Cited By
View all- Desimoni FIlarri SPo LRollo FTrillo-Lado R(2020)Semantic Traffic Sensor Data: The TRAFAIR ExperienceApplied Sciences10.3390/app1017588210:17(5882)Online publication date: 25-Aug-2020
LODGVis: an interactive visualization for linked open data navigation
Authors: 
Danilo Barbosa Coimbra, José Olimpio Mouzinho Negrão, 
Frederico Araujo DurãoAuthors Info & Claims
Danilo Barbosa Coimbra, José Olimpio Mouzinho Negrão, Frederico Araujo DurãoAuthors Info & ClaimsPages 433 - 440
Abstract
The amount of structured data available on the Web in semantic formats have been growing enormously in recent years. In this scenario, Linked Data effort is essential to retrieve detailed information from the Web, especially if we consider the importance of the Web in our daily lives and activities. However, there is a lack of tools and techniques that allow users to properly navigate on Linked Data formats, such as Resource Description Framework (RDF) documents. This work aims to present LODGVis, a novel interactive visualization technique that enables navigation throughout RDF documents. This technique was developed as an open source Web application and provides a visual exploratory approach that allows users to freely browse semantic data through graphs-base visualization considering several features, including customization, aggregation and multiple level navigation. Our study case considers DBpedia data set, but our technique can be easily extended to any RDF-based data set.
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Index Terms
- LODGVis: an interactive visualization for linked open data navigation
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Published In
October 2019
537 pages
ISBN:9781450367639
DOI:10.1145/3323503
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Published: 29 October 2019
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WebMedia '19
WebMedia '19: Brazilian Symposium on Multimedia and the Web
October 29 - November 1, 2019
Rio de Janeiro, Brazil
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View all- Desimoni FIlarri SPo LRollo FTrillo-Lado R(2020)Semantic Traffic Sensor Data: The TRAFAIR ExperienceApplied Sciences10.3390/app1017588210:17(5882)Online publication date: 25-Aug-2020
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