This book is a journey through coexisting, emerging or speculated about, types of digital value transfer infrastructures. Using digital value transfer infrastructures as a central case study, this thesis is concerned with unpacking the negotiation processes that shape the governance, design and political purposes of digital infrastructures that are closely linked to the public interest and state sovereignty. In particular, the papers that are assembled in this manuscript identify and inspect three main socio-technical developments occurring in the domain of value transfer technologies: a) the privatization and platformization of digital payment infrastructures; b) the spread of blockchain-based digital value transfer infrastructures; c) the construction of digital value transfer infrastructures as public utilities, from the part of public institutions or organizations. Concerned with the relationship between law, discourse and technological development, the thesis explores four transversal issues that strike differences and peculiarities of these three scenarios: i) privacy; ii) the synergy and mutual influence of legal change and technological development in the construction of digital infrastructures; iii) the role of socio-technical imaginaries in policy-making concerned with digital infrastructures; iv) the geography and scale of digital infrastructures. The analyses lead to the argument that, in the co-development of legal systems and digital infrastructures that are core to public life, conflicts are productive. Negotiations, ruptures and exceptions are constitutive of the unending process of mutual reinforcement, and mutual containment, in which a plurality of agencies – expressed through legal institutions, symbolic systems, as well as information and media structures – are entangled.
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This book analyses the values and processes that characterise DIY (do it yourself) digital infrastructure, relating networked initiatives to broader tensions in contemporary alternative media production, namely between ideology and practice in cultural and artistic networked initiatives. Adopting immersive and direct engagement methods, focusing specifcially on the case of A Traversal Network of Feminist Servers, this book shows that contemporary alternative media projects are defined mainly by the people and the networks they build — alternative infrastructures are about the process driving them, more so than the content produced. Small or local organisations intervene in infrastructures by building responses to extractivist platform models, but can be exclusive to the communities already involved in the process. Nevertheless, alternative media initiatives are culturally and socially significant, as they produce critical media discourses and network imaginaries that signify a call for better digital and technical literacy in society.
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Climate change and changing land use challenge the livability and flood safety of Dutch cities. One option cities have to become more climate-proof is to increase infiltration of stormwater into soil through permeable pavement and thus reduce discharge of stormwater into sewer systems. To analyze the market receptivity for permeable pavements in the Netherlands, this article focuses on the perception of end-users towards key transition factors in the infrastructure transformation processes. Market receptivity was studied on two levels: (1) on the system level, by analyzing 20 key factors in the Dutch urban water sector that enable wider application of permeable pavements; and (2) on the technology level, by analyzing 12 key factors that explain why decision makers select permeable pavements or not. Results show that trust between cooperating partners was perceived as the system level key factor that needs to be improved most to facilitate the wider uptake of permeable pavements. Additionally, the association of end-users with permeable pavement, particularly their willingness to apply these technologies and their understanding of what kinds of benefits these technologies could bring, was regarded the most important receptivity attribute. On the technology level, the reliability of permeable pavement was regarded as the most important end-user consideration for selecting this technology.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
298 woorden: In the upcoming years the whole concept of mobility will radically change. Decentralization of energy generation, urbanization, digitalization of processes, electrification of vehicles and shared mobility are only some trends which have a strong influence on future mobility. Furthermore, due to the shift towards renewable energy production, the public and the private sector are required to develop new infrastructures, new policies as well as new business models. There are countless opportunities for innovative business models emerging. Companies in this field – such as charging solution provider, project management or consulting companies that are part of this project, Heliox and Over Morgen respectively – are challenged with countless possibilities and increasing complexity. How to overcome this problem? Academic research proposes a promising approach, namely the use of business model patterns for business model innovation. In short, these business model patterns are descriptions of proven practical solutions to common business model challenges. An example for a general pattern would be the business model pattern “Consumables”. It describes how to lock in a customer into an ecosystem by using a subsidized basic product and complement it with overpriced consumables. This pattern works really well and has been used by many companies (e.g. Senseo, HP, or Gillette). To support the business model innovation process of Heliox and Over Morgen as well as companies in the electric mobility space in general, we propose to systematically consolidate and develop business model patterns for the electric mobility sector and to create a database. Electric mobility patterns could not only foster creativity in the business model innovation process but also enhance collaboration in teams. By having a classified list of business model pattern for electric mobility, practitioners are equipped which a heuristic tool to create, extend and revise business models for the future.
