The recently introduced 5G New Radio is the first wireless standard natively designed to support critical and massive machine type communications (MTC). However, it is already becoming evident that some of the more demanding requirements for MTC cannot be fully supported by 5G networks. Alongside, emerging use cases and applications towards 2030 will give rise to new and more stringent requirements on wireless connectivity in general and MTC in particular. Next generation wireless networks, namely 6G, should therefore be an agile and efficient convergent network designed to meet the diverse and challenging requirements anticipated by 2030. This paper explores the main drivers and requirements of MTC towards 6G, and discusses a wide variety of enabling technologies. More specifically, we first explore the emerging key performance indicators for MTC in 6G. Thereafter, we present a vision for an MTC-optimized holistic end-to-end network architecture. Finally, key enablers towards (1) ultra-low power MTC, (2) massively scalable global connectivity, (3) critical and dependable MTC, and (4) security and privacy preserving schemes for MTC are detailed. Our main objective is to present a set of research directions considering different aspects for an MTC-optimized 6G network in the 2030-era.

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Technology and software-based service development is increasingly important in business or innovation ecosystems. This paper describes an evolution of such an ecosystem as part of a fouryear collaboration with several companies and a research organization. Research was conducted on the ecosystem's functions, from the perspective of managing its members' innovation activities and changing roles. We discuss the methods and tools for supporting and facilitating service innovation activities in the ecosystem formation. We conclude that innovation ecosystems bene¯t from the aid of research organization and the tools and methods they can bring to help the evolution of the ecosystem.

Procedural content generation (PCG)-based game design aims to reach a new way of playing games by focusing gameplay around algorithmic game content generation. However, positioning interaction with PCG systems and generated content to the center of player experience poses design challenges for both game design and AI design. In order to create the wanted affordances, rich contextual information is required to make informed decisions on the generated content. While previous research has presented excellent developments on PCG's possibilities, further considering context and affordances in the early stages of prototyping may aid designers reach these possibilities in a more consistent manner. This study is set to discuss how context, affordances and the game's overall design can be considered during the prototyping process of PCGbased games. Misaligned game context and affordances can result in deeply rooted design issues that may later manifest as subpar gameplay experiences and increased development effort. These emergent issues are examined through a post-mortem case study to produce an extended PCG-based design process, featuring actionable steps, that takes context, affordances, and the game's overall design into account through meaningful play. CCS CONCEPTS • Applied computing → Computer games.

Digital twin (DT) emerges as a key concept of the Industry 4.0 paradigm and beyond. However, the current literature lacks focus on humans and human activities as a part of complex system DTs. Acknowledging human aspects in DTs can enhance work performance, well-being, motivation and personal development of professionals. This study examines emerging requirements for human digital twins (HDTs) in three use cases of industry-academia collaboration on complex systems. The results draw together the overall design problem and four design objectives for HDTs. We propose to combine the machine and human-related aspects of DTs, and highlight the need for virtual-to-virtual interoperability between HDTs and machines alike. Furthermore, we outline differences between humans and machines regarding digital twinning by addressing human activities and knowledge-based behavior on systems. Design of HDTs requires understanding of individual professional characteristics, such as skills and information preferences, together with twinning between the physical and digital machine entities and interactions between the human and machine DTs. As the field moves towards including humans as a part of the DT concept, incorporating HDTs in complex systems emerges as an increasingly significant issue.