Advanced data analytics and visualisation for the management of human perception of safety and security in urban spaces

Abstract

The genesis of this work began during the DESURBS project. The scope of the project was to help build a collaborative decision-support system portal where spatial planning professionals could learn about designing much more secure and safer spaces in urban areas. The portal achieved this via integrating a number of tools under a common, simple to use, interface. However, the deficiencies in the project became apparent with subsequent development. Many of the open data employed changed format while applications were increasingly custom built for a single dataset. In order to overcome this a system called KnowDS was redesigned. The essence of the new design includes decoupling acquisition, analysis and overall presentation of data components. The acquisition component was designed to snap-shot the “data providing methods” and query data provenance in a similar way to a source code repository. The analysis component is built under a number of modular tools with a common interface which allows analysis to build in a plug&play approach. Finally, the data presentation component is where the custom logic goes. Under such design approach, the building of future applications becomes less challenging. As a consequence, two case studies using the new framework were considered. Firstly, a UK crime web-browser which allows data analytics performances at various granularities of crime types while correlating crimes across various UK cities has been achieved. Secondly, a mobile application which enables to generate reports on citizens’ perception of safety in urban zones has also been developed. The two applications were efficiently built under the new design framework; and they clearly demonstrate the capacity of the new system while they actively generate new knowledge about safety in urban spaces

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Identifiers

ORCID for Gianluca Correndo: orcid.org/0000-0003-3335-5759

ORCID for Zoheir Sabeur: orcid.org/0000-0003-4325-4871

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