Data-transformation on historical data using the RDF data cube vocabulary

2015 ◽  
Author(s):  
Sebastian Bayerl ◽  
Michael Granitzer
Keyword(s):  
Historical Data ◽  
Data Transformation ◽  
Data Cube ◽  
Rdf Data

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 INTEGRACuBe: Exploração de dados analíticos em RDF

2021 ◽  
Author(s):  
Jones O. Avelino ◽  
Kelli F. Cordeiro ◽  
Maria C. Cavalcanti
Keyword(s):  
Data Cube ◽  
Rdf Data

O crescimento de conjuntos de dados disponíveis na Web que utilizam o padrão RDF propicia análises de dados que envolvem múltiplas dimensões. Segundo a W3C, um dos recursos para analisar dados multidimensionais é a utilização do vocabulário RDF Data Cube. Contudo ainda há uma carência de instrumentos de apoio para aplicação deste vocabulário em conjuntos de dados. Nesse sentido, este artigo propõe o INTEGRACuBe, um ambiente que utiliza um metaesquema e mecanismos semiautomatizados para apoiar o mapeamento de recursos de dados ao metamodelo RDF Data Cube. Como resultado, será possível a exploração de dados analíticos em RDF. Adicionalmente, um estudo de caso é apresentado no cenário de Gerência de Desenvolvimento de Software.

Development of a FHIR RDF Data Transformation and Validation Framework and Its Evaluation

2021 ◽  
pp. 103755
Author(s):  
Eric Prud'hommeaux ◽  
Josh Collins ◽  
David Booth ◽  
Kevin J. Peterso ◽  
Harold R. Solbrig ◽  
...  
Keyword(s):  
Data Transformation ◽  
Validation Framework ◽  
Rdf Data

scholarly journals Data Extraction, Transformation and Integration Guided by an Ontology

2010 ◽  
pp. 17-37
Author(s):  
Chantal Reynaud ◽  
Nathalie Pernelle ◽  
Marie-Christine Rousset
Keyword(s):  
Data Integration ◽  
Data Warehouse ◽  
Information Sources ◽  
Data Extraction ◽  
Data Transformation ◽  
Heterogeneous Information ◽  
Abstract Schema ◽  
Heterogeneous Information Sources ◽  
External Sources ◽  
Rdf Data

This chapter deals with integration of XML heterogeneous information sources into a data warehouse with data defined in terms of a global abstract schema or ontology. The authors present an approach supporting the acquisition of data from a set of external sources available for an application of interest including data extraction, data transformation and data integration or reconciliation. The integration middleware that the authors propose extracts data from external XML sources which are relevant according to an RDFS+ ontology, transforms returned XML data into RDF facts conformed to the ontology and reconciles RDF data in order to resolve possible redundancies.

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.

scholarly journals Semantics-Preserving RDB2RDF Data Transformation Using Hierarchical Direct Mapping

2020 ◽  
Vol 10 (20) ◽  
pp. 7070
Author(s):  
Hee-Gook Jun ◽  
Dong-Hyuk Im
Keyword(s):  
Relational Databases ◽  
Semantic Information ◽  
Data Transformation ◽  
Transformation Method ◽  
Information Loss ◽  
Mapping Method ◽  
Data Consistency ◽  
Data Generation ◽  
Direct Mapping ◽  
Rdf Data

Direct mapping is an automatic transformation method used to generate resource description framework (RDF) data from relational data. In the field of direct mapping, semantics preservation is critical to ensure that the mapping method outputs RDF data without information loss or incorrect semantic data generation. However, existing direct-mapping methods have problems that prevent semantics preservation in specific cases. For this reason, a mapping method is developed to perform a semantics-preserving transformation of relational databases (RDB) into RDF data without semantic information loss and to reduce the volume of incorrect RDF data. This research reviews cases that do not generate semantics-preserving results, and the corresponding problems into categories are arranged. This paper defines lemmas that represent the features of RDF data transformation to resolve those problems. Based on the lemmas, this work develops a hierarchical direct-mapping method to strictly abide by the definition of semantics preservation and to prevent semantic information loss, reducing the volume of incorrect RDF data generated. Experiments demonstrate the capability of the proposed method to perform semantics-preserving RDB2RDF data transformation, generating semantically accurate results. This work impacts future studies, which should involve the development of synchronization methods to achieve RDF data consistency when original RDB data are modified.

Fiscal rules: Excessive limitation or indispensable instrument of fiscal sustainability?

2016 ◽  
pp. 5-29 ◽  
Author(s):  
E. Gurvich ◽  
I. Sokolov
Keyword(s):  
Historical Data ◽  
Federal Budget ◽  
Fiscal Sustainability ◽  
Fiscal Rules ◽  
External Shocks ◽  
Base Price ◽  
Depth Analysis ◽  
Fiscal Balance ◽  
Lower Size ◽  
Budget Expenditure

In-depth analysis of international and Russia’s experiences with implementing fiscal rules is presented. Theoretical and empirical evidences are suggested in favor of retaining the present fiscal rules with some modifications aimed at ensuring: a) a relatively stable level of federal budget expenditure with guaranteed full execution of all commitments; b) countercyclical fiscal policy, based on flexibleand proper reaction to revenue changes; and c) robustness of fiscal rules to internal and external shocks. The main new features suggested include modified calculation of the oil base price, different measurement of cyclical fiscal revenues, lower size of structural fiscal balance, and thorough specification of sources for each item of the balance. The modified rules envisage increased flexibility by relaxing to a pre-set extent and for a pre-set time spending limits in response to extreme shocks. The suggested version of fiscal rules has been tested by application to historical data for 2005-2015, and macro projections for 2015-2025.

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