QuerioCity: A Linked Data Platform for Urban Information Management

López, Vanessa; Kotoulas, Spyros; Sbodio, Marco Luca; Stephenson, Martin; Gkoulalas-Divanis, Aris; Aonghusa, Pól Mac

doi:10.1007/978-3-642-35173-0_10

Cited by 44 publications

(26 citation statements)

References 11 publications

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“…First of all, the heterogeneity of this data poses challenges on identifying the relevant sources of information for specific needs, e.g. from different repositories in the linked data cloud [2], or otherwise fusing multiple sources of information including sensor streams [3]. Also, this data can be noisy, messy and incomplete, which adds an additional burden of cleansing, capturing the anomalies, and consolidating multiple sources.…”

Section: Cities Of the 21mentioning

confidence: 99%

Information Access in Smart Cities (i-ASC)

Albakour

Macdonald

Ounis

et al. 2014

Lecture Notes in Computer Science

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Abstract. Modern cities are becoming smart where a digital knowledge infrastructure is deployed by local authorities (e.g. City councils and municipalities) to better serve the information needs of their citizens, and to ensure sustainability and efficient use of power and resources. This knowledge infrastructure consists of a wide range of systems from lowlevel physical sensors to advanced sensing devices through social sensors. This proposed workshop will be a venue for research on digesting the city's data streams and knowledge databases in order to serve the information needs of citizens and support decision making for local authorities. Possible use cases include helping tourists to find interesting places to go or activities to do while visiting a city, or assisting journalists in reporting local incidents. Indeed, this workshop will foster the development of new information access and retrieval models that can harness effectively and efficiently the large number of heterogeneous big data streams in a city to provide a new generation of information services. Background, Motivation and ThemesCities of the 21 st century do not only have the physical infrastructure of roads, buildings, and power networks, but also have the knowledge infrastructure represented with heterogeneous systems and big data platforms. These systems vary from low-level sensing devices including environmental sensors and CCTV cameras, to public databases, and social network streams. On the other hand, a recent study [1] has identified a variety of emerging information needs that citizens often have in their public urban spaces. These local information needs may be complex and are not necessarily served by existing systems such as web search engines. These include obtaining real-time information about events in the city or finding free parking spaces. The aforementioned knowledge infrastructure opens up opportunities for cities to become smarter and serve the emerging information needs of their citizens by harnessing the vast amount of diverse information stemming from the various systems within the city.The proposed workshop would be an opportunity for researchers from the information retrieval (IR) community, and other related communities, to discuss M. de Rijke et al.

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Section: Cities Of the 21mentioning

confidence: 99%

Information Access in Smart Cities (i-ASC)

Albakour

Macdonald

Ounis

et al. 2014

Lecture Notes in Computer Science

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“…Following Linked Data principles, we previously created a metadata catalogue to index and search heterogeneous city data coming from the DubLinked Web portal, as described in [8].…”

Section: Publishing Cataloguing and Indexingmentioning

confidence: 99%

“…However, this is not enough to enable queries that span across datasets. As described in [8], a set of challenges in managing urban information remains: the openness of the domain, the lack of a common model, the diversity of the data formats, the volume of information and the requirement for a low entry threshold. To address these challenges, we have qualified the advantages of using an incremental semantic approach based on a graph data model to go from raw data to structured data consumption, eliminating the need for tight integration imposed by relational databases.…”

Section: Introductionmentioning

confidence: 99%

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Guided exploration and integration of urban data

López

Kotoulas

Sbodio

et al. 2013

Proceedings of the 24th ACM Conference on Hypertext and Social Media

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Governments and enterprises are interested in the return-oninvestment for exposing their data. This brings forth the problem of making data consumable, with minimal effort. Beyond search techniques, there is a need for effective methods to identify heterogeneous datasets that are closely related, as part of data integration or exploration tasks. The large number of datasets demands a new generation of Smarter Systems for data content aggregation that allows users to incrementally liberate, access and integrate information, in a manner that scales in terms of gain for the effort spent. In the context of such a pay-as-you go system, we are presenting a novel method for exploring and discovering relevant datasets based on semantic relatedness. We are demonstrating a system for contextual knowledge mining on hundreds of real-world datasets from Dublin City. We evaluate our semantic approach, using query logs and domain expert judgments, to show that our approach effectively identifies related datasets and outperforms text-based recommendations.

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“…To achieve this, such systems must integrate heterogenous information such as service timetables, details of routes, and GPS-based vehicle locations, all of which may be provided by different agencies [3]. This paper reports on the work of the Informed Rural Passenger 1 project which investigated the suitability of a Semantic Web approach to data integration and use [4,5] for smart mobility applica-tions. RTPI systems are rare in rural areas, due to a lack of supporting infrastructure and the cost of maintaining technologies such as vehicle tracking in rural environments [6].…”

Section: Introductionmentioning

confidence: 99%

Linking open data and the crowd for real-time passenger information

Corsar

Edwards

Nelson

et al. 2017

Journal of Web Semantics

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The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cost of deploying and maintaining the required technologies outside of urban areas is seen as prohibitive. In this paper we present the GetThere system developed to overcome such issues and to provide public transport users in rural areas with RTPI. An ontological framework for representing mobility information is described, along with the Linked Data approach used to integrate heterogeneous data from multiple sources including government, transport operators, and the public. To mitigate possible issues with the veracity of this data, a quality assessment framework was developed that utilises data provenance. We also discuss our experiences working with Semantic Web technologies in this domain, and present results from both a user trial and a performance evaluation of the system.

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QuerioCity: A Linked Data Platform for Urban Information Management

Cited by 44 publications

References 11 publications

Information Access in Smart Cities (i-ASC)

Information Access in Smart Cities (i-ASC)

Guided exploration and integration of urban data

Linking open data and the crowd for real-time passenger information

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