Citizen participation for social innovation and co-creating urban regeneration proposals can be greatly facilitated with 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 provide an integrated top-down and bottom-up urban planning and decision making approach to smart cities. However, generating automated feedback on citizens initiated 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 platform 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 automated feedback feature for Hamburg use case ‘planting trees’ is demonstrated. Early results and lessons learned yield 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.
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