Database Reference
In-Depth Information
9.4
File Formats for High-Performance Visualization
and Analytics
.........................................................
345
9.4.1
H5Part
........................................................
347
9.4.1.1
Motivation
...........................................
347
9.4.1.2
File Organization and API
..........................
349
..........................................
9.4.1.3
Parallel I/O
350
.............................................
9.4.2
HDF5 FastQuery
352
9.4.2.1
Functionality
.........................................
352
9.4.2.2
Architectural Layout
.................................
353
9.4.3
Status and Sample Applications
..............................
354
9.5
Query-Driven Visualization
..........................................
358
9.5.1
Implementing Query-Driven Visualization
...................
359
9.5.2
Case Study—Network Trac Analysis
.......................
360
9.6
Summary and Conclusion
............................................
363
Acknowledgments
..........................................................
364
References
.................................................................
365
9.1 Introduction
Scientific visualization, which is the transformation of abstract data into read-
ily comprehensible images, and visual data analysis/analytics, which combines
visualization with analysis, play a central role in the modern scientific process.
We use the umbrella term visualization to refer to this broad set of investi-
gatory techniques aimed at enabling knowledge discovery—gaining insight—
from large, complex collections of scientific data.
The term scientific visualization was coined in 1987 in a landmark report, 1
which said:
“Visualization is a method of computing. It transforms the symbolic into
the geometric, enabling researchers to observe their simulations and compu-
tations. Visualization offers a method for seeing the unseen. It enriches the
process of scientific discovery and fosters profound and unexpected insights.
In many fields, it is already revolutionizing the way scientists do science... The
goal of visualization is to leverage existing scientific methods by providing new
scientific insight through visual methods.”
Various data analysis methods covered in Chapter 8 can also benefit from
techniques covered in this chapter.
Although the term was coined in 1987, the art and science of visualization
dates back hundreds of years to DaVinci's illustrations, or even earlier, to
Cicero's written account of an early orrery constructed by the Greek philoso-
pher Posidonious to exhibit the diurnal motions of the sun, moon, and five
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