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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    MOCHA 2017 as a Challenge for Virtuoso
    (Springer International Publishing, 2017-10)
    Spasić, Mirko
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    The Mighty Storage Challenge (MOCHA) aims to test the performance of solutions for SPARQL processing, in several aspects relevant for modern Linked Data applications. Virtuoso, by OpenLink Software, is a modern enterprise-grade solution for data access, integration, and relational database management, which provides a scalable RDF Quad Store. In this paper, we present a short overview of Virtuoso with a focus on RDF triple storage and SPARQL query execution. Furthermore, we showcase the final results of the MOCHA 2017 challenge and its tasks, along with a comparison between the performance of our system and the other participating systems.
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    MOCHA2017: The Mighty Storage Challenge at ESWC 2017
    (Springer International Publishing, 2017-10)
    Georgala, Kleanthi
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    Spasić, Mirko
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    Petzka, Henning
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    Röder, Michael
    The aim of the Mighty Storage Challenge (MOCHA) at ESWC 2017 was to test the performance of solutions for SPARQL processing in aspects that are relevant for modern applications. These include ingesting data, answering queries on large datasets and serving as backend for applications driven by Linked Data. The challenge tested the systems against data derived from real applications and with realistic loads. An emphasis was put on dealing with data in form of streams or updates.
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    Benchmarking Virtuoso 8 at the Mighty Storage Challenge 2018: Challenge Results
    (Springer International Publishing, 2018-10)
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    Spasić, Mirko
    Following the success of Virtuoso at last year’s Mighty Storage Challenge - MOCHA 2017, we decided to participate once again and test the latest Virtuoso version against the new tasks which comprise the MOCHA 2018 challenge. The aim of the challenge is to test the performance of solutions for SPARQL processing in aspects relevant for modern applications: ingesting data, answering queries on large datasets and serving as backend for applications driven by Linked Data. The challenge tests the systems against data derived from real applications and with realistic loads, with an emphasis on dealing with changing data in the form of streams or updates. Virtuoso, by OpenLink Software, is a modern enterprise-grade solution for data access, integration, and relational database management, which provides a scalable RDF Quad Store. In this paper, we present the final challenge results from MOCHA 2018 for Virtuoso v8.0, compared to the other participating systems. Based on these results, Virtuoso v8.0 was declared as the overall winner of MOCHA 2018.
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    MOCHA2018: The Mighty Storage Challenge at ESWC 2018
    (Springer International Publishing, 2018-10)
    Georgala, Kleanthi
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    Spasić, Mirko
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    Papakonstantinou, Vassilis
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    Stadler, Claus
    The aim of the Mighty Storage Challenge (MOCHA) at ESWC 2018 was to test the performance of solutions for SPARQL processing in aspects that are relevant for modern applications. These include ingesting data, answering queries on large datasets and serving as backend for applications driven by Linked Data. The challenge tested the systems against data derived from real applications and with realistic loads. An emphasis was put on dealing with data in form of streams or updates.
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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.