The State‐of‐the‐Art in Predictive Visual Analytics

Yafeng Lu; Rolando Garcia; Brett Hansen; Michael Gleicher; Ross Maciejewski

doi:10.1111/cgf.13210

The State‐of‐the‐Art in Predictive Visual Analytics

Computer Graphics Forum ◽

10.1111/cgf.13210 ◽

2017 ◽

Vol 36 (3) ◽

pp. 539-562 ◽

Cited By ~ 21

Author(s):

Yafeng Lu ◽

Rolando Garcia ◽

Brett Hansen ◽

Michael Gleicher ◽

Ross Maciejewski

Keyword(s):

Visual Analytics ◽

State Of The Art ◽

The State

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The State of the Art of Visual Analytics

Springer Proceedings in Physics - EKC 2009 Proceedings of the EU-Korea Conference on Science and Technology ◽

10.1007/978-3-642-13624-5_20 ◽

2010 ◽

pp. 213-222 ◽

Cited By ~ 1

Author(s):

Dong-Han Ham

Keyword(s):

Visual Analytics ◽

State Of The Art ◽

The State

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Science of Analytical Reasoning

Information Visualization ◽

10.1057/ivs.2009.28 ◽

2009 ◽

Vol 8 (4) ◽

pp. 254-262 ◽

Cited By ~ 22

Author(s):

William Ribarsky ◽

Brian Fisher ◽

William M. Pottenger

Keyword(s):

Real World ◽

Visual Analytics ◽

State Of The Art ◽

Design Principles ◽

The State ◽

Future Research ◽

Future Directions ◽

Analytical Reasoning ◽

Tools And Methods ◽

Real World Problems

There has been progress in the science of analytical reasoning and in meeting the recommendations for future research that were laid out when the field of visual analytics was established. Researchers have also developed a group of visual analytics tools and methods that embody visual analytics principles and attack important and challenging real-world problems. However, these efforts are only the beginning and much study remains to be done. This article examines the state of the art in visual analytics methods and reasoning and gives examples of current tools and capabilities. It shows that the science of visual analytics needs interdisciplinary efforts, indicates some of the disciplines that should be involved and presents an approach to how they might work together. Finally, the article describes some gaps, opportunities and future directions in developing new theories and models that can be enacted in methods and design principles and applied to significant and complex practical problems and data.

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The State of the Art in Integrating Machine Learning into Visual Analytics

Computer Graphics Forum ◽

10.1111/cgf.13092 ◽

2017 ◽

Vol 36 (8) ◽

pp. 458-486 ◽

Cited By ~ 52

Author(s):

A. Endert ◽

W. Ribarsky ◽

C. Turkay ◽

B.L. William Wong ◽

I. Nabney ◽

...

Keyword(s):

Machine Learning ◽

Visual Analytics ◽

State Of The Art ◽

The State

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Practical Picture Processing

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100051700 ◽

1974 ◽

Vol 32 ◽

pp. 338-339

Author(s):

T. A. Welton

Keyword(s):

Radiation Damage ◽

Coherence Length ◽

Spatial Information ◽

State Of The Art ◽

Coherent Radiation ◽

The State ◽

Energy Spread ◽

Electron Micrograph ◽

Picture Processing ◽

Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

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