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Obogatitev podatkov v relacijski podatkovni bazi z Linked Data slovarji
Balija, Damir (Author), Lavbič, Dejan (Mentor) More about this mentor... This link opens in a new window

URLURL - Presentation file, Visit http://eprints.fri.uni-lj.si/3012/ This link opens in a new window

Abstract
Namen magistrske naloge je opredeliti metodo, ki bo omogočala povezavo obstoječe relacijske sheme in strukturiranih podatkov semantičnega spleta. Temeljili bomo na različnih načinih integracije podatkov, kjer se bomo osredotočili predvsem na tehnologije semantičnega spleta (RDF, RDF shema, R2RML in OWL). V okviru magistrskega dela smo razvili metodo, ki omogoča povezovanje podatkov iz relacijske podatkovne baze (sheme in primerkov) z obstoječimi strukturiranimi podatki v RDF formatu oz. Linked Data viri (LOD). Rezultat magistrske naloge sta pristop in metoda, ki z obogatitvijo shem in podatkov poljubne relacijske podatkovne baze omogočata izvedbo porazdeljenih poizvedb. Rešitev nam prav tako omogoča pripravo in objavo podatkov v skladu s priporočili za objavo odprtih podatkov na svetovnem spletu (pet-zvezdna Linked Data oblika). V okviru praktične implementacije smo razvili prototip v obliki orodja, s katerim smo razvito metodo verificirali in evalvirali. Obstajajo različne odprtokodne rešitve, ki omogočajo usklajevanje in bogatenje podatkov, vendar tovrstni pristopi delujejo zgolj s semantično manj bogatimi podatki (npr. XML in CSV oblika). Naš prototip, LogMapFRI, predstavlja dopolnitev in izboljšavo orodja LogMap. Omogoča delo z relacijskimi podatkovnimi bazami in uporablja metapodatke iz teh baz za ugotavljanje konteksta, s čimer uporabnika razbremenimo ročnega povezovanja shem. Prav bolj natančen zajem metapodatkov in razširitev sintaktičnih pristopov sta se izkazali kot ključni izboljšavi našega pristopa.

Language:Unknown
Keywords:bogatenje podatkov, ontologije, usklajevanje ontologij, semantični splet, RDB2RDF, morfološka normalizacija nizov, shema relacijske podatkovne baze kot usmerjen graf, iskanje v širino, klasifikacija pristopov pri usklajevanju ontologij, Linked Data viri
Work type:Not categorized (r6)
Organization:FRI - Faculty of computer and information science
Year:2015
COBISS.SI-ID:1536467907 Link is opened in a new window
Views:484
Downloads:169
Metadata:XML RDF-CHPDL DC-XML DC-RDF
 
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Secondary language

Language:Unknown
Title: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.

Keywords:data enrichment, ontologies, ontology matching, semantic web, RDB2RDF, R2RML, morphological string normalization, relational database schema as directed graph, Breadth-first search, classification of ontology matching techniques, Linked Open Data

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