Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

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Start date: 2021Subject: search.filters.subject.RDF

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    RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes
    (Springer Nature (Singapore), 2026-04-01)
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    Vecovska, Marija
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    Jakubowski, Maxime
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    Hose, Katja
    Developing and testing modern RDF-based applications often requires access to RDF datasets with certain characteristics. Unfortunately, it is very difficult to publicly find domain-specific knowledge graphs that conform to a particular set of characteristics. Hence, in this paper we propose RDFGraphGen, an open-source RDF graph generator that uses characteristics provided in the form of SHACL (Shapes Constraint Language) shapes to generate synthetic RDF graphs. RDFGraphGen is domain-agnostic, with configurable graph structure, value constraints, and distributions. It also comes with a number of predefined values for popular schema.org classes and properties, for more realistic graphs. Our results show that RDFGraphGen is scalable and can generate small, medium, and large RDF graphs in any domain.
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    RDFGraphGen: A Synthetic RDF Graph Generator based on SHACL Constraints
    (2024-07-25)
    Marija Vecovska
    ;
    Milos Jovanovik
    This paper introduces RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF graphs based on SHACL constraints. The Shapes Constraint Language (SHACL) is a W3C standard which specifies ways to validate data in RDF graphs, by defining constraining shapes. However, even though the main purpose of SHACL is validation of existing RDF data, in order to solve the problem with the lack of available RDF datasets in multiple RDF-based application development processes, we envisioned and implemented a reverse role for SHACL: we use SHACL shape definitions as a starting point to generate synthetic data for an RDF graph. The generation process involves extracting the constraints from the SHACL shapes, converting the specified constraints into rules, and then generating artificial data for a predefined number of RDF entities, based on these rules. The purpose of RDFGraphGen is the generation of small, medium or large RDF knowledge graphs for the purpose of benchmarking, testing, quality control, training and other similar purposes for applications from the RDF, Linked Data and Semantic Web domain. RDFGraphGen is open-source and is available as a ready-to-use Python package.
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    Semantic Web and Data Science Integration Using Computational Books
    (Ss. Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia, 2021-05)
    Mileski, Dimitar
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    This paper presents the architecture for the development of web applications for exploring semantic knowledge graphs through parameterized interactive visualizations. The web interface and the interactive parameterized visualizations, in the form of a computational book, provide a way in which knowledge graphs can be explored. An important part of using this approach for building interactive web visualizations is that we can substitute the knowledge graph entities with other entities within the existing interactive visualizations, execute commands in a web-based environment, and get the same visualization for the new entities. With this architecture, various applications for interactive visualization of knowledge graphs can be developed, which can also stimulate the interest to explore the graph and its entities. We also present a publicly available open source use-case that is built using the concepts discussed in this paper.
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    A GeoSPARQL Compliance Benchmark
    (MDPI, 2021-07-16)
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    Homburg, Timo
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    Spasić, Mirko
    GeoSPARQL is an important standard for the geospatial linked data community, given that it defines a vocabulary for representing geospatial data in RDF, defines an extension to SPARQL for processing geospatial data, and provides support for both qualitative and quantitative spatial reasoning. However, what the community is missing is a comprehensive and objective way to measure the extent of GeoSPARQL support in GeoSPARQL-enabled RDF triplestores. To fill this gap, we developed the GeoSPARQL compliance benchmark. We propose a series of tests that check for the compliance of RDF triplestores with the GeoSPARQL standard, in order to test how many of the requirements outlined in the standard a tested system supports. This topic is of concern because the support of GeoSPARQL varies greatly between different triplestore implementations, and the extent of support is of great importance for different users. In order to showcase the benchmark and its applicability, we present a comparison of the benchmark results of several triplestores, providing an insight into their current GeoSPARQL support and the overall GeoSPARQL support in the geospatial linked data domain.