Information Visualization Techniques Research Articles

Análise de rede sociais de autores e instituições participantes nos anais do WIDAT 2017 a 2023 por coautoria e palavras-chave

The Information, Data and Technology Workshop (WIDaT), with its six editions from 2017 to 2023, published 210 articles in the proceedings with the participation of 395 authors linked to 80 institutions based in 46 cities and 7 countries. The objective of the research is to reveal affinity groups between authors and institutions participating in WIDaT. Qualitative research of an applied nature, used information visualization techniques with the support of social network analysis methods supported by software, such as: OpenRefine, Gephi and Looker Studio. The main result was the analysis of social networks of authors and institutions participating in the six events. The network of authors by co-authorship showed a giant component composed of the majority of authors, while the network of authors by keywords amplified the density of connections, making it a 'small world'. The network of co-authorship institutions revealed strong collaboration between institutions. The network of institutions using keywords identified seven clusters, complemented by keyword clouds, which revealed a semantic cohesion of the topics covered by the institutions belonging to each cluster. Observing the most common keywords for a given cluster can motivate approaches to research collaboration, both for those already consolidated and to strengthen the development of new investigations and studies.

The Evolutionary Path and Emerging Trends of Circulating Fluidized Bed Technology: An Integrated Analysis through Bibliometric Assessment and Data Visualization

Confronted with the significant challenges of global climate change and environmental deterioration, the pursuit of carbon emission peaks and the realization of carbon neutrality have become a collective goal for countries worldwide. As an exemplary combustion technology noted for its efficiency and environmental friendliness, the circulating fluidized bed (CFB) is instrumental in curbing the release of carbon dioxide alongside other deleterious gases. The technology is pivotal in promoting the clean and efficient use of coal, simultaneously expediting the global shift towards a sustainable, green, and low-carbon future. This study employs a bibliometric analysis, a social network analysis, and information visualization techniques to delve into the evolution of CFB technology, leveraging the Web of Science database (SCI-EXPANDED and CPCI-S) and the Derwent Innovations Index (DII). Through a meticulous examination of academic papers and patent literature related to CFB technology, this research unveils the developmental trajectory and trends of CFB technology, providing a scientific foundation and reference for strategic technology planning and focused research in key areas. The findings indicate that, while there is a downward trend in the global publication of academic papers on CFB technology, the number of patent applications continues to grow steadily. CFB technology has achieved significant advancements in enhancing combustion efficiency, environmental protection, energy utilization, and waste management, and is progressing towards a direction of diversification and greater efficiency. Moving forward, the development of CFB technology should concentrate on pivotal areas such as material science, fluid dynamics simulation, environmental impact assessment, system integration, and intelligentization, to foster ongoing innovation and a broad application of the technology.

SingDistVis: interactive Overview+Detail visualization for F0 trajectories of numerous singers singing the same song

AbstractThis paper describes SingDistVis, an information visualization technique for fundamental frequency (F0) trajectories of large-scale singing data where numerous singers sing the same song. SingDistVis allows to explore F0 trajectories interactively by combining two views: OverallView and DetailedView. OverallView visualizes a distribution of the F0 trajectories of the song in a time-frequency heatmap. When a user specifies an interesting part, DetailedView zooms in on the specified part and visualizes singing assessment (rating) results. Here, it displays high-rated singings in red and low-rated singings in blue. When the user clicks on a particular singing, the audio source is played and its F0 trajectory through the song is displayed in OverallView. We selected heatmap-based visualization for OverallView to provide an overview of a large-scale F0 dataset, and polyline-based visualization for DetailedView to provide a more precise representation of a small number of particular F0 trajectories. This paper introduces a subjective experiment using 1,000 singing voices to determine suitable visualization parameters. Then, this paper presents user evaluations where we asked participants to compare visualization results of four types of Overview+Detail designs and concluded that the presented design archived better evaluations than other designs in all the seven questions. Finally, this paper describes a user experiment in which eight participants compare SingDistVis with a baseline implementation in exploring interested singing voices and concludes that the proposed SingDistVis archived better evaluations in nine of the questions.

Information Visualization on the Reading Comprehension for Elementary School Students in Malaysia

Visualization strategies are strategies that utilize images to help strengthen the students' understanding of reading comprehension. Through this strategy, students will describe the meaning obtained from the text in the form of rough sketches. The use of these images allows the students to be more focused on the continuation of reading because they understand the meaning more clearly. This study aims to investigate the impact of information visualization techniques on reading comprehension performance among elementary school students in Malaysia. The study adapted quantitative study through a quasi-experimental design and survey questionnaire. 300 students from Standard 4 to Standard 6 (10 to 12 years old) were chosen as the participants of the study. They were divided into Experimental Group (n=150) and the control Group (n=150). The experiment has been done in 2 classes per week, in a total of 6 weeks. The participants in the Experimental Group were taught reading comprehension using visualization technique, while the students in the Control Group were taught using conventional method. The reading comprehension score for all the students were recorded both in pre-test and post-test. After the experiment, the students in Experimental Group were asked to answer a set of questionnaires. The finding shows that the student in the Experimental Group has higher increment in terms of their reading comprehension score compared to the students in the Control Group after the experiment. Statistical analysis of Pearson correlation found a very weak significant positive correlation between visualization technique and reading comprehension score (r=0.188, p<0.005). The analysis of Multiple Linear regression also shows that visualization technique has a small effect only on the reading comprehension score (R2=.275, R2Adj=.233, p<0.001). It was also found that there is a significant difference on the information visualization technique on the reading comprehension score based on gender. The study concludes that there are other factors that affect the students’ level of reading comprehension such as the students’ cognitive ability, and the environment of study, in which visualization technique is only a fraction in improving the reading comprehension.

An extended taxonomy of advanced information visualization and interaction in conceptual modeling

Conceptual modeling is integral to computer science research and is widely adopted in industrial practices, e.g., business process and enterprise architecture management. Providing adequate and usable modeling tools is necessary to adopt modeling languages efficiently. Meta-modeling platforms provide a rich and mature set of functionalities for realizing state-of-the-art modeling tools. These tools, albeit their stability and rich set of features, often lack a modern look and feel considering (i) how they visualize the models, and (ii) how modelers interact with the models. Current web technologies enable much richer, advanced opportunities for visualizing and interacting with conceptual models. However, a structured and comprehensive overview of possible information visualization and interaction techniques linked to conceptual models and modeling tools must be established. This paper aims to fill this gap by presenting an extended taxonomy of advanced information visualization and interaction in conceptual modeling. We present a generic taxonomy that is afterward contextualized within the specific domain of conceptual modeling. The taxonomy serves orientation in the vast developing field of information visualization and interaction and hopefully sparks innovation if future modeling tool development.

Enhancing OPAC through Geospatial Data: Stackmaps and Text Visualization in Koha

Physical stacks in academic libraries, despite the advent of digital repositories, remain important to users, especially in countries like India where physical resources hold considerable value. This study seeks to develop a system that enables users to locate books physically by integrating stackmaps functionalities with Koha OPAC. In addition, the study showcases how an open-source text analytics server can be incorporated inside an OPAC in Koha to generate various word-level visualizations by analyzing a text corpus, including the identification of geospatial features such as place names. This research aims to contribute to the advancement of information retrieval and visualization techniques in OPACs in academic libraries, and to improve the user experience in locating physical resources. (The video abstract of this paper may be found at: https://youtu.be/q940TUkcTTE ).

The popularisation of self-care: Tracing the dissemination of Orem's Self-Care Deficiency Nursing Theory into the scientific disciplines.

Bibliometric methods may be used to examine research trends, and information visualisation techniques are useful in illustrating the diffusion of knowledge and how theories are applied. The present study aimed to illustrate how Orem's Self-Care Deficiency Nursing Theory (SCDNT) has been cited and applied in nursing science and beyond. A bibliometric analysis examined scientific publications that cited Orem's nursing theory. In addition, the diffusion of SCDNT was assessed using data visualisation methods and integration scores of SCDNT versions were calculated to define trends in its theoretical usage in other scientific domains. The information visualisation demonstrated increased usage of SCDTN in different disciplines. Integration scores demonstrated that the scientific community still recognises and uses versions of SCDTN. Studying citation patterns helps to identify which publications are still cited and relevant, as well as illustrating the dissemination of theory. Findings may be used in the collection weeding of SCDTN book versions. Findings provided nursing scientists with a better conceptual understanding of SCDNT diffusion and development. For academic library managers, the findings identify which SCDNT should be retained for historical interest and curriculum needs.

Visualization of information in public management using open data of the Municipal Guard of Curitiba

This article presents Information Visualization techniques applied to open data referring to the activations of the Municipal Guard of the city of Curitiba, Paraná, Brazil. It is descriptive research where the chosen database and its visualizations are presented. The analyzed period was from January 2009 to March 2022. Microsoft Excel software was used for data processing and Microsoft Power BI software was used for developing the dashboards. The objective was to use the data to create visualizations capable of instigating improvements in public security policies. Some dashboards were generated and grouped by subjects including, for instance, occurrences of domestic violence. As a result, it was possible to generate information to support decision-making and improve security policies.

Information Visualisation for Antibiotic Detection Biochip Design and Testing

Biochips are engineered substrates that have different spots that change colour according to biochemical reactions. These spots can be read together to detect different analytes (such as different types of antibiotic, pathogens, or biological agents). While some chips are designed so that each spot on its own can detect a particular analyte, chip designs that use a combination of spots to detect different analytes can be more efficient and detect a larger number of analytes with a smaller number of spots. These types of chip can, however, be more difficult to design, as an efficient and effective combination of biosensors needs to be selected for the chip. These need to be able to differentiate between a range of different analytes so the values can be combined in a way that demonstrates the confidence that a particular analyte is present or not. The study described in this paper examines the potential for information visualisation to support the process of designing and reading biochips by developing and evaluating applications that allow biologists to analyse the results of experiments aimed at detecting candidate bio-sensors (to be used as biochip spots) and examining how biosensors can combine to identify different analytes. Our results demonstrate the potential of information visualisation and machine learning techniques to improve the design of biochips.

HyperCube4x: A viewport management system proposal

This article presents a novel management and information visualization system proposal based on the tesseract, the 4D-hypercube. The concept comprises metaphors that mimic the tesseract geometrical properties using interaction and information visualization techniques, made possible by modern computer systems and human capabilities such as spatial cognition. The discussion compares the Hypercube and the traditional desktop metaphor systems. An operational prototype is also available for reader testing. Finally, a preliminary assessment with 31 participants revealed that 81.05% “agree” or “totally agree” that the proposed concepts offer real gains compared to the desktop metaphor.

Using Chained Views and Follow-Up Queries to Assist the Visual Exploration of the Web of Big Linked Data

The Web of Linked Open Data (LOD) provides access to a great number of dynamic datasets containing valuable information to support decision-making processes in diverse application domains while being publicly accessible and up-to-date. While information visualization techniques are useful to explore, analyze, and explain relationships within LOD data, the existing tools are limited to visualizing a single dataset at a time and, often, use static and preprocessed data. In this article, we leverage the linked aspect of LOD to support the dynamic integration of data into a visualization system by connecting views and distributed LOD datasets using the so-called follow-up queries. We demonstrate how our approach uses dynamic SPARQL queries to integrate external data into the exploration flow through visualization techniques and enrich the ongoing analysis. We ran a semi-structured interview to assess the usefulness of our approach, which results were encouraging while showing its relevance to explore big linked data.

Exploring Environmental and Geographical Factors Influencing the Spread of Infectious Diseases with Interactive Maps

Environmental problems due to human activities such as deforestation, urbanisation, and large scale intensive farming are some of the major factors behind the rapid spread of many infectious diseases. This in turn poses significant challenges not only in as regards providing adequate healthcare, but also in supporting healthcare workers, medical researchers, policy makers, and others involved in managing infectious diseases. These challenges include surveillance, tracking of infections, communication of public health knowledge and promotion of behavioural change. Behind these challenges lies a complex set of factors which include not only biomedical and population health determinants but also environmental, climatic, geographic, and socioeconomic variables. While there is broad agreement that these factors are best understood when considered in conjunction, aggregating and presenting diverse information sources requires effective information systems, software tools, and data visualisation. In this article, we argue that interactive maps, which couple geographical information systems and advanced information visualisation techniques, provide a suitable unifying framework for coordinating these tasks. Therefore, we examine how interactive maps can support spatial epidemiological visualisation and modelling involving distributed and dynamic data sources and incorporating temporal aspects of disease spread. Combining spatial and temporal aspects can be crucial in such applications. We discuss these issues in the context of support for disease surveillance in remote regions, utilising tools that facilitate distributed data collection and enable multidisciplinary collaboration, while also providing support for simulation and data analysis. We show that interactive maps deployed on a combination of mobile devices and large screens can provide effective means for collection, sharing, and analysis of health data.

Electrochemical Immunosensor Made with Zein‐based Nanofibers for On‐site Detection of Aflatoxin B1

AbstractA disposable electrochemical immunosensor for on‐site detection of aflatoxin B1(AFB1), one of the most toxic mycotoxins in agri‐food products, was fabricated through a low‐cost cut‐printing method and then modified with zein/polypyrrole(PPy) electrospun nanofibers onto which anti‐AFB1 monoclonal antibodies were immobilized covalently. Fabrication was possible with an innovative and simple approach to adsorb nanofibers onto the working electrode during electrospinning. Electrochemical impedance spectroscopy was employed as the principle of detection, and the data collected with a portable potentiostat were treated with information visualization techniques. The nanostructured immunosensor showed a high sensitivity for AFB1 with a linear detection range from 0.25 to 10 ng mL−1 and a theoretical limit of detection of 0.092 ng mL−1, which is adequate to detect AFB1 in food, according to regulatory agencies.

Music information visualization and classical composers discovery: an application of network graphs, multidimensional scaling, and support vector machines

This article illustrates different information visualization techniques applied to a database of classical composers and visualizes both the macrocosm of the Common Practice Period and the microcosms of twentieth century classical music. It uses data on personal (composer-to-composer) musical influences to generate and analyze network graphs. Data on style influences and composers ‘ecological’ data are then combined to composer-to-composer musical influences to build a similarity/distance matrix, and a multidimensional scaling analysis is used to locate the relative position of composers on a map while preserving the pairwise distances. Finally, a support-vector machines algorithm is used to generate classification maps. This article falls into the realm of an experiment in music education, not musicology. The ultimate objective is to explore parts of the classical music heritage and stimulate interest in discovering composers. In an age offering either inculcation through lists of prescribed composers and compositions to explore, or music recommendation algorithms that automatically propose works to listen to next, the analysis illustrates an alternative path that might promote the active rather than passive discovery of composers and their music in a less restrictive way than inculcation through prescription.

Big Data Analytics and Visualization in Traffic Monitoring

This paper presents a system that employs information visualization techniques to analyze urban traffic data and the impact of traffic emissions on urban air quality. Effective visualizations allow citizens and public authorities to identify trends, detect congested road sections at specific times, and perform monitoring and maintenance of traffic sensors. Since road transport is a major source of air pollution, also the impact of traffic on air quality has emerged as a new issue that traffic visualizations should address. Trafair Traffic Dashboard exploits traffic sensor data and traffic flow simulations to create an interactive layout focused on investigating the evolution of traffic in the urban area over time and space. The dashboard is the last step of a complex data framework that starts from the ingestion of traffic sensor observations, anomaly detection, traffic modeling, and also air quality impact analysis. We present the results of applying our proposed framework on two cities (Modena, in Italy, and Santiago de Compostela, in Spain) demonstrating the potential of the dashboard in identifying trends, seasonal events, abnormal behaviors, and understanding how urban vehicle fleet affects air quality. We believe that the framework provides a powerful environment that may guide the public decision-makers through effective analysis of traffic trends devoted to reducing traffic issues and mitigating the polluting effect of transportation.

Information technology for creating intelligent computer programs for training in algorithmic tasks. Part 1: Mathematical foundations

The existing education system (in particular higher education) due to its focus on basic knowledge is quite inert and cannot satisfy the needs of the modern labor market, which is rapidly developing. Some professions transform or disappear, while the others appear almost every day. Today the employers need specialists with certain skills and abilities, who are able to develop them and adapt to specific projects. That is why short-term courses are very popular today, especially online and with a mentor — a specialist in a particular field. At the same time, graduates of such courses are mostly unable to solve complex problems and make competent decisions on their own. There is a requirement of creation of training programs for testing the development and implementation of tools for productive knowledge and skills transferring in a particular field. The article shows a possible approach to provide some interactivity to computer tutoring tools in addition to the game principle, information visualization and other techniques that have already proven themselves in information systems. It will give an opportunity to create a platform that can accumulate new technologies, integrating them into a digital tutoring environment that can be adapted to each student.

Visualisation of Perception of Experiential Activities in Business and Administration and Economy

This paper explores how to incorporate information visualization tools into qualitative studies to represent the underlying structure of knowledge. Information visualization plays a key role in many areas such as decision-making, data mining, market studies, or knowledge management. A case of experiential learning was developed for Quantitative Techniques in Business and Administration and Economy Degrees at the University of Granada, Spain. The goal is to analyze the opinion of students (n = 227) on the development of the activity through information visualization techniques. The gathered information was subjected to a categorization process to unify and homogenize the responses. After a term-clumping process, a co-word analysis using the VosViewer software is used to analyze the relationships among terms and provide the network maps. Results display the main associations and clusters of terms used when assessing the experiential activity, using qualitative techniques. In conclusion, the strengths of data visualization enabling a better understanding of data for qualitative studies are established.
 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities

The capture, modelling and visualisation of uncertainty has become a hot topic in many areas of science, such as the digital humanities (DH). Fuelled by critical voices among the DH community, DH scholars are becoming more aware of the intrinsic advantages that incorporating the notion of uncertainty into their workflows may bring. Additionally, the increasing availability of ubiquitous, web-based technologies has given rise to many collaborative tools that aim to support DH scholars in performing remote work alongside distant peers from other parts of the world. In this context, this paper describes two user studies seeking to evaluate a taxonomy of textual uncertainty aimed at enabling remote collaborations on digital humanities (DH) research objects in a digital medium. Our study focuses on the task of free annotation of uncertainty in texts in two different scenarios, seeking to establish the requirements of the underlying data and uncertainty models that would be needed to implement a hypothetical collaborative annotation system (CAS) that uses information visualisation and visual analytics techniques to leverage the cognitive effort implied by these tasks. To identify user needs and other requirements, we held two user-driven design experiences with DH experts and lay users, focusing on the annotation of uncertainty in historical recipes and literary texts. The lessons learned from these experiments are gathered in a series of insights and observations on how these different user groups collaborated to adapt an uncertainty taxonomy to solve the proposed exercises. Furthermore, we extract a series of recommendations and future lines of work that we share with the community in an attempt to establish a common agenda of DH research that focuses on collaboration around the idea of uncertainty.

Roadmap for Electrical Impedance Spectroscopy for Sensing: A Tutorial

Electrical impedance spectroscopy has been used extensively for sensing and biosensing due to the multiple electrical properties that can be interrogated through varying the frequency of the electrical excitation. In this paper, we review the basic concepts and key issues for applying impedance spectroscopy in sensing and biosensing, with emphasis on the development of precise, low-cost and portable instruments. An impedance spectroscopy system can be divided into three parts: the signal processing unit, the sensing unit and the data analysis unit. Herein, we focus on the signal processing unit, responsible for generating the excitation signal and performing the impedance readout. Special attention is given to small and low-cost signal processing circuits, which are essential for portability and point-of-care diagnosis. We also elaborate upon the various methods to fabricate the sensing units, including the choice of nanomaterials and biomolecules in controlled molecular architectures. From an instrumentation perspective, we discuss possible sources of interference in the measurement protocols. When impedance spectroscopy measurements are performed with arrays of sensing units, as with electronic tongues, large amounts of data are generated. This has motivated an increasing use of statistical and computational methods for data analysis. We present some of these methods, with examples of information visualization and machine learning techniques, which have been employed in analyzing impedance spectroscopy data in recent years.

Changes in the Structures and Directions of Rock Excavation Research from 1999 to 2020: A Bibliometric Study

Rock excavation has been the hot spot and frontier of scientific research. Rock excavation research is in a period of rapid development. The bibliographies included in ISI Web of Knowledge database from 1999–2020 were used as data samples, and the collected data were analyzed by literature co-citation and cluster analysis using CiteSpace and VOSviewer information visualization techniques and dynamic network analysis tools. A knowledge map of the evolution of bibliometric research development is drawn to reveal the representative literature in the field of bibliometrics. The hot areas of bibliometric research are introduced. The development trend of bibliometrics is proposed. The results of the study show that the amount of the literature on rock excavation is growing rapidly. A large amount of the foreign literature is available in China, the United States, Australia, Canada, France, and other countries. The main included journals are Tunnelling and Underground Space Technology, International Journal of Rock Mechanics and Mining Sciences, “Rock Mechanics and Rock Engineering,” “Engineering Geology,” and “Bulletin of Engineering Geology and the Environment.” Keyword co-occurrence analysis includes the following contents: rock damage constitutive model, excavation damage area, numerical simulation, stability analysis support, and prediction technology of rock.