Industry 4.0 produces large volumes of sensor and machine data, offering new possibilities for manufacturing analytics but also creating challenges in combining domain knowledge with visual analysis. We present a systematic review of 13 peer-reviewed...
The increasing use of electronic health record (EHR)-based systems has led to the generation of clinical data at an unprecedented rate, which produces an untapped resource for healthcare experts to improve the quality of care. Despite the growing dem...
Visual analytics combines computational analysis with interactive visual representations and may strengthen pharmacovigilance, but its use in drug safety research has not been systematically characterized. This scoping review mapped the extent, chara...
12 September 2017
Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which o...
Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results c...
28 April 2010
Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the...
As the levels of automation and reliance on modern artificial intelligence (AI) approaches increase across multiple industries, the importance of the human-centered perspective becomes more evident. Various actors in such industrial applications, inc...
In some of the domain-specific sectors, such as the climate domain, the provision of publicly available present-day high-resolution meteorological time series is often quite limited or completely lacking. This repeatedly leads to excessive deployment...
The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of...
The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D visualization techniques, in the environmental domain is unparalleled. Such advanced systems may enable an in-depth interactive exploration of multifaceted...
With the increasing number of studies, where participants' eye movements are tracked while watching videos, the volume of gaze data records is growing tremendously. Unfortunately, in most cases, such data are collected in separate files in custom-mad...
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sens...
With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis appro...
Manufacturing is critical to the global economy and is a key sector of businesses in today’s world. The pressures of manufacturing mean that companies are often fighting to survive instead of investing in new technologies and factories in order...
Through social media platforms, massive amounts of data are being produced. As a microblogging social media platform, Twitter enables its users to post short updates as “tweets” on an unprecedented scale. Once analyzed using machine learn...
This research studies the occurrence of data breaches in healthcare provider settings regarding patient data. Using visual analytics and data visualization tools, we study the distribution of healthcare breaches by state. We review the main causes an...
The use of data analysis techniques in electronic health records (EHRs) offers great promise in improving predictive risk modeling. Although useful, these analysis techniques often suffer from a lack of interpretability and transparency, especially w...
In the process of multivariate network exploration and analysis, it is important to consider network topology and attribute correlation analysis. In order to consider both in presentation and analysis, existing research focuses on visual design and m...
Employees of different critical infrastructures, including energy systems, are considered to be a security resource, and understanding their behavior patterns may leverage user and entity behavior analytics and improve organization capabilities in in...
Problem solving applications require users to exercise caution in their data usage practices. Prior to installing these applications, users are encouraged to read and comprehend the terms of service, which address important aspects such as data priva...
In the field of visualization, understanding users’ analytical reasoning is important for evaluating the effectiveness of visualization applications. Several studies have been conducted to capture and analyze user interactions to comprehend thi...
Amongst the data mining techniques for exploratory analysis, association rule mining is a popular strategy given its ability to find causal rules between items to express regularities in a database. With large datasets, many rules can be generated, a...
Readily available software analysis and analytics tools are often operated within external services, where the measured software analysis data are kept internally and no external access to the data is available. We propose an approach to integrate vi...
Online debates, specifically the ones about public health issues (e.g., vaccines, medications, and nutrition), occur frequently and intensely, and are having an impact on our world. Many public health topics are debated online, one of which is the ef...
Laboratory tests play an essential role in the early and accurate diagnosis of diseases. In this paper, we propose SUNRISE, a visual analytics system that allows the user to interactively explore the relationships between laboratory test results and...
We investigate the design of ontology-supported, progressively disclosed visual analytics interfaces for searching and triaging large document sets. The goal is to distill a set of criteria that can help guide the design of such systems. We begin wit...
As precipitation analysis reveals critical statistical characteristics, temporal patterns, and spatial distributions of rainfall and snowfall events, it plays an important role in planning urban drainage systems, flood forecasting, hydrological model...
In cancer biology, genomics represents a big data problem that needs accurate visual data processing and analytics. The human genome is very complex with thousands of genes that contain the information about the individual patients and the biological...
Cloud providers such as Amazon Web Services (AWS) stand out as useful platforms to teach distributed computing concepts as well as the development of Cloud-native scalable application architectures on real-world infrastructures. Instructors can benef...
The importance of high-resolution meteorological time-series data for detection of transformative changes in the climate system is unparalleled. These data sequences allow for a comprehensive study of natural and forced evolution of warming and cooli...
Visual Analytics (VA) is a multidisciplinary field that requires various skills including but not limited to data analytics, visualizations, and the corresponding domain knowledge. Recently, many studies proposed creating and using Domain-Specific La...
Graphs are often used to model data with a relational structure and graphs are usually visualised into node-link diagrams for a better understanding of the underlying data. Node-link diagrams represent not only data entries in a graph, but also the r...
With the recent increase in the use of sea transportation, the importance of maritime surveillance for detecting unusual vessel behavior related to several illegal activities has also risen. Unfortunately, the data collected by surveillance systems a...
Analyzing trajectory data plays an important role in practical applications, and clustering is one of the most widely used techniques for this task. The clustering approach based on information bottleneck (IB) principle has shown its effectiveness fo...
Recent advancement in EHR-based (Electronic Health Record) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional data available in EHRs creates great opportunities for machine learning techniques...
Wastewater treatment plant (WWTP) operations manage massive amounts of data that can be gathered with new Industry 4.0 technologies such as the Internet of Things and Big Data. These data are critical to allow the wastewater treatment industry to imp...
Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is stil...
Scoping review is an iterative knowledge synthesis methodology concerned with broad questions about the nature of a research subject. The increasingly large number of published documents in scholarly domains poses challenges in conducting scoping rev...
1 August 2009
The increasing demand for hospital emergency services has important implications for the allocation of limited public resources and the management of healthcare services. Although reform is an oft-cited way to improve the healthcare system, it has a...
This paper presents a web-based visual analytics framework for robust multi-objective aircraft wing design. Aerodynamic and structural simulation data are generated for a redesigned CRM wing, with aspect ratio and skin root thickness as key variables...
The professional development of experienced teachers has received considerably less attention than that of novice teachers. This study focuses on four experienced secondary mathematics teachers in Shanghai, China, with two participating in a year-lon...
The widespread adoption of cyber-physical systems and other cutting-edge digital technology in manufacturing industry production facilities may motivate stakeholders to embrace the idea of Industry 4.0. Some industrial companies already have differen...
In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—serve...
The non-transparency of artificial intelligence (AI) systems, particularly in deep learning (DL), poses significant challenges to their comprehensibility and trustworthiness. This study aims to enhance the explainability of DL models through visual a...
The paper presents a comprehensive deep learning-based framework for automated visual inspection of overhead power line infrastructure using unmanned aerial vehicles. Traditional manual and helicopter inspections are costly, time-consuming, and hazar...
Extreme weather events are expected to increase in frequency and intensity due to global warming. During disaster events, up-to-date relevant information is crucial for early detection and response. Recently, Twitter emerged as a potentially importan...
Power-equipment fault detection is challenging in real-world inspections due to subtle defect cues and cluttered backgrounds. This paper proposes an improved YOLOv12-based framework for multi-class power defect detection. We introduce a Prior-Guided...
Multimorbidity is a growing healthcare problem, especially for aging populations. Traditional single disease-centric approaches are not suitable for multimorbidity, and a holistic framework is required for health research and for enhancing patient ca...
This paper presents a dashboard-oriented visual analytics workflow for classification-related exploratory analysis based on Information Gain (IG), histogram segmentation, and complementary localized interpretation through the Precise Piecewise Correl...
Non-destructive examination (NDE) in the field of materials engineering is a technique based on acoustics and optical principles used for detecting and evaluating internal defects in materials without causing any damage. The majority of current resea...
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