Data Sovereign Humans and the Information Economy: Towards Design Principles for Human Centric B2C Data Ecosystems

The ever-growing amounts of data offer companies many opportunities for data-driven-value generation which, in turn, can be multiplied by leveraging data across company boundaries in evolving data ecosystems. However, while such systems increasingly emerge in B2B environments enabling systematic sharing and utilization of “industrial data”, comparable concepts in B2C ambits have not yet prevailed. Despite the rising importance of personal data in the information economy, B2C data ecosystems represent a widely unexplored research area. To remedy this gap, the study generates design principles for human centric B2C data ecosystems to aid in their development. For this purpose, a qualitative interview study with experts of interdisciplinary domains and a structured literature review are conducted both embedded into a methodology for generating design principles. On this basis, derived design principles help to understand peculiarities of data ecosystems in B2C ambits and provide solutions to overcome their obstacles identified in the empirical investigation

City data ecosystems between theory and practice: A qualitative exploratory study in seven European cities

The exponential growth of data collection opens possibilities for analyzing data to address political and societal challenges. Still, European cities are not utilizing the potential of data generated by its citizens, industries, academia, and public authorities for their public service mission. The reasons are complex and relate to an intertwined set of organizational, technological, and legal barriers, although good practices exist that could be scaled, sustained, and further developed. The article contributes to research on data-driven innovation in the public sector comparing high-level expectations on data ecosystems with actual practices of data sharing and innovation at the local and regional level. Our approach consists in triangulating the analysis of in-depth interviews with representatives of the local administrations with documents obtained from the cities. The interviews investigated the experiences and perspectives of local administrations regarding establishing a local or regional data ecosystem. The article examines experiences and obstacles to data sharing within seven administrations investigating what currently prevents the establishment of data ecosystems. The findings are summarized along three main lines. First, the limited involvement of private sector organizations as actors in local data ecosystems through emerging forms of data sharing became evident. Second, we observed the concern over technological aspects and the lack of attention on social or organizational issues. Third, a conceptual decision to apply a centralized and not a federated digital infrastructure is noteworthy

Sustainable modular IoT solution for smart cities applications supported by machine learning algorithms

The Internet of Things (IoT) and Smart Cities are nowadays a big trend, but with the proliferation of these systems several challenges start to appear and put in jeopardy the acceptance by the population, mainly in terms of sustainability and environmental issues. This Thesis introduces a new system composed by a modular IoT smart node that is self-configurable and sustainable with the support of machine learning techniques, as well as the research and development to achieve a innovative solution considering data analysis, wireless communications and hardware and software development. For all these, concepts are introduced, research methodologies, tests and results are presented and discussed as well as the development and implementation. The developed research and methodology shows that Random Forest was the best choice for the data analysis in the self-configuration of the hardware and communication systems and that Edge Computing has an advantage in terms of energy efficiency and latency. The autonomous communication system was able to create a 65% more sustainable node, in terms of energy consumption, with only a 13% decrease in quality of service. The modular approach for the smart node presented advantages in the integration, scalability and implementation of smart cities projects when facing traditional implementations, reducing up to 45% the energy consumption of the overall system and 60% of messages exchanged, without compromising the system performance. The deployment of this new system will help Smart Cities, in a worldwide fashion, to decrease their environmental issues and comply with rules and regulations to reduce CO2 emission.A Internet das Coisas (IoT) e as Cidades Inteligentes são hoje uma grande tendência, mas com a rápida evolução destes sistemas são vários os desafios que põem em causa a sua aceitação por parte das populações, maioritariamente devido a problemas ambientais e de sustentabilidade. Esta Tese introduz um novo sistema composto por nós de IoT inteligentes que são auto-configuáveis e sustentáveis suportados por de aprendizagem automática, e o trabalho de investigação e desenvolvimento para se obter uma solução inovadora que considera a análise de dados, comunicações sem fios e o desenvolvimento do hardware e software. Para todos estes, os conceitos chave são introduzidos, as metodologias de investigação, testes e resultados são apresentados e discutidos, bem como todo o desenvolvimento e implementação. Através do trabalho desenvolvido mostra-se que as Árvores Aleatórias são a melhor escolha para análise de dados em termos da autoconfiguração do hardware e sistema de comunicações e que a computação nos nós tem uma vantagem em termos de eficiência energética e latência. O sistema de configuração autónoma de comunicações foi capaz de criar um nós 65% mais sustentável, em termos en- ergéticos, comprometendo apenas em 13% a qualidade do servi ̧co. A solução modular do nó inteligente apresentou vantagens na integração, escalabilidade e implementação de projectos para Cidades Inteligentes quando comparado com soluções tradicionais, reduzindo em 45% o consumo energético e 60% a troca de mensagens, sem comprometer a qualidade do sistema. A implementação deste novo sistema irá ajudar as cidades inteligentes, em todo o mundo, a diminuir os seus problemas ambientais e a cumprir com as normas e regulamentos para reduzir as emissões de CO2

ArchiSmartCity: Modelling the Alignment of Services and Information in Smart City Architectures

Digital transformation in the public sector describes the shift from traditional creation and delivery of services, into the massive use of digital technologies to enhance public services. The digitalisation of public administration presents significant challenges for many municipalities in the social, economic, environmental, and sustainable dimensions. Cities take advantage of the rapid advances in information and communication technologies capabilities to make the provision of city services (e.g., health service, transport service, air-quality service, education service) more efficient. These modern urban environments are commonly referred to as Smart Cities, where advanced and innovative services are offered to improve the overall quality of life for the citizens. Smart Cities are complex systems that involve diverse stakeholders and concerns, use heterogeneous information systems and technologies, and aim to fulfill multiple and conflicting goals. Such complexity challenges the provision of services that may fail to achieve city goals and meet the needs of citizens due to the lack of alignment between city services and the information systems that support them. Evidence of this is the existence of city services and systems that fail to address the real needs of stakeholders, and are not perceived as valuable by them because they do not interoperate, leading to duplication of work and incompatible solutions. Enterprise Architecture (EA) is an established planning and governance approach to manage the complexity of corporate systems. EA presents a holistic view of organisational business strategies and IT initiatives to achieve organisational goals by adopting a comprehensive perspective on the overall architecture. Smart Cities can be seen as urban enterprises with more complex and multi-dimensional systems that require integration among smarter services from different domains (e.g., mobility, energy, public safety, emergency, education, culture, etc.) to respond to diverse interests and objectives from a range of stakeholders. Existing research on EAs for Smart Cities uses the concept of layers and views to describe architecture content and guide its implementation. However, these approaches do not identify the concepts to describe and model the relationships between the service and information layers which are essential to address the strategic alignment. Furthermore, there is an absence of such concepts in languages and metamodels for Enterprise Modelling. These architectures and metamodels mostly emphasize technical aspects that constitute Smart Cities and they rarely focus on city services and their strategic aspects towards delivering the cities vision and objectives. This research introduces ArchiSmartCity, a metamodel that addresses the alignment between city services and information systems according to Smart City strategies to assist in the digitalisation of public city services. In this thesis, design principles and design requirements are defined and instantiated by designing the ArchiSmartCity metamodel that explicitly expresses this alignment, following a design science research approach. Further, ArchiSmartCity is developed and implemented as a coherent extension of an EA metamodel to describe an expository instantiation and its application. ArchiSmartCity is evaluated in an iterative manner within multiple-case studies, by creating real-world services models that are validated by Smart City domain experts. Moreover, this thesis demonstrates and evaluates ArchiSmartCity by developing a computer-based solution for semantic alignment analysis. Ex-post evaluation results demonstrate the quality and practical relevance of the developed metamodel extension for cities and municipalities. This study contributes to the current understanding of how city strategies should be aligned with Smart City implementations by providing a prescriptive view and metamodel to guide coherent and unambiguous architecture design in the Smart Cities field