1. Type-based computation of knowledge graph statisticsIztok Savnik, Kiyoshi Nitta, Riste Škrekovski, Nikolaus Augsten, 2025, izvirni znanstveni članek Opis: We propose a formal model of a knowledge graph (abbr. KG) that classifies the ground triples into sets that correspond to the triple types. The triple types are partially ordered by the sub-type relation. Consequently, the sets of ground triples that are the interpretations of triple types are partially ordered by the subsumption relation. The types of triple patterns restrict the sets of ground triples, which need to be addressed in the evaluation of triple patterns, to the interpretation of the types of triple patterns. Therefore, a schema graph of a KG should include all triple types that are likely to be determined as the types of triple patterns. The stored schema graph consists of the selected triple types that are stored in a KG and the complete schema graph includes all valid triple types of KG. We propose choosing the schema graph, which consists of the triple types from a strip around the stored schema graph, i.e., the triple types from the stored schema graph and some adjacent levels of triple types with respect to the sub-type relation. Given a selected schema graph, the statistics are updated for each ground triple t from a KG. First, we determine the set of triple types stt from the schema graph that are affected by adding a triple t to an RDF store. Finally, the statistics of triple types from the set stt are updated.
Ključne besede: knowledge graphs, RDF stores, graph database systems
Objavljeno v RUP: 16.01.2026; Ogledov: 52; Prenosov: 2
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3. Enhancing crisis response efficiency through ICT : a Delphi study on operational and decision-making improvements in mass casualty incidentsPrimož Režek, Boštjan Žvanut, 2025, izvirni znanstveni članek Opis: The potential of information and communication technology (ICT) to improve coordination and decision-making during the training and operational phases of mass casualty incidents (MCIs) has not yet been sufficiently explored. This three-round Delphi study investigates whether ICT use in MCIs can enhance decision-making and increase victim survival rates. The study was conducted from 10 February to 20 September 2024, with 25 international experts from academia, clinical practice, and health informatics. The results were summarised using a SWOT analysis, confirming ICT's perceived potential in MCI management. The analysis revealed a critical asymmetry: while the strengths and opportunities were mainly associated with technical factors (e.g. the effectiveness of drones, global positioning systems, artificial intelligence, dashboards, and virtual and augmented reality to improve the cost-effectiveness of training), weaknesses and threats were mainly social and organisational. These included a lack of standardisation and interoperability, limited ICT-supported training, infrastructure and cybersecurity gaps, resistance to change, legal constraints, underfunding, low technological readiness, and scepticism about the cost-effectiveness of ICT in real-world MCI contexts. Our findings highlight the gap between technological readiness and implementation challenges, suggesting that ICT innovation alone is insufficient without supportive governance, infrastructure, and stakeholder engagement. As the first Delphi study of its kind, it provides a strategic foundation for evidence-based ICT integration in training and operational MCI responses. The findings provide clear priorities for future policy development and empirical validation, emphasising the need to address persistent non-technical barriers to realise ICT’s full potential in crisis management.
Ključne besede: mass casualty incidents (MCI), information and communication technology (ICT), artificial intelligence (AI), drones, electronic triage systems, delphi study, SWOT analysis
Objavljeno v RUP: 08.09.2025; Ogledov: 523; Prenosov: 7
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