Keywords: Developing Economies, e-Government, e-Government Interoperability, Enterprise Architecture
Astract: The growth and uptake of e-government in developing economies is still affected by the interoperability challenge, which can be perceived as an orchestration of several issues that imply the existence of gaps in methods used for e-government planning and implementation. To a great extent, various counterparts in developed economies have succeeded in addressing the method-related gaps by developing e-government enterprise architectures, as blueprints for guiding e-government initiatives in a holistic and manageable way. However, existing e-government enterprise architectures are country-specific to appropriately serve their intended purpose, while enterprise architecture frameworks or methods are generic to accommodate several enterprise contexts. The latter do not directly accommodate the unique peculiarities of e-government efforts. Thus, a detailed method is lacking that can be adapted by developing economies to develop e-government enterprise architectures that fit their contexts. To address the gap, this article presents research that adopted a Design Science approach to develop an e-Government Enterprise Architecture Framework (EGEAF), as an explicit method for guiding the design of e-government enterprise architectures in a developing economy. EGEAF was designed by extending the Architecture Development Method of The Open Group Architecture Framework (TOGAF ADM) to address requirements for developing interoperable e-government solutions in a developing economy. EGEAF was evaluated using two scenarios in the Ugandan context, and findings indicate that it is feasible; its design is understandable to enable its adoption and extension to accommodate requirements for developing interoperable e-government solutions in other developing economies.

Keywords: Conceptual Modeling, Analytical models, Systematics, Machine Learning algorithms, Bibliographies, Semantics, Machine Learning
Astract: Conceptual models are essential in Software and Information Systems Engineering to meet many purposes since they explicitly represent the subject domains. Machine Learning (ML) approaches have recently been used in conceptual modeling to realize, among others, intelligent modeling assistance, model transformation, and metamodel classification. These works en-code models in various ways, making the encoded models suitable for applying ML algorithms. The encodings capture the models' structure and/or semantics, making this information available to the ML model during training. Therefore, the choice of the encoding for any ML-driven task is crucial for the ML model to learn the relevant contextual information. In this paper, we report findings from a systematic literature review which yields insights into the current research in machine learning for conceptual modeling (ML4CM). The review focuses on the various encodings used in existing ML4CM solutions and provides insights into i) which are the information sources, ii) how is the conceptual model's structure and/or semantics encoded, iii) why is the model encoded, i.e., for which conceptual modeling task and, iv) which ML algorithms are applied. The results aim to structure the state of the art in encoding conceptual models for ML.

Keywords: ArchiMate, value co-creation
Astract: The design and engineering of collaborative networks and business ecosystems is a discipline that requires an outstanding and upfront attention of the value cogenerated among the parties involved in the business exchanges of these networks. Understanding this value co-creation is undoubtedly paramount, first to adequately sustain the design and the development of the information system that brings about this value, second, to support the communication between the information system designers, and third to allow discovering new co-creation opportunities among the networks companies. In that context, we proposed an abstract language (meta-model) that structures, and provides an explanatory semantics to, the co-creation of value between information system designers, allowing a better definition of the collaboration and of each one of the value propositions. The design of this language is achieved in the frame of the design science theory and accordingly follows an iterative improvement approach based on real case studies from practitioners. This chapter introduces the second iteration of the language based on a real case in a smart airport network.

Keywords: Enterprise Modelling
Astract: This volume of the Lecture Notes in Business Information Processing series contains the proceedings of the 16th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM), held in Vienna, Austria, during November 28th to December 1st, 2023. The PoEM working conference aims to improve the understanding of the practice of Enterprise Modeling (EM) by offering a forum for sharing experiences and knowledge between the academic community and practitioners from industry and the public sector. These proceedings include 12 full papers selected out of 34 full papers sent for peer review (35.3% acceptance rate). All submissions have been thoroughly reviewed in a single-blind process by three program committee members. The review process was led by the program committee chairs João Paulo A. Almeida and Monika Kaczmarek- Heß overseen by the general chairs Henderik A. Proper and Agnes Koschmider. The selected papers cover topical areas such as Enterprise Modeling and Artificial Intel- ligence, Enterprise Modeling and Emerging Architectures, Enterprise Modeling and Digital Transformation, Enterprise Modeling Tools and Approaches, etc. We would like to show our greatest appreciation to the submitting authors and the members of the program committee as well as additional reviewers for their hard work.

Keywords: Enterprise Modelling
Astract: For over twenty-five years the EDOC conference has been the primary annual event for disseminating and discussing the latest developments in enterprise computing. In addition to the main track, EDOC 2022 offered a forum, a demonstration track, and a doctoral consortium. It also hosted three workshops of interest to the community. All of these events were held in-person, together with the main conference in Bozen-Bolzano, Italy. The forum was introduced this year as a track within the main conference where authors were given a platform to present and discuss early-stage work. In this first edition, we accepted four forum papers for presentation and publication in this proceedings volume. The demonstration track offered a highly interactive outlet for researchers and prac- titioners to present prototypes and applications in the context of enterprise computing. This year, we accepted five tools for presentation, each of which was accompanied with a short paper published here.