Citizen participation for social innovation and co-creating urban regeneration proposals can be greatly facilitated by innovative IT systems. Such systems can use Open Government Data, visualise urban proposals in 3D models and provide automated feedback on the feasibility of the proposals. Using such a system as a communication platform between citizens and city administrations provides an integrated top-down and bottom-up urban planning and decision-making approach to smart cities. However, generating automated feedback on citizens' proposals requires modelling domain-specific knowledge i.e., vocabulary and rules, which can be applied on spatial and temporal 3D models. This paper presents the European Commission funded H2020 smarticipate project that aims to achieve the above challenge by applying it on three smart cities: Hamburg, Rome and RBKC-London. Whilst the proposed system architecture indicates various innovative features, a proof of concept of the automated feedback feature for the Hamburg use case 'planting trees' is demonstrated. Early results and lessons learned show that it is feasible to provide automated feedback on citizen-initiated proposals on specific topics. However, it is not straightforward to generalise this feature to cover more complex concepts and conditions which require specifying comprehensive domain languages, rules and appropriate tools to process them. This paper also highlights the strengths of the smarticipate platform, discusses challenges to realise its different features and suggests potential solutions.

Abstract.As climate change appears, strategies and actions will be necessary to cope with its effects on environment and society in the coming decades. Current climate conditions can be observed everywhere in the world but future climate conditions can only be estimated through climate simulations which produce huge amounts of quantitative data. This data leads to statements like "temperature increase is expected to exceed 2.6• C" or similar and remain fuzzy to non-experts in climate research. The Climate Twins application is designed to communicate climate changes in an intuitive and understandable way by showing regions which have now similar climate conditions according to a given Point of Interest (POI) in the future. This paper explains how the application seeks for locations with similar climatological patterns according to the POI. To achieve this goal a method has been developed to quantify similarity between two locations' climate data.

<p><strong>Abstract.</strong> Citizen participation, co-creation &amp;ndash; a joint development of professionals and citizens &amp;ndash; initiatives for urban planning processes have increased significantly during the last few years. This development has been strongly supported by the evolution of Information and Communication Technologies (ICT). E.g., it has never been easier to get information through your mobile devices wherever and whenever you want it. Public open spatial data is available in many cities around the world and web-based applications use this data to provide tools and services for many different topics such as traffic information, or the communication of health-related information (e.g. ozone, particulate matter or pollen loads). This paper presents typical problems of such web-applications in terms of application design and implementation and usability evaluation via describing three case study applications which have been developed recently. It tries to answer the question: How can this kind of geo-services be developed and used by scientists to enable public participation within data gathering and urban planning processes? All three applications have the common goal to provide interactive geo-visualization and analysis features which are tailored to support users in their urban planning processes. The innovation of those applications lies in their flexibility regarding the topics they can tackle and their capability to perform interactive analyses triggered by the user. The applications have been built with a strong focus on exploring the available data (e.g. Open Government Data &amp;ndash; OGD). Two of the applications have been implemented using the R-Shiny framework, the third application, the smarticipate platform, has been developed using ReactJS for the front-end, running a MongoDB in the background which is fed via a micro-service framework. In the latter application, the users can configure topics, i.e. the platform enables the user to create new services for different planning issues.</p>

Abstract. This paper explains the first insights into the ongoing development of a CityGML based Food Water Energy Application Domain Extension (FWE ADE). Cities are undergoing rapid expansion throughout the globe. As a result, they face a common challenge to provide food, water and energy (FWE) supplies under healthy and economically productive conditions. Consequently, new tools and techniques must be developed to support decision-makers, such as governments, public or private infrastructure providers, investors and city developers, to understand, quantify and visualise multiple interdependent impacts for the sustainable supply of the FWE resources. However, a common practice amongst these stakeholders is to work in their data silos, which frequently results in a lack of data integration and communication between domain specific simulation tools belonging to different infrastructure departments. As a result, insights related to critical indicators showing inter-dependency amongst different urban infrastructure are missed and hence, not included in the cities’ redevelopment action plan. This paper documents the first ongoing attempt by an international group of domain experts from food, water, energy, urban design and geoinformatics to harmonise the data silos of food, water and energy domain for the case study regions of the County of Ludwigsburg in Germany, the city of Vienna in Austria and the neighbourhood of Gowanus in New York, the United States of America.

Worldwide, cities are nowadays formulating their own sustainability goals, including ambitious targets related to the generation and consumption of energy. In order to support decision makers in reaching these goals, energy experts typically rely on simulation models of urban energy systems, which provide a cheap and efficient way to analyze potential solutions. The availability of high-quality, well-formatted and semantically structured data is a crucial prerequisite for such simulation-based assessments. Unfortunately, best practices for data modelling are rarely utilized in the context of energy-related simulations, so data management and data access often become tedious and cumbersome tasks. However, with the steady progress of digitalization, more and more spatial and semantic city data also become available and accessible. This paper addresses the challenge to represent these data in a way that ensures simulation tools can make use of them in an efficient and user-friendly way. Requirements for an effective linking of semantic 3D city models with domain-specific simulation tools are presented and discussed. Based on these requirements, a software prototype implementing the required functionality has been developed on top of the CityGML standard. This prototype has been applied to a simple yet realistic use case, which combines data from various sources to analyze the operating conditions of a gas network in a city district. The aim of the presented approach is to foster a stronger collaboration between experts for urban data modelling and energy simulations, based on a concrete proof-of-concept implementation that may serve as an inspiration for future developments.