Call for Papers

Conceptual Modeling, AI, and Beyond

As AI and ML reshape technology, they're also revolutionizing conceptual modeling. We call for papers exploring this change, particularly how AI and ML integrate with and expand conceptual modeling. Submissions should cover established topics like modeling languages, theories, and methods, as well as AI/ML's novel contributions to the field. We encourage papers that push the boundaries of conceptual modeling and demonstrate AI/ML's transformative effects. Contributions should reflect the current state and forecast the future of conceptual modeling, setting the stage for pioneering research. We also invite industry reports, vision papers, and additional “hackathon” papers.

Important Dates

All deadlines are 23:59 AoE (Anywhere on Earth)

Full paper abstracts submission (mandatory)
19 May 2024

Topics of Interest (Not Limited to the Following)

Foundations of conceptual modeling

Automated and AI-assisted conceptual modeling
Complexity management of large conceptual models
Concept formalization, including data manipulation languages and techniques, formal concept analysis, and integrity constraints
Domain-specific modeling
Discovery of models, (anti-)patterns, and structures
Evolution, exchange, integration and transformation of models
Justification and evaluation of models
Logic-based knowledge representation and reasoning
Multi-level and multi-perspective modeling
Ontological and cognitive foundations
Quality paradigms and metrics
Semantics in conceptual modeling
Theories and methodologies for conceptual modeling
Verification and validation of conceptual models

Conceptual modeling in

Business, climate, compliance, economics, education, energy, entertainment, government, health, law, sustainability, etc.
Collaboration, crowdsourcing, games, and social networks
Engineering, such as agile development, requirements engineering, reverse engineering
Enterprises, including the modeling of business rules, capabilities, goals, services, processes, and values
Ethics, fairness, responsibility, or trust
Digital twins, fog and edge computing, Industry 4.0, internet of things
Information classification, filtering, retrieval, summarization, and visualization
Scientific data management, including FAIR practices

Conceptual modeling showcased by

Computational tools that advance the state-of-the-art
Empirical studies
Experience reports of applications, use cases, and real-world impact

Conceptual modeling for AI and ML

Generative AI & Conceptual Modeling
AI, data mining, data science, machine learning, or statistics
Domain knowledge representation and understanding for ML training
Data engineering and domain knowledge engineering for ML training
Data quality assurance, compliance, and governance
Conceptual modeling and Explainable AI
Development of large-language models, foundation models, and federated learning
Modeling of relational machine learning incl. graph neural networks, inductive logic programming, and statistical relational learning

Conceptual modeling for

Data access, acquisition, integration, maintenance, preparation, transformation, and visualization
Data management, including database design, performance optimization, privacy and security, provenance, transactions, queries
Data value, variety, velocity, veracity, volume, and other dimensions
Distributed, decentralized, ledger-based, parallel and P2P databases
Graph and network databases
Object-oriented and object-relational databases
SQL, NewSQL and NoSQL databases
Spatial and temporal databases
Event-based and stream architectures
Multimedia and text databases
Approximate, probabilistic, and uncertain databases
Web, Semantic Web, knowledge graphs, and cloud databases
Other data spaces

Submission Guidelines

Submit papers via EasyChair for ER 2024 to the “ER 2024 Full Papers” track.

Since the proceedings will be published by Springer in the LNCS series, authors must submit manuscripts using the LNCS style or Overleaf. The page limit is 16 pages (excluding references). Papers will be judged on contribution, literature basis, novelty, clarity, relevance, and rigor. Other types of submissions include: workshops, posters, forum papers, project exhibitions, and hackathon proposals. The review process is double-blind. Submissions must be anonymized.

Post-Conference Special Journal Issue

The authors of selected papers will be invited to prepare a substantially revised and extended version to a special issue in Elsevier’s Data & Knowledge Engineering.