scholarly journals Adding value to Linked Open Data using a multidimensional model approach based on the RDF Data Cube vocabulary

2020 ◽  
Vol 68 ◽  
pp. 103378 ◽  
Author(s):  
Pilar Escobar ◽  
Gustavo Candela ◽  
Juan Trujillo ◽  
Manuel Marco-Such ◽  
Jesús Peral
Keyword(s):  
Open Data ◽  
Data Cube ◽  
Linked Open Data ◽  
Multidimensional Model ◽  
Rdf Data ◽  
Model Approach

scholarly journals Multidimensional Open Government Data

2016 ◽  
Vol 8 (3) ◽  
pp. 1-11 ◽  
Author(s):  
Efthimios Tambouris
Keyword(s):  
Open Data ◽  
Data Cube ◽  
Linked Open Data ◽  
Open Government ◽  
Multidimensional Data ◽  
Data Publication ◽  
Data Fragmentation ◽  
Open Government Data ◽  
Important Challenge ◽  
Government Data

A large number of open government data concerns official and unofficial statistics. These data can be represented as multidimensional data. In this paper, we commence by presenting data fragmentation, an important challenge when exploiting open data. We thereafter introduce multidimensional data as a possible solution to overcome data fragmentation. More specifically, we outline the data cube model and linked open data technologies. In addition, we present a process for multidimensional linked open data publication and reuse. We also present a number of software tools that have been developed to manage multidimensional linked open data. We finally summarize the benefits and some of the main barriers.

scholarly journals Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels

2019 ◽  
Vol 8 (8) ◽  
pp. 353 ◽  
Author(s):  
Alejandro Vaisman ◽  
Kevin Chentout
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Relational Databases ◽  
Open Data ◽  
Linked Open Data ◽  
Sparql Endpoint ◽  
External Data ◽  
Triple Store ◽  
Rdf Data ◽  
Map Data

This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. The second part of the paper shows, through a comprehensive set of the spatial extension to SPARQL (stSPARQL) queries, how the endpoint can be exploited.

Link maintenance for integrity in linked open data evolution: Literature survey and open challenges

Semantic Web ◽  
2020 ◽  
pp. 1-25
Author(s):  
Andre Gomes Regino ◽  
Julio Cesar dos Reis ◽  
Rodrigo Bonacin ◽  
Ahsan Morshed ◽  
Timos Sellis
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Open Data ◽  
Linked Open Data ◽  
Evolutionary Characteristic ◽  
Rdf Data ◽  
Link Maintenance ◽  
Data Elements ◽  
Data Evolution ◽  
Over Time

RDF data has been extensively deployed describing various types of resources in a structured way. Links between data elements described by RDF models stand for the core of Semantic Web. The rising amount of structured data published in public RDF repositories, also known as Linked Open Data, elucidates the success of the global and unified dataset proposed by the vision of the Semantic Web. Nowadays, semi-automatic algorithms build connections among these datasets by exploring a variety of methods. Interconnected open data demands automatic methods and tools to maintain their consistency over time. The update of linked data is considered as key process due to the evolutionary characteristic of such structured datasets. However, data changing operations might influence well-formed links, which turns difficult to maintain the consistencies of connections over time. In this article, we propose a thorough survey that provides a systematic review of the state of the art in link maintenance in linked open data evolution scenario. We conduct a detailed analysis of the literature for characterising and understanding methods and algorithms responsible for detecting, fixing and updating links between RDF data. Our investigation provides a categorisation of existing approaches as well as describes and discusses existing studies. The results reveal an absence of comprehensive solutions suited to fully detect, warn and automatically maintain the consistency of linked data over time.

scholarly journals Multidimensional enrichment of spatial RDF data for SOLAP

Semantic Web ◽  
2021 ◽  
pp. 1-35
Author(s):  
Nurefşan Gür ◽  
Torben Bach Pedersen ◽  
Katja Hose ◽  
Mikael Midtgaard
Keyword(s):  
Semantic Web ◽  
Spatial Data ◽  
Spatial Information ◽  
Complex Geometry ◽  
Open Data ◽  
Data Cube ◽  
Multidimensional Data ◽  
Wide Range ◽  
Advanced Analysis ◽  
Rdf Data

Large volumes of spatial data and multidimensional data are being published on the Semantic Web, which has led to new opportunities for advanced analysis, such as Spatial Online Analytical Processing (SOLAP). The RDF Data Cube (QB) and QB4OLAP vocabularies have been widely used for annotating and publishing statistical and multidimensional RDF data. Although such statistical data sets might have spatial information, such as coordinates, the lack of spatial semantics and spatial multidimensional concepts in QB4OLAP and QB prevents users from employing SOLAP queries over spatial data using SPARQL. The QB4SOLAP vocabulary, on the other hand, fully supports annotating spatial and multidimensional data on the Semantic Web and enables users to query endpoints with SOLAP operators in SPARQL. To bridge the gap between QB/QB4OLAP and QB4SOLAP, we propose an RDF2SOLAP enrichment model that automatically annotates spatial multidimensional concepts with QB4SOLAP and in doing so enables SOLAP on existing QB and QB4OLAP data on the Semantic Web. Furthermore, we present and evaluate a wide range of enrichment algorithms and apply them on a non-trivial real-world use case involving governmental open data with complex geometry types.

Europeana no Linked Open Data: conceitos de Web Semântica na dimensão aplicada das humanidades digitais

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Caio Saraiva Coneglian ◽  
José Eduardo Santarem Segundo
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Linked Open Data

O surgimento de novas tecnologias, tem introduzido meios para a divulgação e a disponibilização das informações mais eficientemente. Uma iniciativa, chamada de Europeana, vem promovendo esta adaptação dos objetos informacionais dentro da Web, e mais especificamente no Linked Data. Desta forma, o presente estudo tem como objetivo apresentar uma discussão acerca da relação entre as Humanidades Digitais e o Linked Open Data, na figura da Europeana. Para tal, utilizamos uma metodologia exploratória e que busca explorar as questões relacionadas ao modelo de dados da Europeana, EDM, por meio do SPARQL. Como resultados, compreendemos as características do EDM, pela utilização do SPARQL. Identificamos, ainda, a importância que o conceito de Humanidades Digitais possui dentro do contexto da Europeana.Palavras-chave: Web semântica. Linked open data. Humanidades digitais. Europeana. EDM.Link: https://periodicos.ufsc.br/index.php/eb/article/view/1518-2924.2017v22n48p88/33031

scholarly journals A Hybrid Approach Combining R*-Tree and k-d Trees to Improve Linked Open Data Query Performance

2021 ◽  
Vol 11 (5) ◽  
pp. 2405
Author(s):  
Yuxiang Sun ◽  
Tianyi Zhao ◽  
Seulgi Yoon ◽  
Yongju Lee
Keyword(s):  
Flash Memory ◽  
Query Language ◽  
Hybrid Approach ◽  
Open Data ◽  
Main Memory ◽  
Linked Open Data ◽  
Index Structure ◽  
Identification Algorithm ◽  
Distributed Computing Systems ◽  
Query Performance

Semantic Web has recently gained traction with the use of Linked Open Data (LOD) on the Web. Although numerous state-of-the-art methodologies, standards, and technologies are applicable to the LOD cloud, many issues persist. Because the LOD cloud is based on graph-based resource description framework (RDF) triples and the SPARQL query language, we cannot directly adopt traditional techniques employed for database management systems or distributed computing systems. This paper addresses how the LOD cloud can be efficiently organized, retrieved, and evaluated. We propose a novel hybrid approach that combines the index and live exploration approaches for improved LOD join query performance. Using a two-step index structure combining a disk-based 3D R*-tree with the extended multidimensional histogram and flash memory-based k-d trees, we can efficiently discover interlinked data distributed across multiple resources. Because this method rapidly prunes numerous false hits, the performance of join query processing is remarkably improved. We also propose a hot-cold segment identification algorithm to identify regions of high interest. The proposed method is compared with existing popular methods on real RDF datasets. Results indicate that our method outperforms the existing methods because it can quickly obtain target results by reducing unnecessary data scanning and reduce the amount of main memory required to load filtering results.

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