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In current Open Banking services, the European Payment Services Directive (PSD2) allows the secure collection of bank customer information, on their behalf and with their consent, to analyze their financial status and needs. The PSD2 directive has lead to a massive number of daily transactions between Fintech entities which require the automatic management of the data involved, generally coming from multiple and heterogeneous sources and formats. In this context, one of the main challenges lies in defining and implementing common data integration schemes to easily merge them into knowledge-base repositories, hence allowing data reconciliation and sophisticated analysis. In this sense, Semantic Web technologies constitute a suitable framework for the semantic integration of data that makes linking with external sources possible and enhances systematic querying. With this motivation, an ontology approach is proposed in this work to operate as a semantic data mediator in real-world open banking operations. According to semantic reconciliation mechanisms, the underpinning knowledge graph is populated with data involved in PSD2 open banking transactions, which are aligned with information from invoices. A series of semantic rules is defined in this work to show how the financial solvency classification of client entities and transaction concept suggestions can be inferred from the proposed semantic model. [ABSTRACT FROM AUTHOR]

Nowadays, the increasing demand of water for electricity production, agricultural and industrial uses are directly affecting the reduction of available quality water for human consumption in the world. Efficient and sustainable maintenance of water reservoirs and supply networks implies a holistic strategy that takes into account, as much as possible, information from the stages of water usage. Next,-generation decision-making software tools, for supporting water management, require the integration of multiple and heterogeneous data sources of different knowledge domains. In this regard, Linked Data and Semantic Web technologies enable harmonization of different data sources, as well as the efficient querying for feeding upper-level Business Intelligence processes. This work investigates the design, implementation and usage of a semantic approach driven by ontology to capture, store, integrate and exploit real-world data concerning water supply networks management. As a main contribution, the proposal helps with obtaining semantically enriched linked data, enhancing the analysis of water network performance. For validation purposes, in the use case, a series of data sources from different measures have been considered, in the scope of an actual water management system of the Mediterranean region of Valencia (Spain), throughout several years of activity. The obtained experience shows the benefits of using the proposed approach to identify possible correlations between the measures such as the supplied water, the water leaks or the population. [ABSTRACT FROM AUTHOR]