Managing road safety through the use of linked data and heat maps

Colacino, Vincenzo Giuseppe; Po, Laura

doi:10.1145/3102254.3102273

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Further, based on SGO, we automatically generated RDF datasets. The resulting RDF data were at the 4-star level of 5-star open data model [18]. In addition, based on the ontology design patterns, we provided a solid model and rich semantic vocabularies for promoting the goal of opening Saudi OGD with linked data technologies.…”

Section: The Saudi Linked Open Government Data Ontology (Slogdo)mentioning

confidence: 99%

A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia

et al. 2020

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Due to the wide-ranging development of data-oriented sustainable systems in the government and the public sectors, the development of such sustainable systems is replete with potential. The ultimate focus of developing these sustainable systems is to provide citizens with transparency, accountability, awareness as well as a single point of query for asking integrated and smart queries. In view of these benefits, the Saudi government has taken the initiative to publish and develop sustainable open data-oriented information systems. However some major challenges in the Saudi Government Open Data are that the (1) data are published and available in different formats such as Excel sheets, CSV files (Comma Separated Values), images, scanned documents and social media sources such as Twitter, (2) datasets from different government departments are not linked with each other or to existing datasets in Linked Open Data Cloud (even though they have strong links with each other), and (3) there is no SPARQL Endpoint that can be used to pose smart semantic-based queries to Saudi Government Data. This paper is part of an ongoing research project to present a framework that can be used to transfer the government data from different sources to RDF format. The framework can also be used to clean and classify/map the data according to the Saudi Government Ontology. We also describe our approach for semiautomatically linking Saudi Government Datasets with one another as well as with other existing open datasets, thus resulting in the Saudi Linked Open Government Data Cloud (SLOGDC). Finally, taking the topic “Public’s Response to Women’s Driving in Saudi Arabia” as a case study, we demonstrate the SLOGD SPARQL Endpoint as a data-oriented system by executing different queries and analyzing results of these queries. This work also contributes new insights into women’s driving in Saudi Arabia using the SLOGDC, thus suggesting the way forward in shaping policies for decision-making.

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Section: The Saudi Linked Open Government Data Ontology (Slogdo)mentioning

confidence: 99%

A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia

et al. 2020

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“…On the other hand, the analysis of traffic data is crucial not only for the development of smart traffic management systems (e.g., see [3]) but also for making the cities more safe, healthy, and sustainable [4]. Several European countries have adopted the Vision Zero and Safe System approach [5], to eliminate deaths and grave injuries on European roads.…”

Section: Introductionmentioning

confidence: 99%

Semantic Traffic Sensor Data: The TRAFAIR Experience

Desimoni

Ilarri

et al. 2020

Applied Sciences

Self Cite

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Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective.

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Building an Urban Theft Map by Analyzing Newspaper Crime Reports

Rollo

2018

2018 13th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)

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Crime analysis is a set of systematic, analytical processes directed at providing timely and pertinent information relative to crime patterns and trend correlations in order to assist the police in crime reduction, prevention, and evaluation.Crime mapping is the process of using a geographic information system (GIS) to conduct spatial analysis of crime problems.Mapping crime allows police analysts to identify crime hot spots, moreover it increases public confidence and citizen engagement and promotes transparency. Crime MappingCrime analysis [1] is a set of systematic, analytical processes directed at providing timely and pertinent information relative to crime patterns and trend correlations in order to assist the police in crime reduction, prevention, and evaluation.Crime mapping [2] is the process of using a geographic information system (GIS) to conduct spatial analysis of crime problems.Mapping crime allows police analysts to identify crime hot spots, moreover it increases public confidence and citizen engagement and promotes transparency.

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Managing road safety through the use of linked data and heat maps

Cited by 3 publications

References 7 publications

A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia

A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia

Semantic Traffic Sensor Data: The TRAFAIR Experience

Building an Urban Theft Map by Analyzing Newspaper Crime Reports

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