Towards Normalized Systems from RDF with SPARQL
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00359952" target="_blank" >RIV/68407700:21240/22:00359952 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.3233/FAIA220290" target="_blank" >https://doi.org/10.3233/FAIA220290</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/FAIA220290" target="_blank" >10.3233/FAIA220290</a>
Alternative languages
Result language
angličtina
Original language name
Towards Normalized Systems from RDF with SPARQL
Original language description
Normalized Systems are a model-driven development technique focusing on evolvability and sustainability of resulting enterprise information systems. It applies well-defined principles to create a fine-grained modular structure while limiting combinatorial effects. The systems are generated (or, more precisely, expanded) from models of so-called NS Elements. NS has its own modelling language; however, interoperability with other knowledge representations is necessary. This work presents our solution for transforming knowledge kept in one of the most generic forms – RDF semantic triples – to NS Elements. The transformation enables mapping using RDFS/OWL ontologies describing both the input RDF. It utilizes SPARQL for executing the transformation to RDF based on the existing NS Element ontology. The presented transformation is demonstrated on an example case study, and its features and limitations are discussed together with potential future steps.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
New Trends in Intelligent Software Methodologies, Tools and Techniques
ISBN
978-1-64368-316-4
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
609-620
Publisher name
IOS Press
Place of publication
Amsterdam
Event location
Kitakyushu
Event date
Sep 20, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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