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2024 | Book

Adaptation of Enterprise Modeling Methods for Large Language Models Read chapter Read first chapter

The Practice of Enterprise Modeling

16th IFIP Working Conference, PoEM 2023, Vienna, Austria, November 28 – December 1, 2023, Proceedings

Editors: João Paulo A. Almeida, Monika Kaczmarek-Heß, Agnes Koschmider, Henderik A. Proper

Publisher: Springer Nature Switzerland

Book Series : Lecture Notes in Business Information Processing

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book constitutes the proceedings of the 16th IFIP Working Conference on the Practice of Enterprise Modeling, PoEM 2023, which took place in Vienna, Austria, during November 28 - December 1, 2023.

PoEM offers a forum for sharing experiences and knowledge between the academic community and practitioners from industry and the public sector. This year the theme of the conference is Enterprise Modeling in the Circular Economy.

The 12 full papers presented in this volume were carefully reviewed and selected from a total of 34 submissions. They were organized in topical sections named as follows: Enterprise modeling and artificial intelligence; emerging architectures and digital transformation; modeling tools and approaches; and enterprise modeling at work.

Table of Contents

Frontmatter

Enterprise Modeling and Artificial Intelligence

Frontmatter
Adaptation of Enterprise Modeling Methods for Large Language Models
Abstract
Large language models (LLM) are considered by many researchers as promising technology for automating routine tasks. Results from applying LLM in engineering disciplines such as Enterprise Modeling also indicate potential for the support of modeling activities. LLMs are fine-tuned for specific tasks using chat based interaction through the use of prompts. This paper aims at a detailed investigation of the potential of LLMs in Enterprise Modeling (EM) by taking the perspective of EM method adaptation of selected parts of the modeling process within the context of using prompts to interrogate the LLM. The research question addressed is: What adaptations in EM methods have to be made to exploit the potential of prompt based interaction with LLMs? The main contributions are (1) a meta-model for prompt engineering that integrates the concepts of the modeling domain under consideration with the notation of the modeling language applied and the input and output of prompts, (2) an investigation into the general potential of LLM in EM methods and its application in the 4EM method, and (3) implications for enterprise modeling methods.
Balbir S. Barn, Souvik Barat, Kurt Sandkuhl
EA ModelSet – A FAIR Dataset for Machine Learning in Enterprise Modeling
Abstract
The conceptual modeling community and its subdivisions of enterprise modeling are increasingly investigating the potentials of applying artificial intelligence, in particular machine learning (ML), to tasks like model creation, model analysis, and model processing. A prerequisite—and currently a limiting factor for the community—to conduct research involving ML is the scarcity of openly available models of adequate quality and quantity. With the paper at hand, we aim to tackle this limitation by introducing an EA ModelSet, i.e., a curated and FAIR repository of enterprise architecture models that can be used by the community. We report on our efforts in building this data set and elaborate on the possibilities of conducting ML-based modeling research with it. We hope this paper sparks a community effort toward the development of a FAIR, large model set that enables ML research with conceptual models.
Philipp-Lorenz Glaser, Emanuel Sallinger, Dominik Bork
Towards AI as a Service for Small and Medium-Sized Enterprises (SME)
Abstract
AI-as-a-Service (AIaaS) combines Artificial Intelligence (AI) and cloud computing to make AI accessible to enterprises without implementing complex solutions or technologies on-premise. Many small and medium-sized enterprises (SME) that lack competencies in the AI and technology sector consider AIaaS as a promising option to implement AI solutions. However, the differences between AIaaS and AI on-premise have not attracted much research. The intention of this paper is to contribute to this area by analysing the literature in the field and investigating a concrete example in more detail. Exploring AIaaS is crucial to better understand the opportunities and limitations of AI services. The contributions of the paper are (a) an analysis of the literature on AIaaS to identify factors affecting AI implementation and how AIaaS solutions differ from on-premise solutions when introducing AI in a company, (b) a case study of an SME that compares AIaaS and AI on-premise in practice, and (c) the application potential of a morphological box to compare AIaaS and AI on-premise.
Leon Griesch, Jack Rittelmeyer, Kurt Sandkuhl

Emerging Architectures and Digital Transformation

Frontmatter
Evaluating ArchiMate for Modelling IoT Systems
Abstract
The Internet of Things (IoT) is a disruptive technology that allows connecting physical objects with the digital world. This challenges organizations in adjusting their Enterprise Architecture (EA) for adopting the IoT technology to improve their operations and maximize their value. Considering the complexity of such changes, a suitable modelling language must be used for EA design and documentation. ArchiMate, being a de facto standard for EA modelling, has already been used for modelling IoT systems, however, it is not used in a consistent manner and different extensions have been proposed to address limitations identified in specific domains. Based on the most common practices reported in the literature, we propose and evaluate a set of guidelines for modelling IoT elements in ArchiMate. The guidelines are evaluated by performing qualitative research based on case studies. The evaluation shows that ArchiMate is suitable for modelling IoT systems, but only at the conceptual level. When technical details are required, extensions to the standard may be needed. In addition, domain-specific limitations such as the lack of showing time-based communication and redundancy in an industry context are identified.
Yara Verhasselt, Janis Stirna, Estefanía Serral
A Domain-Specific e3value Extension for Analyzing Blockchain-Based Value Networks
Abstract
Adopting blockchain technologies in organizations has multiple implications for business models. To make adoption successful, both the business as well as the technical perspectives must be carefully aligned. However, understanding the impact of the technological changes on business models is a challenge due to the technological complexity, the lack of knowledge in the organization, and regulatory requirements. Further, domain-specific modeling methods that inherently deal with blockchain concepts in business models are currently missing. To address this gap, we present an extension of the \({e}^{3} value\) modeling method to depict blockchain-specific aspects in value networks, including the automatic inference of transparency based on blockchain usage and configuration. The extended modeling method was implemented on the ADOxx metamodeling platform and applied to three exemplary use cases for a first evaluation.
Simon Curty, Hans-Georg Fill
Building a New Information Technology Operating Model to Support Digital Transformation: A Case Study in Oil and Gas Sector
Abstract
Multinational corporations are facing increasing demands on their IT function due to digital innovation and transformation. However, a traditional IT function often lacks capabilities required for successful digital transformation. This necessitates a comprehensive change in its IT operating model (ITOM), encompassing people, processes, technology, governance, agility, outsourcing, and more. This article presents a case study of a large European oil and gas company's IT function, exploring the design and implementation process of a new ITOM. Qualitative interviews with IT executives and digital leads, along with data analysis, shed light on the involvement of external consulting firms during the design phase, while the implementation phase is driven by internal IT teams. The process is labor-intensive and spans several years, highlighting the complexity of ITOM implementation within a multimodal IT function structure. Key findings stress the need for close alignment among strategic IT leaders and strong business executive ownership. Scaling an agile approach requires an agile mindset achieved through continuous training and clearly defining the role of the product owner. The study has significant implications for IT function transformation through the adoption of a new ITOM, making it relevant for practitioners, researchers, and CIOs alike.
Muhammad Suleman, Jolita Ralyté, Samuli Pekkola, Tuomas Ahola

Modeling Tools and Approaches

Frontmatter
A Vision for Flexible GLSP-Based Web Modeling Tools
Abstract
In the past decade, the modeling community has produced many feature-rich modeling editors and tool prototypes not only for modeling standards but particularly also for many domain-specific languages. More recently, however, web-based modeling tools have started to become increasingly popular in the industry for visualizing and editing models adhering to such languages. This new generation of modeling tools is built with web technologies and offers much more flexibility when it comes to their user experience, accessibility, reuse, and deployment options. One of the technologies behind this new generation of tools is the Graphical Language Server Platform (GLSP), an open-source client-server framework hosted under the Eclipse foundation, which allows tool developers to build modern diagram editors for modeling tools that run in the browser or can be easily integrated into IDEs such as Eclipse, VS Code, or Theia. In this paper, we describe our vision for more flexible modeling tools which is based on our experiences from developing several traditional and web-based modeling tools in an industrial and academic context. With that, we aim at sparking a new line of research and innovation in the modeling community for modeling tool development practices and to explore opportunities, advantages, and limitations of web-based modeling tools, as well as bridge the gap between scientific tool prototypes and industrial tools being used in practice.
Dominik Bork, Philip Langer, Tobias Ortmayr
Investigating Quality Attributes in Behavior-Driven Development Scenarios: An Evaluation Framework and an Experimental Supporting Tool
Abstract
Behavior-Driven Development (BDD) refers to an agile development practice to express the fulfillment of a requirement often depicted in a user story. BDD is meant to facilitate the understanding of how to properly execute requirements among role-divergent stakeholders in a software project. In that way, the development team avoids an excessive focus on coding at the early requirements definition stage and can focus on truly capturing the features and behaviors that are expected by the end-users. In BDD, user-driven scenarios are written in structured natural language following a defined template. Notwithstanding, not much attention has been placed in the literature in terms of defining/studying the quality aspects of the written BDD scenarios; therefore, practitioners tend to use the technique in an ad-hoc manner. In this study, we explore the quality attributes assigned to a well-written BDD scenario. We refine an existing framework by establishing formal definitions for each of the scenarios’ attributes, study their applicability through real BDD scenarios, and link them to the quality attributes appointed to user stories. We then develop and present an experimental Computer-Aided Software Engineering (CASE) tool that helps practitioners assess the quality of the BDD scenarios through the automated evaluation of a set of conforming quality attributes namely Uniqueness, Essentiality, Integrity, and Singularity. We further validate the framework and the tool by collecting two expert opinions.
Yves Wautelet, Anousheh Khajeh Nassiri, Konstantinos Tsilionis
Semiautomatic Design of Ontologies
Abstract
The design of ontologies is a time-consuming and resource-intensive endeavour. Rather than (manually) design the ontology first and then associate it with data, can we (semiautomatically) design the ontology from the data itself? This paper presents a novel approach to the semi-automated design of ontologies that incorporates axiom generation from data models, semantic parsing, and ontology learning from examples and counterexamples via search through an ontology repository.
Michael Grüninger, Amanda Chow, Janette Wong

Enterprise Modeling at Work

Frontmatter
Enterprise Modelling Can Be Used as a Research Method: An Application to Sustainability Reporting Research
Abstract
Enterprise modelling (EM) refers to eliciting and documenting knowledge about an organisation from several interrelated perspectives. Often EM is industrially applied and scientifically researched within the fields of enterprise and information systems (IS) engineering. In this paper, we put forward that EM constitutes a sound and valid research method that could be used outside these disciplines. Its systematic elicitation and modelling techniques lend themselves to rigorous empirical investigations. We report on our experience in applying an EM method as a research method in a project exploring the relationships between sustainability reporting and strategic management practices. The results were rich in high-quality, detailed research data, that allowed drawing strong evidence-based conclusions. If EM were known in other scientific fields interested in phenomena taking place inside or around enterprises, these research communities would benefit from a structured and rigorous approach to investigate aspects related to the organisational structure, processes, communications and information, motivations, and relationships among these, which are core constructs in EM methods.
Sergio España, Gudrun Thorsteinsdottir, Vijanti Ramautar, Oscar Pastor
Using the Business Motivation Model as an Organising Principle to Clarify Public Policy
Abstract
Public policies use constructive ambiguity as a linguistic and diplomatic tool to manage the conflicting views of stakeholders and facilitate policy implementation in the presence of tensions. However, the ambiguity of policy content is a knowledge problem. It can lead to misunderstandings of its ends and means and may result in failed mitigation measures for societal crises. The Business Motivation Model (BMM) combined with the UML attribute elements can solve this problem by structurally decomposing the policy content into a BMM representation. This representation is an epistemic artefact that generates meta-knowledge about the policy by clarifying its intentions and conceptual structure, thus decreasing the likelihood of it being misunderstood. We present the case of the Aviation Chapter of the Greenhouse Gas Emissions Trading System (EU ETS), where we clarify its prescriptions for the European Commission (EC), Member States, and aircraft operators using BMM concepts and relationships as deductive coding patterns. The artefact has undergone artificial empirical evaluation by expert opinion (n = 15). Possible use scenarios were discussed with enterprise modellers, climate policy researchers, and aircraft industry experts concerned with EU ETS enforcement, implementation, and auditing. The BMM representation presented advantages over the policy’s textual form and improved the aviation industry experts’ understanding of the Chapter. Future research could look into increasing the analytical capabilities of the notation to address the needs of policy researchers working with gap analyses and co-development of policy revisions with stakeholders. Other modelling and diagramming tools should be examined to enable model durability and robustness.
Helena Zhemchugova, Friederike Stock, Lutho Madala
A Study on the Impact of the Level of Participation in Enterprise Modeling
Abstract
Participatory enterprise modeling (PEM) is presumed to have a positive impact on commitment, ownership feelings and further appraisals by domain experts with respect to the model. Whether PEM actually produces the desired effects, however, has been little studied. In this paper we report on an investigation of the effects of three different participatory settings: an overall model was created 1) from four individual interviews, 2) from four individual models, or 3) in a joint meeting of domain and modeling experts. The results show that the non-participatory interview setting led to less favorable appraisals, e.g., the level of participation was perceived as lower and the contribution of the modeling experts was perceived as higher. Our findings should help practitioners in weighing possible benefits of participatory enterprise modeling against the organizational and monetary effort it involves.
Anne Gutschmidt, Charlotte Verbruggen, Monique Snoeck
Backmatter
Metadata
Title
The Practice of Enterprise Modeling
Editors
João Paulo A. Almeida
Monika Kaczmarek-Heß
Agnes Koschmider
Henderik A. Proper
Copyright Year
2024
Electronic ISBN
978-3-031-48583-1
Print ISBN
978-3-031-48582-4
DOI
https://doi.org/10.1007/978-3-031-48583-1

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