Keywords: Model repository, Dataset, UML, Open models, Curation, Community, Education, Machine learning
Astract: Datasets of Unified Modeling Language (UML) models are becoming increasingly valuable for education, empirical research, and tool development in model-driven engineering (MDE) and conceptual modeling. In recent years, several datasets have emerged - mostly compiled through automated crawling of open platforms such as GitHub and GenMyModel. While these efforts have improved access to real-world modeling artifacts, the resulting collections often suffer from serious quality issues: they include syntactically invalid models, semantically incorrect structures, and placeholder or dummy content. Moreover, most models are not accompanied by textual domain descriptions, which are essential for understanding the intent behind the model and assessing its semantic soundness. Therefore these model datasets are far from ideal as a source for modeling exercises or empirical MDE research. This paper presents an initial step toward a community-curated golden dataset of UML models, designed to address these limitations. Our contribution includes i) a curated set of UML models, each paired with a natural language description of the modeled domain requirements, ii) a publicly accessible web platform for exploring and querying the dataset, and iii) a structured process for community-based contribution and evaluation to support sustainable growth and quality assurance of the dataset. By fostering community involvement and providing high-quality, semantically grounded models, this work lays the foundation for a widely accepted benchmark dataset in UML-based research and education.

Keywords: GLSP, LSP, Modeling tool, Software modeling, UML, Web modeling
Astract: Web-based modeling tools provide unprecedented opportunities for the realization of modern, powerful, and usable diagram editors running in the cloud. The development of such tools, however, still poses significant challenges for developers. The graphical language server platform (GLSP) aims to reduce some of these challenges by providing the necessary frameworks to efficiently create web modeling tools. However, realizing modeling tools with GLSP remains challenging and not much support for interested tool developers is provided yet. This paper discusses these challenges and lessons learned after working with GLSP and realizing several GLSP-based modeling tools. We present experiences, concepts, and a reusable reference architecture to develop and operate GLSP-based web modeling tools. As a proof of concept, we report on the realization of a GLSP-based UML editor called bigUML. Through bigUML, we show that our procedure and the reference architecture we developed resulted in a scalable and flexible GLSP-based web modeling tool for the UML. The lessons learned, the procedural approach, the reference architecture, and the critical reflection on the challenges and opportunities of using GLSP provide valuable insights to the community and shall ease the decision of whether or not to use GLSP for future tool development projects. With this paper, we publicly release a reference implementation of our architecture.

Keywords: Enterprise Architecture, Architectural Coordination, Digital Twins for Urban Planning, Local Digital Twin
Astract: Digital Twins (DTs) carry the promise of improved decision-making about, as well as monitoring and understanding of, the twinned entity. This makes them an attractive instrument to support the, often complex and multi-faceted, decision-making processes germane to urban planning. DTs require considerable technological investments, as they tend to be data-hungry and computing-intensive. Business-wise, such investments are only meaningful if they really add value to the intended decision-making processes. However, most current DT development approaches primarily focus on the technological potential of DTs within the limited scope of isolated business scenarios, and rarely address trade-offs between costs and benefits towards the business case, let alone the broader implications for IT/IS portfolio management. These broader considerations are crucial in urban planning contexts, which typically involve a broad ecosystem of parties, complex decision-making challenges, and pre-existing technological landscapes. Drawing on the discipline of Enterprise Architecture Management (EAM), this paper argues that architectural coordination of DT development initiatives would enable more effective valorisation of DTs potential, and more effective management of DT-related technology within a broader technological landscape. To this end, the paper discusses the vision for and an initial sketch of a specialisation of EAM for DT development.

Keywords: Accessibility, GLSP, Modeling tool, Natural language interface, Speech-based interaction, UML
Astract: Modeling is a core task in enterprise systems engineering. The use of graphical modeling editors, however, remains cumbersome in general and poses a significant challenge for users with disabilities. Natural language processing (NLP) and intent recognition are at the forefront of making many technologies more accessible and intuitive by allowing users to engage using natural language. This paper presents a natural language interface (NLI) for speech-based UML model interaction that leverages state-of-the-art NLP technologies to enable speech-based modeling. We provide a workflow for the creation of NLIs for modeling editors, a proof-of-concept integration of this approach into the bigUML open-source modeling editor, and an empirical evaluation that shows promising results in intent recognition, the effectiveness of model creation, and usability. Thereby, this paper makes significant contributions towards more natural, inclusive, and accessible modeling.

Keywords: Model-Driven Engineering, Accessibility, Inclusion
Astract: While model-driven engineering (MDE) claims to be a good development approach for cross-cutting concerns, this raises the question of why not every application created with MDE is accessible. Moreover, why are the MDE development processes and the tools themselves not more inclusive? In this vision paper, we sketch an ideal picture of how inclusivity in MDE - considered throughout tools, methods, artifacts, and processes - would intrinsically lead to more accessible software systems. We review the state-of-the-art, discuss current challenges, and present a possible future of inclusive MDE.

Keywords: AI-assisted Domain Modeling, Domain Model Validation, Domain Modeling, Large Language Models
Astract: The use of Large Language Models (LLMs), combined with advanced prompting strategies, automates the creation of domain models from textual domain descriptions. However, the output is often influenced by mistakes and limitations that arise from the inherent characteristics of LLMs, including hallucinations and inconsistencies. Additionally, ambiguities and incompleteness in the input text further affect the quality of the results. We propose a new LLM-based modeling method with human in the loop that aims to combine the strengths of automatic model creation with human supervision and interaction to refine and validate the model. In our approach, the LLM generates an initial draft model from textual descriptions. This draft is then subjected to a feedback loop moderated by a rule-based agent, which engages the user through a Q&A dialogue. The rule-based agent selects the questions based on their potential to clarify the most uncertain aspects of the model up to that point.

Keywords: CDS, Domain-specific language, Langium, LSP, Model-driven engineering, Modeling tool, SAP Core Data Services, Sprotty
Astract: This paper introduces bigER2CDS, a novel model-driven engineering approach and tool support for SAP Core Data Services (CDS). bigER2CDS addresses the need for a higher abstraction level in CDS development, enabling blended, i.e., textual and graphical modeling of CDS Views through a domain-specific modeling language. Based on web technologies and the Language Server Protocol (LSP), we realized a modeling tool for SAP CDS. Our tool supports the hybrid modeling of CDS and the import of existing SAP CDS view entities for analysis and development support. This model-driven approach aims to enable domain experts to develop CDS views, mitigating the need for extensive programming skills. We report on the development of the ER2CDS domain-specific language (DSL) and the implementation of the corresponding bigER2CDS modeling tool. Finally, bigER2CDS is evaluated in the form of a controlled experiment and a case study with domain experts and CDS developers. The results show a high usability score for our tool and a willingness by domain experts and CDS developers to use it. The tool can be freely downloaded from the VS Code marketplace: https://marketplace.visualstudio.com/items?itemName=BIGModelingTools.er2cds.

Keywords: Accessibility, Conceptual modeling, Disability, Modeling tools, Systematic literature review, Tool review
Astract: The reports on Disability by the World Health Organization show that the number of people with disabilities is increasing. Consequently, accessibility should play an essential role in information systems engineering research. While there is an increasingly rich set of available web accessibility guidelines, testing frameworks, and generally accessibility features in modern web-based software systems, software development frameworks, and Integrated Development Environments, this paper shows, based on a systematic review of the literature and current modeling tools, that accessibility is, so far, only scarcely focused in conceptual modeling research. With this paper, we assess the state of the art of accessibility in conceptual modeling, we identify current research gaps, and we delineate a vision toward more accessible conceptual modeling methods and tools. As a concrete step forward toward this vision, we present a generic concept of a keyboard-only modeling tool interaction that is implemented as a new module for the Graphical Language Server Platform (GLSP) framework. We show—using a currently developed UML modeling tool—how efficiently this module allows GLSP-based tool developers to introduce accessibility features into their modeling tools, thereby engaging physically disabled users in conceptual modeling.

Keywords: BERTopic, Data-driven approach, Dynamic Topic Modeling, EMMSAD, IS analysis and design
Astract: Modeling for information systems (IS) analysis and design offers broad insights into the advances and challenges of enterprise, business process, software, and conceptual modeling. In celebration of its 30th edition, this paper presents a data-driven retrospective analysis of studies published at the Exploring Modeling Methods for Systems Analysis and Development (EMMSAD) working conference from 2005 to 2024. EMMSAD has long been a key venue for research on Information Systems (IS) Modeling, covering areas such as conceptual modeling, enterprise modeling, and model-driven engineering, as well as the evaluation of modeling techniques and tools. Using machine learning, specifically Dynamic Topic Modeling (DTM) with BERTopic, this study identifies recurring topics, emerging trends, and shifts in research focus within the IS modeling community. The findings highlight key areas of alignment between IS modeling and the broader modeling landscape, providing insights into the field’s evolution and future research opportunities.

Keywords: design science, framework, maturity assessment, MBSE adoption
Astract: As engineering systems become increasingly complex, organizations must adopt strategic approaches to manage the interdependencies of their processes, tools, and teams. Model-Based Systems Engineering (MBSE) offers a promising solution, but transitioning from a traditional SE approach to MBSE is a complex endeavor that requires significant organizational change. This paper addresses the need for structured guidance in this process by proposing a maturity assessment framework that supports organizations in navigating this transition. The proposed framework is developed using a design science based approach and identifies key challenges, pitfalls, and best practices that are organized into several maturity levels of MBSE adoption. This structured, high-level approach provides organizations with the tools to understand their current maturity level, prioritize efforts, and avoid common missteps. The framework allows organizations to tailor the insights to their unique context, ensuring practical applicability. It emphasizes the importance of leadership, cultural readiness, technical tools, workforce development, and modeling practices for successful MBSE implementation.