thesis

Enrichment of data in relational database with Linked Data resources

Abstract

The goal of the master's thesis is to introduce a method that will define how to link relational schemas with the existing structured data sources on the Semantic Web. Our study is based on different methods of data integration, where we will focus on the technologies of the Semantic Web (RDF, RDF scheme, R2RML and OWL). More precisely, we developed a method that enables integration of data from a relational database (schema and instances) with existing structured data in RDF format - so called Linked Data (LOD) sources. The result of the master's thesis are therefore approach and method which determines the method of implementation of distributed queries; enrichment of schema and data from any relational database. The solution also enables us to produce and publish information in accordance with the recommendations published by Tim Berners-Lee in 2010 (five-star Linked Data format). The second part of master's thesis presents a prototype in the form of a tool. With this tool we have verified and evaluated method from the first part. There are variety of open source solutions that enable matching and enrichment of data, but such approaches work only with semantically less rich information (e.g. XML and CSV format). Our prototype is actually a complement and enhancement of LogMap tool - we named it LogMapFRI. It allows user to work with relational databases, which implicitly contain useful metadata. These metadata can be used to identify the context of the data in the database and thus relieve the user from integrating schemas manually. Being able to do just that and extension of syntactic approaches are in fact key improvements of LogMap and main contribution of our solution

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