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Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in…
Nowadays, many decision support applications need to exploit data that are not only numerical or symbolic, but also multimedia, multistructure, multisource, multimodal, and/or multiversion. We term such data complex data. Managing and…
Microservices architectures have become the foundation for developing scalable and modern software systems, but they also bring significant challenges in managing heterogeneous and distributed data. The pragmatic solution is polyglot…
This paper examines how a "Distributed Heterogeneous Relational Data Warehouse" can be integrated in a Grid environment that will provide physicists with efficient access to large and small object collections drawn from databases at…
Nowadays, data-intensive applications face the problem of handling heterogeneous data with sometimes mutually exclusive use cases and soft non-functional goals such as consistency and availability. Since no single platform copes everything,…
Regional planning processes and associated redevelopment projects can be complex due to the vast amount of diverse data involved. However, all of this data shares a common geographical reference, especially in the renaturation of former…
Microservices architectures are an integral part of modern software development. Their adoption brings significant changes to database management. Instead of relying on a single database, a microservices architecture is typically composed…
Standard Federated Learning (FL) techniques are limited to clients with identical network architectures. This restricts potential use-cases like cross-platform training or inter-organizational collaboration when both data privacy and…
Modern real-time business analytic consist of heterogeneous workloads (e.g, database queries, graph processing, and machine learning). These analytic applications need programming environments that can capture all aspects of the constituent…
Data distribution across different facilities offers benefits such as enhanced resource utilization, increased resilience through replication, and improved performance by processing data near its source. However, managing such data is…
Today's international corporations such as BASF, a leading company in the crop protection industry, produce and consume more and more data that are often fragmented and accessible through Web APIs. In addition, part of the proprietary and…
In recent years, the increased need to house and process large volumes of data has prompted the need for distributed storage and querying systems. The growth of machine-readable RDF triples has prompted both industry and academia to develop…
The inherent connectivity and dependency of graph-structured data, combined with its unique topology-driven access patterns, pose fundamental challenges to conventional data replication and request routing strategies in geo-distributed…
The development of a company often entails the emergence of autonomous data sources with different structural and technological organization. This can lead to the inability of data analysis at a high level and a violation of the integrity…
Federated learning (FL) has recently gained considerable attention due to its ability to learn on decentralised data while preserving client privacy. However, it also poses additional challenges related to the heterogeneity of the…
Dynamic graph storage systems are essential for real-time applications such as social networks and recommendation, where graph data continuously evolves. However, they face significant challenges in efficiently handling concurrent read and…
Low-code application development as proposed by the OutSystems Platform enables fast mobile and desktop application development and deployment. It hinges on visual development of the interface and business logic but also on easy integration…
Hypergraphs, increasingly utilised for modelling complex and diverse relationships in modern networks, gain much attention representing intricate higher-order interactions. Among various challenges, cohesive subgraph discovery is one of the…
In this paper, we describe a multidatabase system as 4tiered Client-Server DBMS architectures. We discuss their functional components and provide an overview of their performance characteristics. The first component of this proposed system…
Organizations are often faced with the challenge of providing data management solutions for large, heterogenous datasets that may have different underlying data and programming models. For example, a medical dataset may have unstructured…