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Information 2017, 8(2), 47; doi:10.3390/info8020047

Developing Knowledge-Based Citizen Participation Platform to Support Smart City Decision Making: The Smarticipate Case Study

1
Department of Computer Science and Creative Technologies, University of the West of England, Bristol BS16 1QY, UK
2
Fraunhofer IGD, Competence Centre for Spatial Information Management, Fraunhoferstrasse 5, 64283 Darmstadt, Germany
3
Austrian Institute of Technology-AIT, Center for Energy, Giefinggasse 6, 1210 Vienna, Austria
4
Austrian Institute of Technology-AIT, Center for Technology Experience, Giefinggasse 2, 1210 Vienna, Austria
5
Wetransform GmbH, Fraunhoferstrasse 5, 64283 Darmstadt, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 28 February 2017 / Revised: 12 April 2017 / Accepted: 15 April 2017 / Published: 21 April 2017
(This article belongs to the Special Issue Smart City Technologies, Systems and Applications)
View Full-Text   |   Download PDF [5309 KB, uploaded 21 April 2017]   |  

Abstract

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. View Full-Text
Keywords: citizen participation; knowledge generation; automated feedback; planning proposals; domain vocabulary and rule languages citizen participation; knowledge generation; automated feedback; planning proposals; domain vocabulary and rule languages
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Khan, Z.; Dambruch, J.; Peters-Anders, J.; Sackl, A.; Strasser, A.; Fröhlich, P.; Templer, S.; Soomro, K. Developing Knowledge-Based Citizen Participation Platform to Support Smart City Decision Making: The Smarticipate Case Study. Information 2017, 8, 47.

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