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.

Browse

Settings

Author: search.filters.author.Spasić, Mirko

Search Results

Now showing 1 - 8 of 8
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    An RDF Dataset Generator for the Social Network Benchmark with Real-World Coherence
    (2016-10)
    Jovanovik, Milos
    ;
    Spasić, Mirko
    ;
    Prat-Pérez, Arnau
    Synthetic datasets used in benchmarking need to mimic all characteristics of real-world datasets, in order to provide realistic benchmarking results. Synthetic RDF datasets usually show a ignificant discrepancy in the level of structuredness compared to real-world RDF datasets. This structural difference is important as it directly affects storage, indexing and querying. In this paper, we show that the synthetic RDF dataset used in the Social Network Benchmark is characterized with high-structuredness and therefore introduce modifications to the data generator so that it produces an RDF dataset with a real-worldstructuredness.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    MOCHA 2017 as a Challenge for Virtuoso
    (Springer International Publishing, 2017-10)
    Spasić, Mirko
    ;
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    MOCHA2017: The Mighty Storage Challenge at ESWC 2017
    (Springer International Publishing, 2017-10)
    Georgala, Kleanthi
    ;
    Spasić, Mirko
    ;
    ;
    Petzka, Henning
    ;
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Benchmarking Virtuoso 8 at the Mighty Storage Challenge 2018: Challenge Results
    (Springer International Publishing, 2018-10)
    ;
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    MOCHA2018: The Mighty Storage Challenge at ESWC 2018
    (Springer International Publishing, 2018-10)
    Georgala, Kleanthi
    ;
    Spasić, Mirko
    ;
    ;
    Papakonstantinou, Vassilis
    ;
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A GeoSPARQL Compliance Benchmark
    (MDPI, 2021-07-16)
    ;
    Homburg, Timo
    ;
    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.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Software for the GeoSPARQL Compliance Benchmark
    (Elsevier, 2021-05)
    ;
    Homburg, Timo
    ;
    Spasić, Mirko
    Checking the compliance of geospatial triplestores with the GeoSPARQL standard represents a crucial step for many users when selecting the appropriate storage solution. This publication presents the software which comprises the GeoSPARQL compliance benchmark — a benchmark which checks RDF triplestores for compliance with the requirements of the GeoSPARQL standard. Users can execute this benchmark within the HOBBIT benchmarking platform to quantify the extent to which the GeoSPARQL standard is implemented within the triplestore of interest. This enables users to make an informed decision when choosing an RDF storage solution and helps assess the general state of adoption of geospatial technologies on the Semantic Web.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Transforming Geospatial RDF Data into GeoSPARQL-Compliant Data: A Case of Traffic Data
    (Ss. Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia, 2019-05)
    ;
    Spasić, Mirko
    Geospatial RDF datasets have a tendency to use latitude and longitude properties to denote the geographic location of the entities described within them. On the other hand, geographic information systems prefer the use of WKT and GML geometries when working with geospatial data. In this paper, we present a process of RDF data transformation which produces a GeoSPARQL-compliant dataset, using an RDF geospatial dataset with traffic data as a starting point. The traffic is comprised of vehicle traces, which consist of numerous points with specific latitude and longitude values. With our transformations, we enable querying of the dataset with GeoSPARQL extensions, which can be used to feed a GIS solution.