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1.
IEEE Comput Graph Appl ; 41(6): 7-12, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34890313

RESUMO

The increasing use of artificial intelligence (AI) technologies across application domains has prompted our society to pay closer attention to AI's trustworthiness, fairness, interpretability, and accountability. In order to foster trust in AI, it is important to consider the potential of interactive visualization, and how such visualizations help build trust in AI systems. This manifesto discusses the relevance of interactive visualizations and makes the following four claims: i) trust is not a technical problem, ii) trust is dynamic, iii) visualization cannot address all aspects of trust, and iv) visualization is crucial for human agency in AI.

2.
IEEE Comput Graph Appl ; 41(5): 7-15, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34506269

RESUMO

The medical domain has been an inspiring application area in visualization research for many years already, but many open challenges remain. The driving forces of medical visualization research have been strengthened by novel developments, for example, in deep learning, the advent of affordable VR technology, and the need to provide medical visualizations for broader audiences. At IEEE VIS 2020, we hosted an Application Spotlight session to highlight recent medical visualization research topics. With this article, we provide the visualization community with ten such open challenges, primarily focused on challenges related to the visualization of medical imaging data. We first describe the unique nature of medical data in terms of data preparation, access, and standardization. Subsequently, we cover open visualization research challenges related to uncertainty, multimodal and multiscale approaches, and evaluation. Finally, we emphasize challenges related to users focusing on explainable AI, immersive visualization, P4 medicine, and narrative visualization.

3.
IEEE Comput Graph Appl ; 41(4): 125-132, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34264822

RESUMO

In recent years, research on immersive environments has experienced a new wave of interest, and immersive analytics has been established as a new research field. Every year, a vast amount of different techniques, applications, and user studies are published that focus on employing immersive environments for visualizing and analyzing data. Nevertheless, immersive analytics is still a relatively unexplored field that needs more basic research in many aspects and is still viewed with skepticism. Rightly so, because in our opinion, many researchers do not fully exploit the possibilities offered by immersive environments and, on the contrary, sometimes even overestimate the power of immersive visualizations. Although a growing body of papers has demonstrated individual advantages of immersive analytics for specific tasks and problems, the general benefit of using immersive environments for effective analytic tasks remains controversial. In this article, we reflect on when and how immersion may be appropriate for the analysis and present four guiding scenarios. We report on our experiences, discuss the landscape of assessment strategies, and point out the directions where we believe immersive visualizations have the greatest potential.

4.
PLoS Comput Biol ; 17(4): e1008901, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33822781

RESUMO

[This corrects the article DOI: 10.1371/journal.pcbi.1008259.].

5.
IEEE Comput Graph Appl ; 41(2): 8-16, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33729921

RESUMO

We argue that visualization research has overwhelmingly focused on users from the economically developed world. However, billions of people around the world are rapidly emerging as new users of information technology. Most of the next billion users of visualization technologies will come from parts of the world that are extremely populous but historically ignored by the visualization research community. Their needs may be different to the types of users that researchers have targeted in the past, but, at the same time, they may have even more to gain in terms of access to data potentially affecting their quality of life. We propose a call to action for the visualization community to identify opportunities and use cases where users can benefit from visualization; develop universal design principles; extend evaluations by including the general population; and engage with a wider global population.

6.
IEEE Comput Graph Appl ; 41(1): 8-14, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33444127

RESUMO

Public awareness and concern about climate change often do not match the magnitude of its threat to humans and our environment. One reason for this disagreement is that it is difficult to mentally simulate the effects of a process as complex as climate change and to have a concrete representation of the impact that our individual actions will have on our own future, especially if the consequences are long term and abstract. To overcome these challenges, we propose to use cutting-edge artificial intelligence (AI) approaches to develop an interactive personalized visualization tool, the AI climate impact visualizer. It will allow a user to enter an address-be it their house, their school, or their workplace--and it will provide them with an AI-imagined possible visualization of the future of this location in 2050 following the detrimental effects of climate change such as floods, storms, and wildfires. This image will be accompanied by accessible information regarding the science behind climate change, i.e., why extreme weather events are becoming more frequent and what kinds of changes are happening on a local and global scale.

7.
IEEE Comput Graph Appl ; 40(6): 88-96, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33095702

RESUMO

In interactive visual machine learning (IVML), humans and machine learning algorithms collaborate to achieve tasks mediated by interactive visual interfaces. This human-in-the-loop approach to machine learning brings forth not only numerous intelligibility, trust, and usability issues, but also many open questions with respect to the evaluation of the IVML system, both as separate components, and as a holistic entity that includes both human and machine intelligence. This article describes the challenges and research gaps identified in an IEEE VIS workshop on the evaluation of IVML systems.

9.
IEEE Comput Graph Appl ; 40(5): 108-119, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32833626

RESUMO

The American National Academies of Sciences, Engineering, and Medicine (NASEM) has recently released the report "Reproducibility and Replicability in Science." The report has prompted discussions within many disciplines about the extent of the current adoption of reproducibility and replicability, the challenges involved in publishing reproducible results as well as strategies for improving. We organized a panel at the IEEE VIS conference 2019 to start a discussion on the reproducibility challenges faced by the visualization community and how those challenges might be addressed. In this viewpoint, we summarize key findings of the NASEM report, the panel discussion, and outline a set of recommendations for the visualization community.

10.
IEEE Comput Graph Appl ; 40(4): 84-95, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32540790

RESUMO

Visualizations produced by collaborations between artists, scientists, and visualization experts lay claim to being not only more effective in delivering information but also more effective in their abilities to elicit qualities like human connection. However, as prior work in the visualization community has demonstrated, it is difficult to evaluate these claims because characteristics associated with human connection are not easily measured quantitatively. In this Visualization Viewpoints piece, we address this problem in the context of our work to develop methods of evaluating visualizations created by Sculpting Visualization, a multidisciplinary project that incorporates art and design theory and practice into the process of scientific visualization. We present the design and results of a study in which we used close reading, a formal methodology used by humanities scholars, as a way to test reactions and analyses from evaluation participants related to an image created using Sculpting Visualization. In addition to specific suggestions about how to improve future iterations of the visualization, we discuss key findings of the evaluation related to contextual information, visual perspective, and associations that individual viewers brought to bear on their experience with the visualization.


Assuntos
Gráficos por Computador , Visualização de Dados , Escultura , Encéfalo/diagnóstico por imagem , Ciências da Terra , Golfo do México , Humanos , Modelos Teóricos , Neuroimagem
11.
IEEE Comput Graph Appl ; 40(3): 73-82, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32356729

RESUMO

Interactive data exploration and analysis is an inherently personal process. One's background, experience, interests, cognitive style, personality, and other sociotechnical factors often shape such a process, as well as the provenance of exploring, analyzing, and interpreting data. This Viewpoint posits both what personal information and how such personal information could be taken into account to design more effective visual analytic systems, a valuable and under-explored direction.

12.
IEEE Comput Graph Appl ; 40(2): 82-90, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32149613

RESUMO

The visualization research community can and should reach broader audiences beyond data-savvy groups of people, because these audiences could also greatly benefit from visual access to data. In this article, we discuss four research topics-personal data visualization, data visualization on mobile devices, inclusive data visualization, and multimodal interaction for data visualization-that, individually and collaboratively, would help us reach broader audiences with data visualization, making data more accessible.

13.
IEEE Comput Graph Appl ; 40(1): 90-98, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31944943

RESUMO

Scientific users present unique challenges to visualization researchers. Their high-level tasks require them to apply domain-specific expertise. We introduce a broader audience to the CinemaScience project and demonstrate how CinemaScience enables efficient visualization workflows that can bring in scientist expertise and drive scientific insight.

14.
IEEE Comput Graph Appl ; 39(6): 76-85, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31714213

RESUMO

In situ visualization is an increasingly important approach for computational science, as it can address limitations on leading edge high-performance computers and also can provide an increased spatio-temporal resolution. However, there are many open research issues with effective in situ processing. This article describes the challenges identified by a recent Dagstuhl Seminar on the topic.

15.
IEEE Comput Graph Appl ; 39(5): 8-17, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31442961

RESUMO

When assessing the value of visualizations, researchers traditionally focus on efficiency, comprehension, or insight. However, analyzing successful data physicalizations leads to a deep appreciation for hedonic qualities. Informed by the role of emotion in psychology, art, design, marketing, and HCI, we argue for an expanded definition of value, applicable to all forms of data visualization.

16.
IEEE Comput Graph Appl ; 39(4): 78-85, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31226061

RESUMO

Promoting a wider range of contribution types can facilitate healthy growth of the visualization community, while increasing the intellectual diversity of visualization research papers. In this paper, we discuss the importance of contribution types and summarize contribution types that can be meaningful in visualization research. We also propose several concrete next steps we can and should take to ensure a successful launch of the contribution types.

17.
IEEE Comput Graph Appl ; 39(3): 67-72, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31034400

RESUMO

Recently, there has been an increasing trend to extend the demonstrational interaction paradigm to visualization tools. As more analytic operations can be performed by demonstration, new user tasks can be supported. In this paper, we discuss the properties of tasks where the by-demonstration paradigm can be effective and describe the main components needed to implement the demonstrational paradigm in visualization tools.

18.
IEEE Comput Graph Appl ; 39(1): 44-52, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30869597

RESUMO

Visualization is thriving as an academic discipline. However, the development of visualization heavily relies on applications in other base sciences. We examine the visualization development process, which includes both collaborative development with domain scientists and independent development by visualization tool developers, and tell the behind-the-scene stories of FluoRender.


Assuntos
Gráficos por Computador , Processamento de Imagem Assistida por Computador , Software , Animais , Encéfalo/citologia , Encéfalo/diagnóstico por imagem , Drosophila/citologia
19.
IEEE Comput Graph Appl ; 39(2): 95-103, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30908186

RESUMO

This paper explores the meaning of the term "skill" in the context of information (data) visualization and its place in the labor market. It examines the visualization skills and software competencies that are in high demand in industry today, and the ramifications for teaching Data Visualization for professional students in higher education.

20.
IEEE Comput Graph Appl ; 32(2): 89-95, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-24804950

RESUMO

Early detection and rapid response to infectious-disease outbreaks rely on effective decision making based on information from disparate sources. To improve decision-making in outbreak detection and response, it's important to understand how public health practitioners seek relevant information. Epinome, a user-centric visual-analytics system, supports research on decision-making in public health, particularly evaluation of information search strategies. Epinome facilitates investigation of scripted high-fidelity large-scale simulated disease outbreaks. Its dynamic environment seamlessly evolves and adapts as the user's tasks and focus change. This video shows how the Epinome system facilitates interactive simulations of disease outbreaks.


Assuntos
Gráficos por Computador , Simulação por Computador , Sistemas de Gerenciamento de Base de Dados , Epidemiologia , Surtos de Doenças , Humanos
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