University and college laboratories are important places to train professional and technical personnel. Various regulatory departments in colleges and universities still rely on traditional laboratory management in research projects, which are prone...
The growing importance of data as a driver of the digital economy is promoting the creation of data spaces for the secure and controlled exchange of data between organizations. Data governance is emerging as an essential pillar to ensure efficient, e...
This paper addresses the research gap in the realm of data-driven transformation by leveraging the Resource-Based View (RBV) theory and the dynamic capabilities concept to the contours of a data-driven enterprise. It confronts the limitations of conv...
Big Data platforms are expected to unify data engineering, governance and machine learning in one environment, and the data lakehouse has become the dominant architectural answer. Empirical evaluations on real operational data remain scarce, and thos...
ActoDatA (Actor Data Analysis) is an actor-based software library for the development of distributed data mining applications. It provides a multi-agent architecture with a set of predefined and configurable agents performing the typical tasks of dat...
Driven by technological innovation, service diversification, and the evolution and defects of current networks, the 6th-generation (6G) network architecture is lacking in research. One of the challenges in this research is that the architectural desi...
The unceasingly increasing needs for data acquisition, storage and analysis in transportation systems have led to the adoption of new technologies and methods in order to provide efficient and reliable solutions. Both highways and vehicles, nowadays,...
Effective and efficient data management is crucial for smart farming and precision agriculture. To realize operational efficiency, full automation, and high productivity in agricultural systems, different kinds of data are collected from operational...
The architecture design of industrial data analytics system addresses industrial process challenges and the design phase of the industrial Big Data management drivers that consider the novel paradigm in integrating Big Data technologies into industri...
Today, everything is connected, including the exchange of data and the generation of new information. As a result, large amounts of data are being collected at an ever-increasing rate and in a variety of forms, a phenomenon now known as Big Data. Rec...
The building sector is undergoing a deep transformation to contribute to meeting the climate neutrality goals set by policymakers worldwide. This process entails the transition towards smart energy-aware buildings that have lower consumptions and bet...
This paper describes the architecture of a cross-sectorial Big Data platform for the process industry domain. The main objective was to design a scalable analytical platform that will support the collection, storage and processing of data from multip...
28 September 2020
Organizations are attempting to harness the power of big data analytics. Enterprise architecture can be used as an instrument to integrate big data analytics into the existing IT landscape and enabling the development of capabilities to create value...
Data sharing within and across large, complex systems is one of the most topical challenges in the current IT landscape, and the energy domain is no exception. As the sector becomes more and more digitized, decentralized, and complex, new Big Data an...
This paper deals with the mediator–wrapper architecture and observes it in more modern aspects by relating it to architectural quanta. It is an important architectural pattern that enables a more flexible and modular architecture in opposition...
Very often, the root of problems found to produce food sustainably, as well as the origin of many environmental issues, derive from making decisions with unreliable or inexistent data. Data-driven agriculture has emerged as a way to palliate the lack...
This paper describes a novel architecture that aims to create a template for the implementation of an IT platform, supporting the deployment and integration of the different digital twin subsystems that compose a complex urban intelligence system. In...
Highly populated cities depend highly on intelligent transportation systems (ITSs) for reliable and efficient resource utilization and traffic management. Current transportation systems struggle to meet different stakeholder expectations while trying...
Integrating third-party and legacy systems has become a critical necessity for companies, driven by the need to exchange information with various entities such as banks, suppliers, customers, and partners. Ensuring data integrity, keeping integration...
This study develops and implements a scalable system architecture for dynamic data acquisition and knowledge modeling in industrial contexts. The objective is to efficiently process large datasets to support decision-making and process optimization w...
Rapid and accurate identification of maize architecture characteristics is important for understanding both yield potential and crop breeding experiments. Most canopy architecture indicators cannot fully reflect the vertical leaf distribution in fiel...
We study big-data hybrid-data-processing lambda architecture, which consolidates low-latency real-time frameworks with high-throughput Hadoop-batch frameworks over a massively distributed setup. In particular, real-time and batch-processing engines a...
Genomics-based diagnostic data (GBDD) are becoming increasingly important for laboratory diagnostics. Due to the large quantity of data and their heterogeneity, GBDD poses a big data challenge. Current analysis tools for GBDD are primarily designed f...
The heterogeneity of the formats and standards of clinical data, which includes both structured, semi-structured, and unstructured data, in addition to the sensitive information contained in them, require the definition of specific approaches that ar...
Implementing smart microgrids for Non-Interconnected Zones (NIZs) has become an alternative solution to provide electrical energy by taking advantage of the resources available through the generation of renewable energy within these isolated areas. W...
Cryptocurrencies have recently emerged as financial assets that allow their users to execute transactions in a decentralized manner. Their popularity has led to the generation of huge amounts of data, specifically on social media networks such as Twi...
Although the defense field is also one of the key areas that use big data for security reasons, there is a lack of study that designs system frameworks and presents security requirements to implement big data in defense. However, we overcome the secu...
Modern embedded systems are vulnerable to complex data-oriented attacks that subvert not only existing control-flow integrity protections but also have dire implications on safety-critical applications. To overcome this challenge, this work proposes...
This paper presents Nexus, a proof-of-concept low-cost, modular, and reprogrammable multichannel data logger aimed at validating the architectural feasibility of an open and scalable acquisition platform for scientific instrumentation. The system was...
This paper proposes the Architecture-Aware Real Options Framework (AA-ROF), a systems-based model for valuing research data in multi-tier socio-technical infrastructures (Institutional Archive, Federated Mesh, AI Sandbox). AA-ROF treats architecture...
The high volume of information produced by project management and its quality have become a challenge for organizations. Due to this, emerging technologies such as big data, data science and artificial intelligence (ETs) have become an alternative in...
Artificial intelligence (AI) approaches continue to spread in almost every research and technology branch. However, a simple adaptation of AI methods and algorithms successfully exploited in one area to another field may face unexpected problems. Acc...
The increasing complexity of data ecosystems demands advanced methodologies for systematic privacy risk assessment. This work introduces two complementary metrics—the privacy risk expansion factor (PREF) and the privacy exposure index (PEI)&mda...
Time-interleaved high-speed data acquisition (HS-DAQ) systems based on three-dimensional network-on-chip (3D NoC) architectures require efficient transmission of multi-channel sampled data. However, existing general-purpose NoC architectures are not...
In recent years, technological advances and the ever-increasing power of embedded systems have seen the emergence of so-called smart cities. In these cities, application needs are increasingly calling for Large-Scale Wireless Sensor Networks (LS-WSN)...
This study introduces a novel methodology designed to assess the accuracy of data processing in the Lambda Architecture (LA), an advanced big-data framework qualified for processing streaming (data in motion) and batch (data at rest) data. Distinct f...
The growth of big data ecosystems has shifted the classical paradigm of selective storage toward an approach that preserves large volumes of heterogeneous data for subsequent exploitation, thereby strengthening the adoption of repositories such as da...
Modern organizations increasingly rely on heterogeneous database environments that combine relational, document-oriented, and key-value storage systems to optimize performance for diverse application requirements. However, this technological diversit...
AI assistants are increasingly integrated into digital financial services; however, relying on generative language models for response generation can introduce challenges related to response reliability, data exposure, and resource requirements. This...
Detecting anomalies in data streams from smart communication environments is a challenging problem that can benefit from novel learning techniques. The Attention Mechanism is a very promising architecture for addressing this problem. It allows the mo...
The use of mobile nodes to collect data in a Wireless Sensor Network (WSN) has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs) as mobile node for such data-collection purposes. Analyzi...
The development of smart cities provides a vital foundation for the intelligent advancement of landscape architecture and engineering technologies, where multimodal spatio-temporal data visualization plays a key role. This study conducts a scoping re...
Personalized federated learning (PFL) faces significant challenges in resource-constrained edge environments, where strict communication budgets and severe system heterogeneity must be jointly addressed. Although one-shot federated learning reduces c...
The increasing complexity of healthcare data ecosystems demands educational technologies capable of supporting data-intensive learning through advanced analytics, immersive interfaces, and learning analytics. This paper presents a cloud-based referen...
Microgrids are considered a viable solution for achieving net-zero targets and increasing renewable energy integration. However, there is a lack of conceptual work focusing on practical data analytics deployment schemes and case-specific insights. Th...
Advances in artificial intelligence (AI), particularly agentic AI, have created opportunities to enhance global sustainability by improving the efficiency and accuracy of environmental monitoring and response systems. Agentic AIs autonomously plan an...
The deployment of large language models (LLMs) in real-world applications introduces a compounding security problem: detecting adversarial inputs such as prompt injection and jailbreak-driven data leakage while simultaneously preventing the detection...
The prediction of partial discharges in hydrogenerators depends on data collected by sensors and prediction models based on artificial intelligence. However, forecasting models are trained with a set of historical data that is not automatically updat...
The evolution of automation has reached marine operations in general and offshore operations in particular. Many facilities in these areas use the Internet of Things (IoT) to consolidate processes and improve data release systems. In addition, the IE...
Efficient and low-cost modes for detecting metro track geometry defects (TGDs) are essential for condition-prediction-based preventive maintenance, which can help improve the safety of metro operations and reduce the maintenance cost of metro tracks....
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