Achieving interoperability of smart city data: An analysis of 311 datas

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Soroosh Nalchiga, Mark Fox

Abstract


A major challenge in making cities smarter is performing comparative analyses across two or more cities, or within a city across two or more departments. The problem is that data models and the underlying semantics of their content differ, making analysis difficult at best and erroneous at worst. This paper explores the hypothesis that a single, interoperable (i.e., shareable) data model/ontology can be designed for one category of city data: openly published 311 call centre data. 311 is a service provided by many North American cities that responds to non-emergency questions and reports made by the public. It has rapidly become the single point of contact for city services, inquiries, etc. We perform a semantic analysis of the content of 311 open datasets from four cities. The result of the analysis is that existing 311 datasets combine multiple semantic dimensions in their data making it impossible to perform comparative analysis. We then construct a 311 Reference Ontology that separates the semantic dimensions, and show how 311 data from multiple cities can be mapped onto the 311 Reference Ontology.  We also demonstrate how the ontology can be used to support analysis

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DOI: http://dx.doi.org/10.26789/JSC.2017.01.001

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Copyright (c) 2017 Mark Fox

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


 

Journal of Smart Cities is a peer-reviewed, open-access journal. All journal content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.