassiliades, Aristotle University of Thessaloniki, Greece
- Sjaak Brinkkemper, Utrecht University, The Netherlands
- Michael Fellmann, University of Rostock, Germany
- Hans-Georg Fill, University of Fribourg, Switzerland
- Aurona Gerber, University of Pretoria, South Africa
- Ana-Maria Ghiran, Babeș-Bolyai University, Romania
- Adrian Groza, Technical University of Cluj-Napoca, Romania
- Marite Kirikova, Riga Technical University, Latvia
- Manolis Koubarakis, National and Kapodistrian University of Athens, Greece
- Ana León, Universitat Politècnica de València, Spain
- Andreas Opdahl, University of Bergen, Norway
- Andrea Polini, University of Camerino, Italy
- Achim Reiz, University of Rostock, Germany
- Ben Roelens, Open University, The Netherlands
- Anisa Rula, University of Brescia, Italy
- Maribel Yasmina Santos, University of Minho, Portugal
- Alberto Rodrigues da Silva, University of Lisbon, Portugal
- Takahira Yamaguchi, Keio University, Japan
Contact
kgworkshop@omilab.orgSponsored by
and 
Registration
Please register via the organizer.
Agenda
09:00 - 09:20:
Opening. Chair's Welcome Message
09:20 - 10:20:
Keynote - Neuro-Coachable AI is the Answer! What is the Question?
10:30 - 11:00:
Coffee Break
11:00 - 11:25:
LLMs for Knowledge-Graphs enhanced Task-Oriented Dialogue Systems - Challenges and Opportunities
11:25 - 11:50:
An Ontology Based Meta-modelling Approach for Semantic-Driven Building Management Systems
11:50 - 12:15:
Understanding the SQL Semantic Transducer
12:30 - 14:00:
Lunch Break
14:00 - 14:25:
Knowledge Graph for Reusing Research Knowledge on Related Works in Data Analytics
14:25 - 14:50:
Improving the Service Quality in Fitness Industry by Using a Knowledge Graph based Modeling Toolkit
14:50 - 15:05:
Property Graphs at Scale - A Roadmap and Vision for the Future
15:05 - 15:20:
Enhancing Complex Linguistic Tasks Resolution through Fine-tuning LLMs, RAG and Knowledge Graphs
15:30 - 16:00:
Coffee break
16:00 - 17:00:
Metamodeling and Abstraction in the Era of LLMs - Challenges and Opportunities