ER 2024 Co-Located Workshops
Continuing a long tradition, ER 2024 will host multiple workshops on cutting-edge topics to be held in conjunction with the main ER 2024 conference. The workshops will serve as an intensive collaborative forum for exchanging innovative ideas about conceptual modeling, and for discovering new frontiers for its use. The following workshops focus on new, emerging, or established topics in conceptual modeling, or its application in specific domains.
All workshop papers must be submitted to EasyChair. Details for Call for Workshop Papers for each workshop are available below. Scroll down further to see each workshop’s description or click the following links to see their individual call for papers as downloadable PDFs.
- The 5th International Workshop on Conceptual Modeling for Life Sciences (CMLS)
- 5th International Workshop on Quality and Measurement of Model-Driven Software Development (QUAMES 2024)
- 3rd International Workshop on Digital JUStice, Digital Law and Conceptual MODeling (JUSMOD24)
- 7th International Workshop on Empirical Methods in Conceptual Modeling (EmpER’24)
- 2nd Workshop on Modeling in the Age of Large Language Models (LLM4Modeling)
- II Workshop on Conceptual Modeling, Semantic Technologies and Data Platforms for Smart Food Systems (SmartFood)
- The First International Workshop on AI Services and Applications (AISA’2024)
- The First International Workshop on AI-Driven Modeling and Management of Data (AIMM 2024)
- Special Workshops (Invitation Only)
Important Dates*
All deadlines are 23:59 AoE (Anywhere on Earth)
Intention to Submit Proposal
Closed
Workshop Abstract Submission (optional)
13 July 2024
*Since iStar'24 workshop plans to publish all its accepted papers in the CEUR proceedings, it has different important dates. Please see the details on its website.
Accepted Workshops
Find below the list of accepted workshops at ER 2024. To submit a proposal, please click on the link on the workshop of your choice. All proposals must be submitted to EasyChair.
The 5th International Workshop on Conceptual Modeling for Life Sciences (CMLS)
The recent advances in unraveling the secrets of human conditions and diseases have encouraged new paradigms for their prevention, diagnosis, and treatment. As information is increasing at an unprecedented rate, it directly impacts the design and future development of information and data management pipelines; thus, new ways of processing data, information, and knowledge in healthcare environments are strongly needed.
This workshop aims to continue being a meeting point for Information Systems (IS), Conceptual Modeling (CM), Data Management (DM), and Artificial Intelligence (AI) researchers working on health care and life science problems. It is also an opportunity to share, discuss, and find new approaches to improve promising fields, with a special focus on Genomic Data Management – how to use the information from the genome to better understand biological and clinical features – and Precision Medicine – giving each patient an individualized treatment by understanding the peculiar aspects of the disease.
From the precise ontological characterization of the components involved in complex biological systems to the modeling of the operational processes and decision support methods used in the diagnosis and prevention of diseases, the joined research communities of IS, CM, DM, and AI have an important role to play; they must help in providing feasible solutions for high-quality and efficient health care. CMLS aims to become a forum for discussing the responsibility of the conceptual modeling community in supporting the life sciences related to these new realities.
5th International Workshop on Quality and Measurement of Model-Driven Software Development (QUAMES 2024)
The success of software development projects depends on the productivity of human resources and the efficiency of development processes to deliver high quality products. Model-driven development (MDD) is a widely adopted paradigm that automates software generation by means of model transformations and reuse of development knowledge. The MDD advantages have motivated the emergence of several modeling proposals and MDD tools related to different application domains and stages of the development lifecycle.
In MDD, the quality of conceptual models is critical because it directly impacts the final software systems' quality. Therefore, it is essential to evaluate conceptual models and predict the software products' relevant characteristics. Additionally, MDD project management must be adapted to take into account that programming effort is being replaced by a modelling effort at an earlier stage. Hence, measuring models is crucial to support cost estimation and project management.
To address these challenges, QUAMES aims to attract research on methods, procedures, techniques, and tools for measuring and evaluating the quality of conceptual models that can be used in MDD environments. Its primary goal is to enable the development of high-quality software systems by promoting quality assurance in the modeling process.
3rd International Workshop on Digital JUStice, Digital Law and Conceptual MODeling (JUSMOD24)
Law plays a crucial role in almost every aspect of our both public and private life. Thousands of legal documents are constantly produced by institutional bodies, such as Parliaments and Courts, which constitute a prominent source of information and knowledge for judges, lawyers, and other professionals involved in legal decision-making. To cope with growing volume, complexity, and articulation of legal documents as well as to foster digital justice and digital law, increasing effort is being devoted to digital transformation processes in the legal domain.
Conceptual Modeling (CM) plays a crucial role in this scenario to formalize entities, its features, and its relations. Also, conceptual modeling joined with well-founded ontologies has been used to harmonize different terminologies used in legal documents as well as to promote the development and the adoption of shared vocabularies and open linked data in legislation, case-law, and other relevant legal information. Furthermore, advanced functionalities for legal data and process modeling and management are advocated, embracing modern technologies like Semantic Web, NLP, AI, to enable semantic text search and exploration, legal knowledge extraction and formalization, legal decision-making and legal analytics.
This workshop aims to constitute a meeting venue for a variety of researchers involved in digital justice and digital law, originating a rich community crossing different disciplines besides computer science, such as law, legal informatics, management, economics and social sciences. The workshop will provide an opportunity to share, discuss, and identify new approaches and solutions for modeling, analysis, formalization, and interpretation of legal data and related processes.
7th International Workshop on Empirical Methods in Conceptual Modeling (EmpER’24)
Conceptual modeling has enjoyed substantial growth over the past decades in diverse fields such as Information Systems Analysis, Software Engineering, Enterprise Architecture, Business Analysis and Business Process Engineering. A plethora of conceptual modeling languages, and frameworks have been proposed promising to facilitate activities such as communication, design, documentation or decision-making. Success in designing a conceptual modeling language, framework, or tool is, however, predicated on demonstrably attaining such goals through observing their use in practical scenarios. At the same time, the way individuals and groups produce and consume models gives rise to cognitive, behavioral, organizational or other phenomena, whose systematic observation may help us better understand how models are used in practice and how we can make them more effective.
Furthermore, the act of building conceptual models is ideally informed by empirical evidence that is nowadays abundant in the form of digital data. This overabundance of data, combined with the advent of advanced data analysis and artificial intelligence (AI) techniques, introduces major opportunities and challenges in an empirically-informed conceptual modeling practice.
In this workshop, we aim at bringing together researchers with an interest in the empirical investigation of conceptual modeling languages, frameworks, tools, methods, and practices as well as the study of a data-driven, evidence-based conceptual modelling practice. The workshop invites reports on specific finished, on-going or proposed empirical studies, theoretical, review and experience papers about empirical research in conceptual modeling or technical contributions and studies on empirical (data-driven, evidence-based) conceptual modeling.
2nd Workshop on Modeling in the Age of Large Language Models (LLM4Modeling)
Submit a paper for LLM4Modeling
Large language models (LLM) have received enormous attention in practice and science since ChatGPT at the latest. It is obvious that the use of LLM has the potential to quickly develop some rudimentary aspects of a domain model. However, it is unclear in which precision and quality this might be possible. The question is how modeling deals with LLM in the future. Which influence will LLM have on modeling? How will the tasks of modeling change? Will modeling lose its importance? Or, the other way around, will modeling increase its importance in the future?
II Workshop on Conceptual Modeling, Semantic Technologies and Data Platforms for Smart Food Systems (SmartFood)
The future of food production and consumption is being shaped now as a combination of different kinds of technology, such as big data, mobile technologies, robotics, remote-sensing services, virtual and augmented reality, distributed computing, the Internet of things, adaptive systems, Semantic Web technologies, among other technologies. In fact, this field is often known as Smart Food Systems, Digital agriculture, e-Agriculture, Agriculture 4.0 or Smart Agriculture. Efforts in this direction are necessary, as agriculture is still considered one of the least digitalized productive sectors in the world, and it can profit from the benefits of digitalization. Conceptual Modeling is essential to develop smart food systems, by providing a solid basis to support the integration and interoperability of all these kinds of technologies. In particular, semantic technologies are applied in different domains of agriculture and smart food systems, playing an important role in data interoperability, sharing, and reuse. These technologies include ontologies (i.e., shared semantically well-founded conceptualizations of given domains of discourse) and controlled vocabularies (i.e., systematic arrangements of concepts developed to cover the date description needs of a particular community). By using such technologies to build smart food data platforms, it is possible to support reuse and allow such platforms to make more accurate data analysis.
The 17th International i* Workshop (iStar’24)
The iStar workshop series is dedicated to the discussion of concepts, methods, techniques, tools, and applications associated with i* (iStar) and related goal modelling frameworks and approaches (Tropos, GRL, ...).
The proposed iStar’21 workshop would follow successful workshops from Trento in 2002 to London in 2005, up until Hyderabad (2022, Virtual), and most recently Hannover (2023).
As with previous editions, the objective of the workshop is to provide a unique opportunity for researchers in the area to exchange ideas, compare notes, promote interactions, and forge new collaborations.
The focus of the iStar workshop series is quite specific and provides an additional forum for the conceptual modeling community to exchange the latest ideas and research on goal and social modeling. In line with the ER24 conference theme “Conceptual Modeling, AI, and Beyond", this edition of the iStar workshop series also seeks to explore how i* may be best applied to support AI and new avenues of research.
The First International Workshop on AI Services and Applications (AISA’2024)
The rapid advancement of artificial intelligence (AI) technologies has opened up new possibilities for conceptual modelling (ER) businesses across various industries. However, the effective application of these technologies requires a deep understanding of both their potential and their limitations. The International Workshop on AI Services and Applications (AISA’2024) is where AI services and applications comes into play.
- Knowledge Sharing: The workshop will serve as a platform for sharing knowledge and best practices in the field of AI. It will bring together experts from academia, industry, and consulting to share their insights and experiences. This will help participants to stay updated with the latest trends and developments in AI.
- Practical Applications: The workshop will focus on practical applications of AI in various business contexts. This includes AI-powered knowledge services that can help organizations to manage and leverage their knowledge assets more effectively. It will also cover AI consulting services that can guide businesses in their AI journey.
- Hands-on Experience: the workshop welcomes any project or tools that can provide hands-on experience on AI services or applications.
- Networking Opportunities: The workshop will provide ample opportunities for networking. Participants will be able to connect with like-minded professionals and potential collaborators. This can lead to future partnerships and collaborations.
- Promoting AI Adoption: By educating participants about the benefits and applications of AI, the workshop will promote the adoption of AI technologies. This can lead to increased efficiency, improved decision-making, and enhanced competitiveness for businesses.
The First International Workshop on AI-Driven Modeling and Management of Data (AIMM 2024)
Artificial intelligence and machine learning techniques are widely used in software development for various applications. This workshop focuses on AI and machine learning approaches in seeking semantics and building conceptual modeling and managing data for various datasets such as text, image, video, stream data, drone or satellite data, GIS, etc.
This track aims to tackle research problems and practical applications for AI and machine learning applications on modeling and management of data. Researchers and practitioners are invited to submit papers on theoretical, technical, and practical issues. We are particularly interested in applying AI and machine learning techniques to specific application domains (e.g., e-learning, e-business, social networks, geographic information systems, medical informatics, bioinformatics, cyber-physical systems, etc.).
Topics include, but are not limited to, machine learning applications or AI-driven approach for:
- AI-driven Conceptual modeling
- Semantic interoperability
- Ontology, Taxonomy, and Folksonomy
- Ontology generation/learning
- Building/utilizing ontologies and knowledge bases
- Semantics and ontologies in data integration
- Ontology-enabled search (engines)
- Semantic search
- Knowledge graph and applications
- Personalization
- User modeling
- Recommender systems
- Data Analytics
- AI-Driven data systems
- AI-enabled data platforms
- AI-enabled question-answering
- AI-enabled data platforms
- Large language models (LLMs) applications
- Data processing for LLMs
- Applications of LLMs for real-world applications
- The ethical and societal implications of LLMs
- E-learning, e-business, medical informatics, bioinformatics, and legal domains
- Anomaly/Outlier detection
- Fairness, Bias, and Ethical Issues
Special Workshops (Invitation Only)
The objectives of the “Special Workshops” track of the ER2024 Conference include:
- To explore the interactions and integration of conceptual/ER modeling with another scientific domain such as:
- Natural or Programming Languages
- Biology Sciences
- Library Sciences
- Cybersecurity
- Digital Twins
- Software Engineering
- Cognitive Sciences
- Chip Design
- Supply Chain
- Decision Making
- Etc.
- To experiment new/innovative ways to generate fruitful ideas such as
- Organizing panels as a Dagstuhl Seminar
- To focus on one specific conceptual modeling technique or methodology
- A timing subject