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Cities’ population growth goes in hand with the development of new technologies that are becoming the key factor of the Smart City (SC) concept. It allows the implementation of efficient management solutions, operation, and sustainable development of a city to face the challenges of urbanization and improve the services for the citizens and visitors.

The concept of the SC 5.0 was first presented in Svítek, Skobelev, and Kozhevnikov (2020), where the problems of the complexity of current cities due to rigid management processes, variety of infrastructure, and SC modules, systems, subsystems, and applications were described.

To prove the concept, several practical examples were developed to cover the topics: modeling in SCs, practical implementation of multiagent technologies, the approach of creating city ontology and the city knowledge base as the instrument of semantic interoperability, and visualization possibilities of Smart Evropská as a SC Testbed used for teaching purposes.

The new organizational structure is proposed based on knowledge graphs, and practical examples are shown. The applicability of knowledge graphs to be used in combination with data management platforms for monitoring SC key performance indicators (KPIs) and providing interoperability of services is presented.

In this chapter, we develop an argument in support of comparative framing in teacher education research with the purpose of strengthening the education profession and particularly the professional field of teaching and teacher education. There is little agreement in the field on the required knowledge needed to become a highly effective teacher and on how to know that teachers know enough of a subject to teach it. We argue that comparative and collaborative cross-national studies serve as ideal catalytic forces to develop much-needed ontologies to develop definitions and realize contrasts, possibilities, and limitations. The construction of ontologies supports the epistemological bases of the profession. Comparative studies help to understand what others with similar goals such as the education and support of teachers have been able to achieve under what conditions, resources, and contexts.

Cities evolved into quite complex urban systems. The rigid management process must reflect the complexity of the current political, social, and economic environment. With the vast city growth, citizens experience new difficulties – traffic congestion, pollution, immigration, overcrowding, and inadequate services.

In our research, we analyze problems and benefits that occur with the growing complexity and offer a new concept considering every city as a live and constantly developing complex adaptive system of many participants and actors that operate in an uncertain environment. These actors (residents, businesses, transport, energy, water supply providers, entertainment, and others) are the main elements of city life.

The new concept of “Smart City 5.0” is based on a previously developed model of Smart City 4.0 (compared with Industry 4.0) and implements the Urban Digital Ecosystem, where every element can be represented by a smart agent operating on its behalf. It is shown that smart services can interact vertically and horizontally in the proposed ecosystem, supporting competition and cooperation behavior based on specialized network protocols for balancing the conflicting interests of different city actors.

The chapter describes the design principles and the general architecture of the Urban Digital Ecosystem, including the basic agent of smart service, protocols of the agent’s negotiation, the architecture, and basic principles Smart City knowledge base.

The developed evolutionary methodology of implementation will ensure a minimum of disruptions to city services during its transformation into an urban ecosystem to harmoniously balance all spheres of life and the contradictory interests of different city actors.

Cultural heritage archiving is experiencing an increase in digitalisations of artefacts in the last 15 years. The reason behind this trend is a demand for providing information about the artefact in a more accessible way to the audience, for example, through online delivery or virtual reality. Other reasons might be to simplify and automate the management of artefacts. Having a ‘digital copy’ of artefacts, allows one to search an archive and plan its storage and dissemination in a comprehensive manner. With the increased digitalisation comes an increased use of artificial intelligence [AI] applications. AI can be very beneficial in classifying artefacts automatically through machine learning [ML] and natural language processing [NLP]. For example, an algorithm can identify the source and age of artefacts based on an image and can do this much faster for a large collection of photos than a human. Although AI provides many benefits, it also presents challenges: Sophisticated AI techniques require certain insights on how they work, need specialists to customise a solution, and require an existing large dataset to train an algorithm. Another challenge is that typical AI techniques are regarded as black boxes, which means they decide, but it is not obvious why a decision has been made. This chapter describes a project in collaboration with the South Australian Museum [SAM] on the application of AI to extract material lists from a description of artefacts. A large dataset to train an algorithm did not exist, and hence, a customised approach was required. The outcome of the project was the application of NLP in combination with easy-to-customise rules that can be applied by non-IT specialists. The resulting prototype achieved the extraction of materials from a large list of artefacts within seconds and a flexible solution that can be applied on other collections in the future.

Like pro-bono service of law and other professional practices, micro-credentialing has become the quasi-charity project of the rapidly commodifying higher education (HE) sector. Produced with minimum waste and expense, qualifications through micro-credentialing economises time spent and optimises efforts. As a result, these bite-size educational offerings are becoming abundant and attractive to both learners and providers. While learners learn on the job or in the job market, providers get an opportunity to package knowledge and skills. Among a plethora of courses with potential overlapping and mismatched competencies, however, a clear pathway to target a career through pastures of micro-credentialing is yet to emerge. If not, it may result in another system of skill poverty and thus alienate the essential autonomy of credential seekers. Autonomy or self-tailoring your own package of micro-credentials (MC) without a proper wayfinding system could be overwhelming, sometimes even counterproductive, if competency management is based on a one-size-fits-all model. Via a local case, this chapter reviews current MC available to capacitate a career using Construction Management (CM) as a point of departure. It aims to develop a wayfinding framework or user-friendly menu for those wanting to craft a career via a micro-credentialing ecosystem. Broadly, it investigates navigating various MC offerings equivalent to undergraduate qualifications needed to become a CM professional recognised by accreditation bodies. In the process, it systematically discourses multiple ontologies of micro-credentialing in links, lapses, overlaps, and intersections among competencies to untangle complexities and optimise opportunities. It was hoped that learners could target a career instead of matching a job profile in the micro-credentialing universe.