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The current thesis presents research about new methods of citizen participation based on digital technologies. The focus on the research lies on decentralized methods of participation where citizens take the role of co-creators. The research project first conducted a review of the literature on citizen participation, its origins and the different paradigms that have emerged over the years. The literature review also looked at the influence of technologies on participation processes and the theoretical frameworks that have emerged to understand the introduction of technologies in the context of urban development. The literature review generated the conceptual basis for the further development of the thesis.
The research begins with a survey of technology enabled participation applications that examined the roles and structures emerging due to the introduction of technology. The results showed that cities use technology mostly to control and monitor urban infrastructure and are rather reluctant to give citizens the role of co-creators. Based on these findings, three case studies were developed. Digital tools for citizen participation were conceived and introduced for each case study. The adoption and reaction of the citizens were observed using three data collection methods.
The results of the case studies showed consistently that previous participation and engagement with informal citizen participation are a determinining factor in the potential adoption of digital tools for decentralized engagement. Based on these results, the case studies proposed methods and frameworks that can be used for the conception and introduction of technologies for decentralized citizen participation.
In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases, that have been used to test and further develop our concepts and implementations.
This work presents a concept of interactive machine learning in a human design process. An urban design problem is viewed as a multiple-criteria optimization problem. The outlined feature of an urban design problem is the dependence of a design goal on a context of the problem. We model the design goal as a randomized fitness measure that depends on the context. In terms of multiple-criteria decision analysis (MCDA), the defined measure corresponds to a subjective expected utility of a user. In the first stage of the proposed approach we let the algorithm explore a design space using clustering techniques. The second stage is an interactive design loop; the user makes a proposal, then the program optimizes it, gets the user’s feedback and returns back the control over the application interface.
In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of a calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases that have been used to test and further develop our concepts and implementations.