Relevant bibliographies by topics / Visualization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Visualization'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 November 2024

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Journal articles on the topic "Visualization"

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Byrne, Lydia, Daniel Angus, and Janet Wiles. "Figurative frames: A critical vocabulary for images in information visualization." Information Visualization 18, no. 1 (August 29, 2017): 45–67. http://dx.doi.org/10.1177/1473871617724212.

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Critical analyses provide information visualization practitioners with insight into the range and suitability of different techniques for visualization. Theory provides the necessary models and vocabulary to deconstruct, explain and classify visualizations, allowing the analysis and comparison of alternate designs, and evaluation of their success. While the critical vocabulary for information visualization in general is well developed, the same cannot be said for ‘hybrid’ information visualizations which combine abstract representation of data with figurative elements such as illustrations. Figurative elements are widely used in information visualization in practice and are increasingly recognized as beneficial for memorability. However, the information encoded by a figurative image and how that information contributes to the overall content of the visualization lacks robust definition within visualization theory. To support critical analysis of hybrid visualization, we provide a model of the information content of a figurative image, which we call the figurative frame model. We use the model to classify hybrid visualizations along two dimensions: information density in the images (defined as the number of features and preserved measurements) and integration of figurative and abstract forms of representation. The new vocabulary for analysing hybrid visualizations reveals how the figurative images expand the expressiveness of information visualization by integrating descriptive and abstract information and allows the formulation of new measures of visualization quality which can be applied to hybrid visualizations.
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Kjellin, Andreas, Lars Winkler Pettersson, Stefan Seipel, and Mats Lind. "Different Levels of 3D: An Evaluation of Visualized Discrete Spatiotemporal Data in Space-Time Cubes." Information Visualization 9, no. 2 (June 11, 2009): 152–64. http://dx.doi.org/10.1057/ivs.2009.8.

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New technologies and techniques allow novel kinds of visualizations and different types of 3D visualizations are constantly developed. We propose a categorization of 3D visualizations and, based on this categorization, evaluate two versions of a space-time cube that show discrete spatiotemporal data. The two visualization techniques used are a head-tracked stereoscopic visualization (‘strong 3D’) and a static monocular visualization (‘weak 3D’). In terms of effectiveness and efficiency the weak 3D visualization is as good as the strong 3D and thus the need for advanced 3D visualizations in these kinds of tasks may not be necessary.
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North, Chris, Nathan Conklin, Kiran Indukuri, and Varun Saini. "Visualization Schemas and a Web-Based Architecture for Custom Multiple-View Visualization of Multiple-Table Databases." Information Visualization 1, no. 3-4 (December 2002): 211–28. http://dx.doi.org/10.1057/palgrave.ivs.9500020.

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Relational databases provide significant flexibility to organize, store, and manipulate an infinite variety of complex data collections. This flexibility is enabled by the concept of relational data Schemas, which allow data owners to easily design custom databases according to their unique needs. However, user interfaces and information visualizations for accessing and utilizing databases have not kept pace with this level of flexibility. Visualizations need to integrate multiple tables and diverse visualization tools into custom solutions. This paper describes advances to Snap-Together Visualization, introduces Visualization Schemas, and presents an extensible system architecture. The Snap model for custom multiple-view visualization establishes an analogy to the relational data model, enabling coordinated data design and visualization design. Visualization Schemas are a natural extension to data Schemas, and provide a user interface that enables data owners to rapidly construct and disseminate custom visualizations without programming. The web-based software architecture supports run-time extensibility, enabling end-user integration and dissemination of diverse data and visualization tools from the field.
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Gaikwad, Sushmita, Vaishnavi Ajmire, Komal Patil, and Vaishali Khandave. "Graph Algorithm Visualizer." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (December 23, 2023): 1–3. http://dx.doi.org/10.55041/ijsrem27719.

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A comprehensive study on algorithm visualization reveals insights into content distribution, creator demographics, and visualization quality. The associated wiki catalogues over 350 algorithm visualizations and includes an annotated bibliology on algorithm visualization literature. Unfortunately, the majority of visualizations are deemed low-quality, with a bias towards simpler topics. The report proposes the development of an e-learning tool focusing on specific visualizations like Pathfinder, Prime Numbers, Sorting Algorithms, N Queen, Convex Hull, and Binary Search Game. The absence of effective repositories for algorithm visualizations is recognized as a significant gap. Emphasizing the need for improved dissemination, the report suggests initiatives to inform developers about existing gaps and requirements within the field. It also underscores the importance of propagating established best practices for creating high-quality visualizations. In conclusion, the report highlights the urgency of addressing these deficiencies to cultivate a more robust and accessible ecosystem for algorithm visualization resources. Despite the challenges, there is a clear call to action to enhance the standard of algorithm visualizations and foster a more inclusive and informed community. Key Words: Algorithm, Visualization, Pathfinder, Sorting, Search Game.
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Song, Jihye, Olivia B. Newton, Stephen M. Fiore, Corey Pittman, and Joseph J. LaViola. "Examining Training Comprehension and External Cognition in Evaluations of Uncertainty Visualizations to Support Decision Making." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 1654–58. http://dx.doi.org/10.1177/1071181319631520.

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Recent advances in uncertainty visualization research have focused not only on design features to support decision making, but also on challenges of evaluating the effectiveness of uncertainty visualizations, such as the degree to which individuals’ baseline task comprehension may alter their performance on experimental tasks regardless of a visualization’s effectiveness. Building on recent work, we investigated the effect of training comprehension on performance across varying representations of uncertainty and varying degrees of visualization interactivity using a simulated course of action selection task. Additionally, we explored how extended cognition theory can be applied to visualization evaluations by incorporating interface features that afford externalization of knowledge within the task environment. Our findings suggest that regardless of how uncertainty is represented, training comprehension leads to superior transfer, reduced workload, more accurate metacognitive judgments, and higher cognitive efficiency. Our findings also suggest that external cognition during decision making leads to improved accuracy and cognitive efficiency. The present study contributes to research on the design and evaluation of uncertainty visualizations. In addition, this study extends previous work by demonstrating how extended cognition theory can inform the design of human-machine interfaces to support decision making.
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Avazpour, Iman, John Grundy, and Hai L. Vu. "Generating Reusable Visual Notations Using Model Transformation." International Journal of Software Engineering and Knowledge Engineering 25, no. 02 (March 2015): 277–305. http://dx.doi.org/10.1142/s0218194015400100.

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Visual notations are a key aspect of visual languages. They provide a direct mapping between the intended information and set of graphical symbols. Visual notations are most often implemented using the low level syntax of programming languages which is time consuming, error prone, difficult to maintain and hardly human-centric. In this paper we describe an alternative approach to generating visual notations using by-example model transformations. In our new approach, a semantic mapping between model and view is implemented using model transformations. The notations resulting from this approach can be reused by mapping varieties of input data to their model and can be composed into different visualizations. Our approach is implemented in the CONVErT framework and has been applied to many visualization examples. Three case studies for visualizing statistical charts, visualization of traffic data, and reuse of a Minard's map visualization's components, are presented in this paper. A detailed user study of our approach for reusing notations and generating visualizations has been provided. 80% of the participants in this user study agreed that the novel approach to visualization was easy and 87% stated that they quickly learned to use the tool support.
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Kullman, Kaur, and Don Engel. "Interactive Stereoscopically Perceivable Multidimensional Data Visualizations for Cybersecurity." Journal of Defence & Security Technologies 4, no. 1 (January 2022): 37–52. http://dx.doi.org/10.46713/jdst.004.03.

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Interactive Data Visualizations (IDV) can be useful for cybersecurity subject matter experts (CSMEs) while they are exploring new data or investigating familiar datasets for anomalies, correlating events, etc. For an IDV to be useful to a CSME, interaction with that visualization should be simple and intuitive (free of additional mental tasks) and the visualization’s layout must map to a CSME's understanding. While CSMEs may learn to interpret visualizations created by others, they should be encouraged to visualize their datasets in ways that best reflect their own ways of thinking. Developing their own visual schemes makes optimal use of both the data analysis tools and human visual cognition. In this article, we focus on a currently available interactive stereoscopically perceivable multidimensional data visualization solution, as such tools could provide CSMEs with better perception of their data compared to interpreting IDV on flat media (whether visualized as 2D or 3D structures).
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Grammel, L., M. Tory, and M. Storey. "How Information Visualization Novices Construct Visualizations." IEEE Transactions on Visualization and Computer Graphics 16, no. 6 (November 2010): 943–52. http://dx.doi.org/10.1109/tvcg.2010.164.

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Lobo, M. J., and S. Christophe. "OPPORTUNITIES AND CHALLENGES FOR AUGMENTED REALITY SITUATED GEOGRAPHICAL VISUALIZATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2020 (August 3, 2020): 163–70. http://dx.doi.org/10.5194/isprs-annals-v-4-2020-163-2020.

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Abstract. Augmented reality (AR) enables to display situated geographical visualizations, i.e visualizations that use virtual elements that are displayed in a geographical location. The place where the data is displayed complements the visualization. Many applications that take advantage of AR and situated visualizations exist, but they differ in the visualizations they present, their relationship to the geographic locations and goals. To better understand why and how AR based situated geovisualization is used, we review 45 papers coming from Human Computer Interaction, Visualization and Geographical Information Science venues that present such applications. Inspired by existing classifications, we characterize these papers according to the data they visualize and the geographical distance between the visualization and the data the visualization represents. This analysis reveals existing opportunities for situated geovisualization applications using AR.
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Kharakhash, О. "DATA VISUALIZATION: TRANSFORMING COMPLEX DATA INTO ACTIONABLE INSIGHTS." Automation of technological and business processes 15, no. 2 (June 19, 2023): 4–12. http://dx.doi.org/10.15673/atbp.v15i2.2520.

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Abstract. This article explores the power of data visualization and its impact on decision-making processes. It begins by highlighting the importance of data visualization in making data more accessible and understandable, emphasizing how visual representations enhance comprehension, facilitate exploration, and support data-driven decision-making. Real-world scenarios are provided to showcase the significant impact of data visualization on decision-making processes. Case studies illustrate how organizations have leveraged visualizations to gain actionable insights and drive strategic outcomes. The article delves into the process of choosing the right visualization techniques, exploring different types of visualization techniques such as charts, graphs, maps, and interactive dashboards. Guidelines for selecting the right visualization method are provided, focusing on effectively conveying desired insights. The article “Data Visualization: Transforming Complex Data into Actionable Insights” emphasizes the need to consider factors such as data complexity, audience, and objectives when choosing visualization techniques. It encourages data analysts to adopt a thoughtful approach in selecting visualizations that best serve the purpose and maximize impact. Design principles for creating visually appealing and informative data visualizations are explored, and open source information is utilized to highlight best practices and common pitfalls to avoid. The article concludes by summarizing the importance of data visualization in transforming complex data into actionable insights. It emphasizes the need for data analysts to prioritize data visualization skills and enhance their visual storytelling abilities to effectively communicate insights, influence stakeholders, and drive meaningful outcomes. Overall, the article provides readers with knowledge, insights, and practical guidance to harness the power of data visualization and unlock the full potential of their data.
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Dissertations / Theses on the topic "Visualization"

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Liu, Jiayi. "Visualization of Weather Data : Temperature trend visualization." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-20969.

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Weather data are huge. Traditional visualization techniques are limited to show temperature trends. Pixel-based approaches could be used to visualize the huge amount of weather data and in process show the temperature trends. A prototype using this approach is built to make temperature data more understandable in changing trends. It is implemented using a 2D representation and many popular interaction techniques. It is a lightweight and reusable tool to visualize temperatures.
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Brath, R. "Text in visualization : extending the visualization design space." Thesis, London South Bank University, 2018. http://researchopen.lsbu.ac.uk/2743/.

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This thesis is a systematic exploration and expansion of the design space of data visualization specifically with regards to text. A critical analysis of text in data visualizations reveals gaps in existing frameworks and the use of text in practice. A cross-disciplinary review across fields such as typography, cartography and technical applications yields typographic techniques to encode data into text and provides the scope for the expanded design space. Mapping new attributes, techniques and considerations back to well understood visualization principles organizes the design space of text in visualization. This design space includes: 1) text as a primary data type literally encoded into alphanumeric glyphs, 2) typographic attributes, such as bold and italic, capable of encoding additional data onto literal text, 3) scope of mark, ranging from individual glyphs, syllables and words; to sentences, paragraphs and documents, and 4) layout of these text elements applicable most known visualization techniques and text specific techniques such as tables. This is the primary contribution of this thesis (Part A and B). Then, this design space is used to facilitate the design, implementation and evaluation of new types of visualization techniques, ranging from enhancements of existing techniques, such as, extending scatterplots and graphs with literal marks, stem & leaf plots with multivariate glyphs and broader scope, and microtext line charts; to new visualization techniques, such as, multivariate typographic thematic maps; text formatted to facilitate skimming; and proportionally encoding quantitative values in running text - all of which are new contributions to the field (Part C). Finally, a broad evaluation across the framework and the sample visualizations with cross-discipline expert critiques and a metrics based approach reveals some concerns and many opportunities pointing towards a breadth of future research work now possible with this new framework. (Part D and E).
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Дядечко, Алла Миколаївна, Алла Николаевна Дядечко, Alla Mykolaivna Diadechko, and V. Sulim. "Architectural visualization." Thesis, Видавництво СумДУ, 2008. http://essuir.sumdu.edu.ua/handle/123456789/16040.

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Lum, Eric Brian. "Expressive visualization /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2004. http://uclibs.org/PID/11984.

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Sivertsson, Anton. "Overviewing and VR information visualizations : How interacting with, and perceiving an information visualization in VR affects our overview of the information visualization." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210554.

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Society generates more and more data every day, and with competent ways to visualize it, we can learn new things about the world we live in. While traditional visualizations try to stay clear of 3D graphs because they are hard for a user to process without proper depth cues, VR technology allows us to better perceive 3D structures, but what happens to our overview of the data when we perceive and interact with it in 3D? 6 participants were subject to a 3D VR visualization of customer data with filtering possibilities, where they were to perform a series of short tasks as well as a more open-ended free form task. Qualitative data was gathered through extensive semi-structured interviews. Quantitative supportive data was gathered as well in the form of interaction logs, time to complete tasks and the Presence Questionnaire. After this first round of tests, feedback and data was compiled into a new version of the visualization that was then tested on seven new participants. Results showed that seeing the graph from different perspectives was important to gaining an overview of the 3D graph, but also to actively interact with the data helped participants gain an overview by digging deeper into the data. In order to dig into the data in the 3D graph, participants expressed that they would’ve liked to be able to compare subsets of the data.
Vi genererar ofantliga mängder data varje dag, men utan att visualisera denna data är det inte säkert att vi lär oss någonting av den. Med detta följer även ett behov av att visualisera denna data i flera dimensioner, något som varit svårt i informationsvisualiseringar tidigare då det är svårt att representera djup på en platt skärm så att människor förstår. Med VR-teknik kan vi däremot använda detta djupseende i informationsvisualiseringar, men vad händer med vår överblick av informationen när vi ser och interagerar med den i 3D?   6 testpersoner fick interagera med en 3D-visualisering av kunddata med filtreringsmöjligheter i VR och fick i denna utföra en serie mindre uppgifter samt en större, fri uppgift. Under testet samlades kvalitativ data in i form av utförliga semi-strukturerade intervjuer och kvantitativ supportdata i form av loggar av interaktioner, tid att slutföra uppgifter samt svar från Presence Questionnaire för alla testpersoner. Åsikterna från denna testrunda användes sedan för att skapa en ny version av 3Dvisualiseringen som sedan testades på 7 nya personer enligt samma studieformat.   Resultaten visade att det var viktigt att kunna se grafen från olika perspektiv för att få en överblick, såväl som att kunna aktivt filtrera och interagera med visualiseringen för att kunna gräva djupare i datan. För att kunna gräva djupare kände många testpersoner att de behövde ett sätt att enkelt kunna jämföra delmängder av datan med varandra.
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Chang, Jiae. "A PERCEPTUAL VISUALIZATION ASSISTANT FOR MULTI-DIMENSIONAL DATA VISUALIZATION." NCSU, 2001. http://www.lib.ncsu.edu/etd/public/etd-32441612810132541/etd.pdf.

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Jankun-Kelly, T. J. "Visualizing Visualization : a model and framework for visualization exploration /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2003. http://uclibs.org/PID/11984.

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Xu, Yinglai. "Fluid Interactive Information Visualization: A Visualization Tool for Book Recommendation." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216941.

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The accuracy of recommender systems has been largely discussed and the user experience of the recommended systems is now becoming a new focus. Combining recommendations with information visualization (InfoVis) can be a way to improve the acceptance of the system. This thesis investigates how InfoVis can support the recommended systems, aiming at improving the enjoyment and engagement of the user experience. Three prototypes are designed to evaluate the impact of using InfoVis and fluid interactive InfoVis on user engagement and enjoyment with exploratory of recommended books. The methods of product reaction card and Likert questionnaire are used during the evaluation. Results suggest that InfoVis is a viable way to improve the engagement and enjoyment of the book recommended system and it should be further researched.
Precisionen för rekommenderingssystem har diskuterats i hög grad och användarupplevelsen för rekommenderingssystem har nu blivit ett nytt fokus. Att kombinera rekommendationer med informationsvisualisering (InfoVis) är ett möjligt vis att förbättra systemets acceptans. Denna rapport undersöker hur informationsvisualisering kan kompletterarekommenderingssystemen, med fokus på att förbättra användarglädjen och engagemanget i användarupplevelsen. Tre prototyper designas i syfte att evaluera påverkan som InfoVis, och fluid interactive InfoVis, har på engagemang och användarglädje i och med exploration av rekommenderade böcker. Produktreaktionskort och Likertfrågeformulär användes under evalueringen. Resultaten indikerar att InfoVis är en möjlig lösning för att förbättra engagemang och användargläjde i samband med bokrekommendationer, och att det bör undersökasytterligare.
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Manovich, Lev. "What is visualization?" Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2011/4984/.

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Over the last 20 years, information visualization became a common tool in science and also a growing presence in the arts and culture at large. However, the use of visualization in cultural research is still in its infancy. Based on the work in the analysis of video games, cinema, TV, animation, Manga and other media carried out in Software Studies Initiative at University of California, San Diego over last two years, a number of visualization techniques and methods particularly useful for cultural and media research are presented.
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Hui, Wu. "Visualization of Bags." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-28398.

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The purpose of this thesis is to develop a toolkit to visualize bag calculations for teaching. We take full advantage of interaction techniques in Computer Science to achieve it, which could lead to a modern and impressive way for teaching.   In this thesis, the developed toolkit is going to show the bag calculations and corresponding animations interactively and aesthetically which make new learners easier to acquire the concept of multiset.
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Books on the topic "Visualization"

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Grant, Robert. Data Visualization. Boca Raton, Florida : CRC Press, [2019]: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315201351.

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Brodlie, K. W., J. R. Gallop, C. D. Osland, L. A. Carpenter, R. J. Hubbold, P. Quarendon, R. A. Earnshaw, and A. M. Mumford, eds. Scientific Visualization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-76942-9.

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Badoer, Emilio, ed. Visualization Techniques. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-897-9.

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Anouncia, S. Margret, Hardik A. Gohel, and Subbiah Vairamuthu, eds. Data Visualization. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2282-6.

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Diehl, Stephan, ed. Software Visualization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45875-1.

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Hansen, Charles D., Min Chen, Christopher R. Johnson, Arie E. Kaufman, and Hans Hagen, eds. Scientific Visualization. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6497-5.

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Zhang, Kang, ed. Software Visualization. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0457-3.

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Spence, Robert. Information Visualization. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07341-5.

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Strothotte, Thomas. Computational Visualization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-59847-0.

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Dodge, Martin, Mary McDerby, and Martin Turner, eds. Geographic Visualization. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470987643.

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Book chapters on the topic "Visualization"

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Zamora Saiz, Alfonso, Carlos Quesada González, Lluís Hurtado Gil, and Diego Mondéjar Ruiz. "Visualization." In An Introduction to Data Analysis in R, 111–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48997-7_4.

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Colomb, Robert M. "Visualization." In Information Spaces, 173–88. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0163-5_13.

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Torbert, Shane. "Visualization." In Applied Computer Science, 61–90. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-1888-7_3.

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Beer, Thomas, and Tobias Meisen. "Visualization." In Integrative Computational Materials Engineering, 131–41. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527646098.ch7.

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Rubner, Yossi, and Carlo Tomasi. "Visualization." In Perceptual Metrics for Image Database Navigation, 79–90. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3343-3_6.

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Peled, Doron A. "Visualization." In Texts in Computer Science, 299–316. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3540-6_11.

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Shen, Yuzhong. "Visualization." In Modeling and Simulation Fundamentals, 181–225. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470590621.ch7.

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Meijers, Alexander. "Visualization." In Immersive Office 365, 197–221. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5845-3_8.

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Morra, Gabriele. "Visualization." In Lecture Notes in Earth System Sciences, 15–33. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55682-6_2.

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Turner, J. Rick, J. Rick Turner, Jonathan Newman, Alexandra Erdmann, Erin Costanzo, Leah Rosenberg, Jonathan Newman, et al. "Visualization." In Encyclopedia of Behavioral Medicine, 2032. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_101842.

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Conference papers on the topic "Visualization"

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Queiroz Santos, Caroline, and Milene Selbach Silveira. "Design de Visualizações Narrativas Interativas." In XVII Simpósio Brasileiro de Fatores Humanos em Sistemas Computacionais. Sociedade Brasileira de Computação (SBC), 2018. http://dx.doi.org/10.5753/ihc.2018.4173.

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Narrative visualization is an emerging data visualization field and has been used for the purpose of communicating information efficiently and intuitively as well as providing greater engagement in data exploration. In this mini-course, we will present and discuss fundamental concepts for interactive narrative visualizations design, and explore these concepts - in theory, and practice - by means of a model that aims to enable reflection on decisions to be taken in narrative visualization’s design.
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Humphrey, M. C. "Creating reusable visualizations with the Relational Visualization Notation." In Proceedings Visualization 2000. VIS 2000. IEEE, 2000. http://dx.doi.org/10.1109/visual.2000.885676.

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Williams, Trefor, and John Betak. "Visualization of Railroad Equipment Accident Causes Using Data Visualization Systems and GIS." In 2017 Joint Rail Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/jrc2017-2239.

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The objective of this paper is to demonstrate how GIS and data visualization systems can be used to identify spatial relationships to add to our understanding of railroad accident factors. Examples are given of the spatial analysis of broken rail accidents and grade crossing accidents on GIS maps. Additionally, using the Weave data visualization system a data dashboard was constructed that shows the complex interaction between variables like track type, FRA track classification, train speed and track density with broken rail accident causes. The findings indicate that broken rail accidents occur most frequently in the Midwest. Possibly this trend is related to climate change and increased temperatures and precipitation in the United States. GIS visualizations also showed that many truck-trailer accidents at grade crossings occur in low population areas. This work indicates that GIS and data visualizations are a useful method of identifying trends in railroad accidents.
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Kumar Uppalapati, Vinay, and Bo Sun. "Automated Visualization for Visual Analytics: Trends, Challenges, and Opportunities." In 12th International Conference on Human Interaction and Emerging Technologies (IHIET 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005502.

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Visualization, as a major approach of visual analytics, involves many human interaction techniques, especially in terms of how individuals communicate, comprehend, and interpret information. Creating visualizations is a tedious process and requires skill, but automatic data visualization technologies have made it easier to create visualizations. They completely changed the landscape of data analysis and decision-making processes. As the demand for effective and efficient visualization solutions grows across diverse sectors, researchers and practitioners have developed a plethora of autonomous systems aimed at transforming raw data into meaningful visual representations. This paper investigates the methodologies utilized by these systems, categorizing them based on machine learning approaches combined with various data inputs, template-based approach, and other technique/algorithm-based approach. We collected 31 top-tier journal papers in the field and shed light on the diverse techniques employed in generating visualizations automatically, enhancing our understanding of their capabilities, compatibility, and usability across various contexts. Our survey aims to provide insights into the strengths, limitations, and potential areas for future exploration in automatic data visualization, offering guidance to practitioners, researchers, and developers in selecting appropriate techniques for their specific needs and datasets. By systematically examining these systems and pinpointing areas for improvement, we contribute to the advancement and refinement of automatic data visualization methodologies, fostering progress in this dynamically evolving domain.
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Lupton, Glenn. "Visualization---Visualization using Linux clusters." In the 2006 ACM/IEEE conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1188455.1188492.

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Hauser, Helwig. "Visualization." In the 2009 Spring Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1980462.1980464.

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Williams, Trefor, James Abello, John Betak, and David Desimone. "Using Data Visualization to Analyze Grade Crossing Accidents." In 2015 Joint Rail Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/jrc2015-5695.

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The Federal Railroad Administration grade crossing accident database contains numerous interrelated variables. Understanding of how the variables are interrelated can be enhanced using modern visualization techniques. These techniques can allow managers from railroads and government agencies to find complex variables relationships not usually provided by routine statistical analyses. For this research we have developed several dashboards of linked visualizations using the Weave data visualization software [5]. Our visualizations explore various accident types of concern to the railroad industry including trespassing and pedestrian accidents, passenger train accidents, actions of highway users involved in accidents, and the effect of different types of warning devices on grade crossing accidents. In addition, we are currently developing an advanced visualization system that views the accident data as time varying events occurring over a fixed grade crossings topology. This view allows the application of a recent network data abstraction termed “Graph Cards.” We present initial examples of the advanced system that provides a variety of filtering mechanisms to view statistical distributions and their time varying behavior over the grade crossings topology.
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Oliveira, George M., and Simone D. J. Barbosa. "Evaluating ChatGPT to Support Data Visualization Design." In Anais Estendidos do Simpósio Brasileiro de Fatores Humanos em Sistemas Computacionais, 221–25. Sociedade Brasileira de Computação, 2024. http://dx.doi.org/10.5753/ihc_estendido.2024.242031.

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Large language models (LLMs) can help retrieve information to answer questions, construct images and audio, and assist in complex activities such as data visualization design. The latter requires specific knowledge that can be found on the internet and therefore used to train LLMs. This work investigates the ability of ChatGPT to assist in data visualization design. We conduct a metrics-based evaluation of the model and plan to expand it to understand the views of users who create visualizations, whether they are experts or not.
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Sizykh, A. K., and V. N. Khokhlova. "Features of lighting settings for interior visualization using the example of 3D visualization of a cottage." In Modern Problems of Telecommunications - 2024. Siberian State University of Telecommunications and Information Systems, 2024. http://dx.doi.org/10.55648/spt-2024-1-278.

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This paper discusses the features of lighting settings for creating photorealistic 3D visualization using the example of visualizing the interior of a cottage. The work was done in 3ds Max and the Corona Renderer. Room visualizations show the nuances of lighting settings to simulate natural daylight and simulate lighting from artificial light sources.
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Макарова, Елена, Elena Makarova, Дмитрий Лагерев, Dmitriy Lagerev, Федор Лозбинев, and Fedor Lozbinev. "Features of Big Text Data Visualization for Managerial Decision Making." In 29th International Conference on Computer Graphics, Image Processing and Computer Vision, Visualization Systems and the Virtual Environment GraphiCon'2019. Bryansk State Technical University, 2019. http://dx.doi.org/10.30987/graphicon-2019-2-99-102.

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This paper describes text data analysis in the course of managerial decision making. The process of collecting textual data for further analysis as well as the use of visualization in human control over the correctness of data collection is considered in depth. An algorithm modification for creating an "n-gram cloud" visualization is proposed, which can help to make visualization accessible to people with visual impairments. Also, a method of visualization of n-gram vector representation models (word embedding) is proposed. On the basis of the conducted research, a part of a software package was implemented, which is responsible for creating interactive visualizations in a browser and interoperating with them.
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Reports on the topic "Visualization"

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Schnitzlein, Daniel. Principles of Data Visualization. Instats Inc., 2024. http://dx.doi.org/10.61700/hltlj4cwyot2c1624.

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This seminar provides an essential introduction to the principles of data visualization for academic researchers and professionals. It focuses on understanding how to effectively communicate quantitative information through visual means, with an emphasis on audience-centric design. Attendees will learn how to select appropriate chart types, declutter visualizations, and enhance clarity, all without relying on a specific software tool. This course is designed to improve data storytelling and ensure that visual presentations of data are both accurate and compelling.
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Monroe, Laura Marie. HPC Visualization. Office of Scientific and Technical Information (OSTI), April 2015. http://dx.doi.org/10.2172/1179065.

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Neal, William J., Sidney T. Weinstein, Amy E. Alving, John H. Cafarella, and John Cittadino. Battlefield Visualization. Fort Belvoir, VA: Defense Technical Information Center, December 1998. http://dx.doi.org/10.21236/ada363997.

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Spencer, Joshua Bradly, Roger Lee Martz, and Jennifer Louise Alwin. Transport Visualization - TranzViz. Office of Scientific and Technical Information (OSTI), May 2018. http://dx.doi.org/10.2172/1438156.

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Pomplun, A. R., G. J. Templet, J. N. Jortner, J. A. Friesen, J. Schwegel, and K. R. Hughes. Visualization Design Environment. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/5897.

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Bock, Geoffrey. When Visualization Matters. Boston, MA: Patricia Seybold Group, January 2004. http://dx.doi.org/10.1571/psgp1-16-04cc.

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Niles, Kenneth, Joseph Jabour, Joshua Church, and Timothy Garton. TradeAnalysis visualization comparisons. Engineer Research and Development Center (U.S.), August 2019. http://dx.doi.org/10.21079/11681/33809.

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Angelini, Richard C. EnSight Volume Visualization. Fort Belvoir, VA: Defense Technical Information Center, November 2012. http://dx.doi.org/10.21236/ada579690.

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Smith, Stephen F., Marcel A. Becker, Mark A. Derthick, and Laurence A. Kramer. Scheduling and Visualization. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada424933.

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Sewell, Christopher Meyer. LANL SDAV Visualization Update. Office of Scientific and Technical Information (OSTI), June 2014. http://dx.doi.org/10.2172/1134773.

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