Data Integration at Scale: From Relational Data Integration to Information Ecosystems

2010 ◽  
Author(s):  
Michael L. Brodie
Keyword(s):  
Data Integration ◽  
Relational Data

Research on Ontology-Based Relational Data Integration

2011 ◽  
pp. 329-336
Author(s):  
Zhuang Miao ◽  
Jingwu Wang ◽  
Jinpeng Wang ◽  
Yang Li ◽  
Weiguang Xu
Keyword(s):  
Data Integration ◽  
Relational Data

SHRDIS: A Semantic-Based Heterogeneous Relational Data Integration System

2010 ◽  
Vol 121-122 ◽  
pp. 335-340
Author(s):  
Jin Peng Wang ◽  
Ya Fei Zhang ◽  
Jian Jiang Lu ◽  
Zhuang Miao
Keyword(s):  
Data Integration ◽  
Relational Databases ◽  
Research Field ◽  
Relational Data ◽  
New Paradigm ◽  
Integration System ◽  
Global Schema ◽  
Database Research ◽  
Data Integration System ◽  
Data Source

Integrating and querying data from heterogeneous sources is a hot research topic in database research field. The emergence of the Semantic Web brings new paradigm shift of computing in data integration research where data is heterogeneous and distributed. To solve the problem this paper proposes a semantic-based approach. A Semantic-based Heterogeneous Relational Data Integration System, called SHRDIS, is presented. In this system, ontology is used as the mediated schema for the representation of the data source semantics. SPARQL queries over global schema are rewritten into local SQL queries that can be executed on heterogeneous relational databases. The architecture and implementation of SHRDIS is illustrated in detail. The experiment results show that the SHRDIS system has nice performance and scalability.

Heterogeneous Embeddings for Relational Data Integration Tasks

2021 ◽  
pp. 680-692
Author(s):  
Xuehui Li ◽  
Guangqi Wang ◽  
Derong Shen ◽  
Tiezheng Nie ◽  
Yue Kou
Keyword(s):  
Data Integration ◽  
Relational Data

scholarly journals Mapping of the descriptive logic into RDF using binary relational data model

2021 ◽  
pp. 056-083
Author(s):  
I.S. Chystiakova ◽  
Keyword(s):  
Data Integration ◽  
Data Model ◽  
Mapping Method ◽  
Relational Data ◽  
Practical Implementation ◽  
Theoretical Level ◽  
Conceptual Information ◽  
Relational Data Model ◽  
Integration Problem ◽  
Conversion Tool

This paper is dedicated to the data integration problem. To establish relationships between data models is one of the key tasks in this solution. The descriptive logic and the relational data model are at the heart of a study. They have been used to create a mapping method on the theoretical level. The binary relational data model has been developed as a part of a mapping method. The previous studies are continued in this paper to prove on practice a mapping creation method between the descriptive logic and the binary relational data model. The method uses the binary relational data model as an integrating model. This paper continues the previous research of practical implementation of the mapping creation between the descriptive logic and the binary relational data model. The task to prove the theoretical mapping method on practice was formulated. A question how to map the binary relational data model into RDF-triples was considered. A brief overview of the R2R ML conversion tool was given. Triple maps were created to convert a conceptual information model of descriptive logic into RDF triplets with the help of R2R ML. Also, triples maps are described to convert basic mapping mechanisms into RDF with the help of R2R ML.

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