Ontology-based Classification and Analysis of non- emergency Smart-city Events

Abstract—Several challenges are faced by citizens of urban centers while dealing with day-to-day events, and the absence of a centralized reporting mechanism makes event-reporting and redressal a daunting task. With the push on information technology to adapt to the needs of smart-cities and integrate urban civic services, the use of Open311 architecture presents an interesting solution. In this paper, we present a novel approach that uses an existing Open311 ontology to classify and report non-emergency city-events, as well as to guide the citizen to the points of redressal. The use of linked open data and the semantic model serves to provide contextual meaning and make vast amounts of content hyper-connected and easily-searchable. Such a one-size-fits-all model also ensures reusability and effective visualization and analysis of data across several cities. By integrating urban services across various civic bodies, the proposed approach provides a single endpoint to the citizen, which is imperative for smooth functioning of smart cities.

Keywords—Smart Cities; Open311; SPARQL; Linked Open Data (LOD); Semantic Web. I. INTRODUCTION Around the world, cities aspire to provide their residents better access to civic services and a superior quality of life. However, as cities grow, developing applications for urban areas that could improve the management of urban flows and allow for real time responses to challenges becomes a pressing need. In several Indian cities and urban centers, the individual entities and different government bodies are sparsely connected that leads to a poor flow of resources and information residents encounter in their daily lives, a variety of events like disruptions in services and utilities, inconvenience caused by elements in the environment, or need for information and updates from the civic authorities. Due to the dissociated nature of the bodies, they often find themselves in a difficult situation to handle such events, e.g., if someone wants to report about stagnant water on the streets that have persisted for more than a few days, they are usually unaware about whom to contact. In such a situation, citizens have to approach multiple authorities before reaching the concerned ones. Although it is difficult to precisely define a ‘smart city’, Deakin and Al Waer list four factors [1] that contribute to the definition of a smart city: (i) The application of a wide range of electronic and digital technologies to communities and cities.
(ii) The use of ICT to transform life and working environments within the region. (iii) The embedding of such ICTs in government systems. (iv)The territorialisation of practices that brings ICTs and people together to enhance the innovation and

knowledge that they offer. Therefore, ICT plays a vital role in information management and analysis in the event and data- driven smart cities. At the same time, the expedited growth of population and access to technology in cities necessitates the generation of huge amounts of data. But city-data originating from heterogeneous sources cannot be effectively integrated or analyzed unless they share common vocabulary and semantics [2]. A semantic data model of a city is, therefore, the most feasible solution as it not only provides cohesive and integrated data access across city’s data sources, but also leads to reusability and can be used for replicating the same across other cities as well. An important breakthrough in this endeavor has been the introduction of the Open311 open standard for civic issue tracking. As a technical standard, it’s a protocol that software systems can implement to create interoperable systems. The Open311 standard has been successfully implemented in various cities around the world such as Helsinki, Chicago, Toronto, San Francisco among many others. An exhaustive list can be found on the Open 3111 official website. ‘311’ is the contact number and name, used primarily in North America, of organizations that help to provide responses to non-emergency requests and reports submitted by the citizens. An ontology enables the integration of 311 data from a myriad of cities with consistent semantics [3]. In our paper, we have used an Open311-ontology2 created at the University of Toronto by Nalchigar and Fox to annotate and map non- emergency city events to a semantic framework, and provide residents a single endpoint to report, query and reach the concerned authorities according to their complaint. A complete and authoritative ontology simplifies the development of applications that require integ

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