Visualization in scientific computing

McCormick, Bruce H.

doi:10.1145/43965.43966

Cited by 191 publications

(111 citation statements)

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“…These independent disciplines influence haptic visualization and provide the foundation and backbone for much of the research. Haptic research is influenced by the studies done in psychology, ergonomics, engineering, and virtual reality, while visualization is influenced by computer graphics, image processing, computer vision, computeraided design, signal processing, user interface studies [20]. In this section we take a brief look at key papers 1 , and key ideas, that directly impinge upon haptic visualization.…”

Section: Influential and Related Areasmentioning

confidence: 99%

“…Since the 1987 report on Scientific Visualization [20] there has been a growth of 'visual' methods to help users perceive information. The word visualization has become to commonly mean 'a visual form or graphic representation of data'.…”

Section: Introductionmentioning

confidence: 99%

“…In fact GROPE is probably the earliest use of the term 'haptic visualization'. The visualization field itself really started flourishing after the NSF report into Visualization in Scientific Computing in 1987 [20].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Where are we with Haptic Visualization?

Roberts

Panëels

2007

Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WHC'07

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There is a growing interest into non-visual forms of data communication, not only driven by the need for accessible representations but also because researchers are realizing the potential of understanding information better or differently through other modalities. Thus, haptic visualization is an immature but exciting area; it represents the abstract realization of information through the use of tactile or force-feedback devices. Through such a realization the user can gain quantitative, qualitative or nominal understanding of some underlying data. This paper presents the growth and development of haptic visualization, shows current trends, and acts as a snapshot of history. In fact, we remember the past based on temporal landmarks: we remember what we were doing when we heard the news of 9/11. Thus it is interesting and useful to look at the subject in the context of key events and seminal work. Moreover, it helps us to not re-invent the wheel: something that is far too common with interdisciplinary work. Thus, we take a holistic approach to the literature and place the research in context of important historic events and seminal work, which shows the reader where we have been, and points towards the future.

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Section: Influential and Related Areasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Where are we with Haptic Visualization?

Roberts

Panëels

2007

Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WHC'07

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“…With the advance of technology, data has grown exponentially during the past few years [1], which has spurred growing attention to data visualization in such fields as commercial finance, economics, medical MRI (Magnetic resonance imaging) applications [2] and so on. Data visualization allows the analysis and presentation of heterogeneous data in abstract form using computer graphics and interactive technologies [3].…”

Section: Introductionmentioning

confidence: 99%

An Automated IoT Visualization BIM Platform for Decision Support in Facilities Management

Chang

Dzeng

2018

Applied Sciences

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Building information modeling (BIM) is the digital representation of physical and functional characteristics (such as geometry, spatial relationship, and geographic information) of a facility to support decisions during its life cycle. BIM has been extended beyond 3D geometrical representations in recent years, and now includes time as a fourth dimension and cost as a fifth dimension, as well as such other applications as virtual reality and augmented reality. The Internet of Things (IoT) has been increasingly applied in various products (smart homes, wearables) to enhance work productivity, living comfort, and entertainment. However, research addressing the integration of these two technologies (BIM and IoT) is still very limited, and has focused exclusively on the automatic transmission of sensor information to BIM models. This paper describes an attempt to represent and visualize sensor data in BIM with multiple perspectives in order to support complex decisions requiring interdisciplinary information. The study uses a university campus as an example and includes several scenarios, such as an auditorium with a dispersed audience and energy-saving options for rooms with different functions (mechanical/electrical equipment, classrooms, and laboratory). This paper also discusses the design of a common platform allowing communication among sensors with different protocols (Arduino, Raspberry Pi), the use of Dynamo to accept sensor data as input and automatically redraw visualized information in BIM, and how visualization may help in making energy-saving management decisions.

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“…A medical researcher might be interested in tumors, while a climatologist might be interested in regions of high pressure. Because humans possess a highly developed visual system, transforming the data into images and movies that can be displayed, and providing the scientist with tools to control them can be a powerful visualization method [47]. Popular techniques employed to create such visualizations are direct volume rendering, slicing, and isocontouring.…”

mentioning

confidence: 99%

Isocontour based Visualization of Time-varying Scalar Fields

Mascarenhas

Snoeyink

2009

Mathematics and Visualization

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Summary. Time-varying scalar fields are produced by measurements or simulation of physical processes over time, and must be interpreted with the assistance of computational tools. A useful tool in interpreting the data is graphical visualization, often through level sets, or isocontours of a continuous function derived from the data. In this paper we survey isocontour based visualization techniques for time-varying scalar fields. We focus on techniques that aid selection of meaningful isocontours, and algorithms to extract chosen isocontours. IntroductionPhysical processes that are measured over time, or that are modeled and simulated on a computer, can produce large amounts of time-varying data that must be interpreted with the assistance of computational tools. Such data arises in a wide variety of studies including computational fluid dynamics [15], oceanography [6], medical imaging [60], and climate modeling [46]. The data typically consists of finitely many points in space-time and measured or computed values for each point. Often the values are scalar, with perhaps several scalar values for each sample point. E.g: Pressure, temperature, density. A study of motion or velocity of some kind will result in vector-valued data. In this paper, we focus on scalar-valued data, often called scalar fields. Irrespective of how the points are sampled, we can connect them into a mesh and interpolate the values to obtain a continuous function over the entire domain. Piecewise-linear interpolation is common for large amounts of data, because of its relative ease; multilinear interpolation is also used for regular grids.The goal is to understand the data, usually by exploring it for important features. A medical researcher might be interested in tumors, while a climatologist might be interested in regions of high pressure. Because humans possess a highly developed visual system, transforming the data into images and movies that can be displayed, and providing the scientist with tools to control them can be a powerful visualization method [47]. Popular techniques employed to create such visualizations are direct volume rendering, slicing, and isocontouring. Direct volume rendering employs two classes of algorithms to display all the data: imagespace projection and volume-space projection. In image-space projection algorithms we cast

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Visualization in scientific computing

Cited by 191 publications

References 0 publications

Where are we with Haptic Visualization?

Where are we with Haptic Visualization?

An Automated IoT Visualization BIM Platform for Decision Support in Facilities Management

Isocontour based Visualization of Time-varying Scalar Fields

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