Sketchy Rendering for Information Visualization.

Much attention has been focused on the provision of information graphics and visualisations inside a web browser.Currently available infovis toolkits produce graphical output by either injecting SVG nodes into the DOM orusing the JavaScript Canvas 2D API. FluidDiagrams is a prototype information visualisation framework writtenin JavaScript which uses the WebGL 3D JavaScript API for its output, falling back to Canvas 2D as necessary,via the Three.js library. Six visualisations are currently implemented: bar chart and line chart, scatter plot andparallel coordinates for multidimensional data, and cone tree and hyperbolic for hierarchies.Anecdotally, visualisations using SVG nodes in the DOM for output can become rather sluggish when displayingmore than a few dozen items. Visualisations using Canvas 2D exhibit similarly slow performance. WebGLutilises hardware acceleration where available and promises much better performance for complex visualisations,potentially in the order of many thousands of items without becoming unresponsive.A comparison of parallel coordinates visualisations with 100 records in 20 dimensions compared three implementations:FluidDiagrams (WebGL), FluidDiagrams (Canvas 2D), and D3 (using SVG nodes). They achieved62, 6, and 10 frames per second respectively. The FluidDiagrams (WebGL) implementation was able to render1,000 records in 20 dimensions at 18 frames per second, compared to 1 and 6 respectively

Event-related potential and oscillatory cortical activities of artistic methodology in information visualization design in human–computer interface

When designing visual charts, effective color coding can help users access data information faster and more accurately. Colormaps are a commonly used method for scalar data visualization，which are usually designed using algorithmic techniques. However, the effectiveness of colormaps in mapping data to colors in visualization charts is not clear at present. In order to evaluate the effectiveness of colormaps application in visualization charts, this paper takes four basic visualization charts (bar chart, pie chart, scatter chart, and line chart) as the research object, and takes task completion time and accuracy rate as the index, quantitatively analyzing the application of blue, coolwarm, viridis, and jet in visualization charts. In addition, the Likert scale method was used to understand the subjective perception of users of the color maps.The results showes that the use of different colormaps had no significant effect on the participants' response time and correctness in completing the bar chart task, and a very significant effect on the pie and scatter charts. Participants were most accurate and took the shortest time on the graphs coded with viridis. The longest time was spent on the chart coded with blue and the accuracy was lower. The results of the Likert scale assessment showed that users found blue to be the least easy to read and the least aesthetically pleasing, and jet to be the most aesthetically pleasing and easy to read.

By studying the contents, culture, characteristics, functions, information, definition and visual design methods of the visual interface of the infographic, the thinking construction of the visualization of the infographic is constructed. The visual design of infographic is to express certain culture, things, states, data and phenomena through content interpretation, visual illustration, table analysis and thinking cognition, and then highlight visual features with abstract or concrete thinking cognition and concept elaboration. The visual interface design of infographic has the advantage of visual expression for some abstract thinking such as time, culture and space, which is easier to be interpreted by the public than text and language. As an interdisciplinary subject, information graphic visual interface design reflects the diversified development of data information, science and technology, information blending and thinking evolution.KeywordsInfographicVisualizationThinkingInteractive

Data stories often seek to elicit affective feelings from viewers. However, how to design affective data stories remains under-explored. In this work, we investigate one specific design factor, animation, and present Kineticharts, an animation design scheme for creating charts that express five positive affects: joy, amusement, surprise, tenderness, and excitement. These five affects were found to be frequently communicated through animation in data stories. Regarding each affect, we designed varied kinetic motions represented by bar charts, line charts, and pie charts, resulting in 60 animated charts for the five affects. We designed Kineticharts by first conducting a need-finding study with professional practitioners from data journalism and then analyzing a corpus of affective motion graphics to identify salient kinetic patterns. We evaluated Kineticharts through two user studies. The results suggest that Kineticharts can accurately convey affects, and improve the expressiveness of data stories, as well as enhance user engagement without hindering data comprehension compared to the animation design from DataClips, an authoring tool for data videos.

When we need to represent data or qualitative structures graphically in order to show a relationship—to make a comparison or highlight a trend—we make use of charts. A chart is a graphic structure consisting of symbols, such as lines, in a line chart; bars, in a bar chart; or slices, in a pie chart. Charts serve as valid tools that can help us discern and understand the relationships underlying large quantities of data. It is easier for humans to read graphic representations, such as a chart, than raw numeric data. Nowadays, use of charts has become common practice in a wide variety of professional fields as well as in many other aspects of daily life. For this reason, charts have come to take on many forms, depending on the stucture of the data and the phenomenon that is being highlighted. For example, if you have data separated into different groups and want to represent the percentage of each, with respect to the total, you usually display these groups of data in a pie chart or a bar chart. In contrast, if you want to show the trend of a variable over time, a line chart is typically the best choice.

Chapter 1.4 - Initial assessment: Measurement errors and interrater reliability

There is a rising trend of data analysis and visualization tasks being performed on a tablet device. Apps with interactive data visualization capabilities are available for a wide variety of domains. We investigate whether users grasp how to effectively interpret and interact with visualizations. We conducted a detailed user evaluation to study the abilities of individuals with respect to analyzing data on a tablet through an interactive visualization app. Based upon the results of the user evaluation, we find that most subjects performed well at understanding and interacting with simple visualizations, specifically tables and line charts. A majority of the subjects struggled with identifying interactive widgets, recognizing interactive widgets with overloaded functionality, and understanding visualizations which do not display data for sorted attributes. Based on our study, we identify guidelines for designers and developers of mobile data visualization apps that include recommendations for effective data representation and interaction.

Chapter 2 - Information Visualization: Scope, Techniques and Opportunities for Geovisualization

The rapidly expanding application of visualization technology has the potential to fundamentally change the way companies conduct business in the oil and gas industry. This technology is already having a significant impact on efficiency, accuracy, completeness and integration in exploration and development. The last three years have seen the growing acceptance of large collaborative and semiimmersive visualization systems in the upstream portion of the oil and gas industry. As this technology matures, and as it is applied broadly to both the upstream and downstream business, it will produce tremendous value through the reduction of cycle times and risk. Large display systems, including large flat screens, curved screen Visionaria and fully immersive CAVEs, hold the potential to revolutionize the way business is conducted. Experience using these large systems suggests that the cost of the visualization system is recovered after only a few months of operation. Once useful applications are available, the utilization of the system rapidly expands to fill all of the available time. Without head tracking (tracking the viewer's position and updating the display appropriately), these large systems facilitate the integration of data, and the integration and collaboration between members of interdisciplinary teams. Systems that incorporate head tracking hold the potential to produce significantly greater value by allowing display and interaction to occur in a truly three-dimensional fashion. An example of this type of system and application is an immersive drilling planner. It integrates all of the geophysical and geological information in the 3-D tracked visual display, and incorporates the algorithms and input data necessary to generate engineered drillable well paths. Introduction Visualization technology has been used for years in oil and gas exploration and development. Visualization is simply the graphical presentation of data in an intuitive fashion to reveal information. A bar chart, line graph, seismic section or reservoir map are all visualizations of data. Over the last five to ten years, the technology of visualization has advanced more and more rapidly, with improving resolution, interactivity and display size. Visualization on smaller desktop display systems has tended to focus on discipline or "domain" specific applications (e.g. 3-D visualization applications used for 3-D seismic interpretation). These applications have demonstrated value through improving the accuracy, completeness and, to some extent, the efficiency of interpretation and reservoir modeling. However, These domain specific applications provide only limited integration between disciplines and little opportunity for collaboration between domain experts in front of the small screen. These limitations arise from the combination of the domain specific nature of the software itself (seismic interpretation software, log analysis software, geologic modeling software, etc.), and the limitations of the desktop display as a viewing medium. A desktop display is typically limited to 1280×1024 pixels (picture elements) on a 21-inch monitor. Although resolutions can be higher on more expensive systems, and displays can be a few inches larger, desktop displays are fundamentally limited in the amount of data that can be displayed, and in the number of people who can view the data simultaneously.

With the rapid development of big data technology, information technology and visualization technology, traditional national headdress design has gradually been combined with it. The strategies and applications related to national headdress design also fully reflect the beauty of modern science and technology, which is a model of the combination of national classics and modern technology. Based on this, this paper will deeply analyze the various links and processes of the design based on the data based on the specific information of Yao ethnic headwear. At the same time, based on the existing visual design, this paper will take spring, hibernate and other systems as the basic software architecture of the design system and deeply study the visualization principles and data information visualization methods of spring, hibernate and other software, and carry out data information visualization processing on the relevant design of national headwear, to build the corresponding digital material library with national characteristics and the digital design process of national headwear. Through the digital processing and matching of the whole design, the current design of national headwear can be simplified and optimized, and the design efficiency can be improved to provide reference samples for the design of other national characteristics. In the specific design part, this paper will carry out design verification based on Yao nationality's corresponding characteristic headdress design and evaluate the corresponding design from the perspective of artistry, practicality and nationality of headdress design. The practice results show that the information visualization design of national headwear proposed in this paper has obvious advantages over the traditional design, which greatly improves the design efficiency and simplifies the design process.

From Stories—via Arguments, Scenarios, and Cases—to Probabilities: Commentary on Floris J. Bex's “The Hybrid Theory of Stories and Arguments Applied to the Simonshaven Case” and Bart Verheij's “Analyzing the Simonshaven Case With and Without Probabilities”

With the rapid development of digital media technology, digital media context emerges as the times require. Visual communication design also presents language features, aesthetic features and communication features, which have a great impact on visual communication design to a certain extent. However, based on the analysis of the actual situation, visual communication design is still in the situation of challenges and opportunities. Based on this, this paper studies the multiple characteristics of visual communication design in digital media environment. This paper expounds the main characteristics of visual communication design, and analyzes the changes of visual communication design performance in the digital media era. It also discusses the influence of digital media era on visual communication design from three dimensions: changing the form of information dissemination, promoting the development of multidimensional design and realizing virtual design. Finally, the paper compares the visual communication design based on digital media environment with the traditional visual communication design method, aiming to provide reference for the digital development of visual communication design. Research shows that visual communication design can reflect the characteristics of digital media era, break through the limitations of time and space, and bring more aesthetic experience to people. It is worth noting that on the basis of the visual impact brought by digital media technology, it is necessary to alleviate the contradiction between the progress of the times and the development of visual communication design.

Visualisation techniques have been one of the best data processing and analysis methods in recent decades, and they have assisted in data understanding efforts in various fields. Visualisation techniques for low-dimensional data are well developed and applied in multiple sectors; however, multidimensional data visualisation techniques still present some limitations, such as inaccurate data comparison and perception, exaggerated visual differences, label occlusion, and overlap. This study addresses the pros and cons and proposes a novel graphical drawing method, the multidimensional rose chart. It adopts the design idea of the Nightingale rose chart, but overcomes relevant limitations. The main challenges of this area include the incomplete presentation of multidimensional data, the neglect of the linkage of multiple attributes, the inefficient use of space, and the lack of simplicity of the interface. Contributions include enriching the representations of multidimensional data through the use of colour shades, area, and height sizes to represent values; straightforward data attribute comparisons via graph nesting; and detailed attributes showing the use of specific value labels. To verify the preliminary validity of this method, we imported COVID-19 data into experiments and further compared the final layouts with traditional methods, such as the line chart, bar chart, tree, parallel coordinate chart, and Nightingale rose chart, as well as their structures, functionalities, clear advantages, and disadvantages. The experimental results show that multidimensional rose diagrams perform effectively in presenting multidimensional data when comparing other graph drawing methods in our case, and the outcomes match existing works' conclusions in related COVID-19 research sectors. This work has the potential to provide a suitable supplemental approach to the multidimensional data analysis.

Rainfall data is essential for applications such as climate monitoring, agricultural planning, flood forecasting, and water resource management. However, the interpretation of this data is often hindered by its high volume, variability, and multi-scale temporal nature. Effective visualization is critical not only for summarizing complex datasets but also for uncovering patterns, detecting anomalies, and facilitating informed decision-making. Despite the availability of numerous visualization techniques, selecting the most suitable method for rainfall data, especially across varying temporal resolutions is a challenging task. This study presents a comparative analysis of widely used data visualization techniques in the context of rainfall data. The methodology was structured into three phases: understanding the nature of rainfall data, reviewing relevant visualization techniques, and conducting a comparative content analysis. A SWOT (Strengths, Weaknesses, Opportunities, and Threats) evaluation was used to assess each technique’s analytical potential, while a temporal suitability comparison was performed across five time granularities: yearly, monthly, weekly, daily, and hourly. Findings show that no single technique is universally effective. Instead, each method demonstrates specific strengths and limitations depending on the temporal scale and analytical objective. Line charts and bar charts are well-suited for lower-frequency data, while heat maps and scatter plots are more effective for high-resolution, time-sensitive patterns. Box plots and histograms provide valuable insights into data distribution and variability, whereas map-based visualizations excel in spatial analysis but require enhancements for temporal exploration. The study concludes that visualization effectiveness depends on aligning method selection with data characteristics and analytical goals. A thoughtful combination of techniques is often necessary to achieve clarity, reduce misinterpretation, and enhance decision support in rainfall data analysis.