Bálint Molnár

Traditional similarity-based schema matching methods fail to resolve semantic ambiguities and conflicts in complex, domain-specific mappings due to a lack of commonsense and domain-specific knowledge. In parallel, large language models (LLMs) without sufficient background knowledge tend to hallucinate, further complicating schema matching. To overcome these limitations, we introduce KG-RAG4SM, a Knowledge Graph-based Retrieval-Augmented Generation for Schema Matching. This method integrates novel retrieval mechanisms, including LLM-based, vector-based, graph traversal-based, and hybrid techniques with advanced reranking schemes to extract the most relevant subgraphs from large external KGs. Our approach achieves superior results without requiring re-training, as evidenced by improvements of 39.79% in precision and 30.56% in F1 score over LLM-based state-of-the-art (SOTA) methods (e.g., Jellyfish-8B) on the MIMIC dataset, and enhancements of 69.20% in precision and 21.99% in F1 score over pre-trained language model (PLM)-based SOTA methods (e.g., SMAT) on the Synthea dataset. Additionally, KG-RAG4SM scales effectively across KGs from commonsense KGs to domain-specific ones, while its instruction-tuning knowledge exclusion component ensures truthful performance in end-to-end schema matching tasks despite the suboptimal relevance of KG context. Our empirical analysis and case studies from real-world scenarios show that the hallucination problem in LLMs for schema matching is well mitigated by our solution.

Enterprise platforms increasingly employ operational ontologies to connect organisational data with decision-making, business logic and executable actions. Palantir Foundry is a prominent implementation of this approach, describing its Ontology as a digital twin and operational layer of an organisation. Nevertheless, the Business or Enterprise Operating System concept remains insufficiently defined in information-systems research, particularly regarding the relationship among enterprise ontology, process semantics, eventdriven execution and formal verification. This paper develops a technology-neutral, six-layer reference architecture for ontologydriven and formally verifiable Enterprise Operating Systems. A structured analysis of public Foundry documentation maps object types, links, actions, functions, interfaces, scenarios and processmining facilities to concepts from enterprise architecture, semantic technologies, business-process management, deontic modelling and model checking. The analysis identifies Foundry's principal strength in integrating data-backed semantics with governed operational action. It also shows why action testing, scenarios and process simulation should not be treated as substitutes for exhaustive model checking. The resulting gap analysis supports a research agenda for a standards-based Business Operating System centred on immutable business events, normative transaction frames, semantic relations, derived state projections and formally verifiable process models. BOS is presented solely as future research; no proprietary implementation details or confidential data are used.

Digital assets (DAs) such as cryptocurrencies, tokenized securities, stablecoins, non-fungible tokens (NFTs), and central bank digital currencies, are transforming financial markets with new business models, investment opportunities, and transaction efficiencies. Underpinned by blockchain, distributed ledger technology, and smart contracts, digital innovations are reshaping the financial ecosystem. However, their rapid growth introduces substantial risks, including fraud, market manipulation, cybersecurity threats, and regulatory uncertainty. This position paper offers an interdisciplinary and empirically grounded analysis of the DA landscape. We define and classify major asset types, trace their evolution from speculative instruments to functional tools, and assess current adoption trends. Additional technological developments (e.g., decentralized finance and NFT expansion) are examined for their role in accelerating this transformation. We also analyze the global regulatory landscape, highlighting jurisdictional differences, classification challenges, and emerging governance frameworks. To address key risks, we derive mitigation strategies via quantitative analysis and case-based evidence. The risks include balancing innovation with investor protection through adaptive regulatory design, promoting cross-border regulatory harmonization to prevent arbitrage and fragmentation, and supporting experimentation through regulatory sandboxes and innovation hubs. By adopting a forward-looking, evidence-based, and collaborative regulatory approaches, stakeholders can harness the benefits of DAs while managing systemic risks and maintaining market integrity.

The characteristics of Food Supply Chains (FSC) make them hard to manage properly, and many efforts have been conducted to alleviate the difficulties related to their management, especially when it comes to integrating the latest Information and Communications Technologies. The Internet of Things (IoT) has shown to be very beneficial in providing a holistic and real-time vision of FSCs. Blockchain, with its decentralization and immutability, is another promising technology, that is showing a great potential in managing FSCs. A lot of research has been carried out to prove the advantages of each of these technologies on its own. However, the research investigating their adoption together is still not enough. Our paper presents a study of recent advances in the integration of IoT and Blockchain in Food Supply Chain Management (FSCM) over the past five years. We identify key research trends, analyze the benefits and limitations of IoT–blockchain integration, and highlight major challenges hindering large-scale adoption. Finally, we propose future research directions to address these challenges and improve the adoption of IoT–blockchain solutions in FSCs. This study aims to serve as a reference for researchers and practitioners seeking to understand and advance the integration of these emerging technologies in FSCM.

IT (Information Technology) support plays a major role in CPSs (cyber-physical systems). More and more IT solutions and CIS (complex information system) modules are being developed to help engineering systems to a higher level of efficiency. The different specificities of different technological environments require a very different IT approach. Increasing the efficiency of different manufacturing processes requires an appropriate architecture. The Zachman framework guidelines were applied to design a suitable framework architecture for the welding process. A literature search was conducted to explore the conditions for component matching to a complex information system, in which advanced data management and data protection are important. In order to effectively manage the standards, a dedicated module needs to be created that can be integrated into the MES-ERP (Manufacturing Execution System-Enterprise Resource Planning) architecture. The result of the study is the creation of business UML (Unified Modeling Language) and BPMN (Business Process Model and Notation) diagrams and a roadmap to start a concrete application development. The paper concludes with an example to illustrate ideas for the way forward.