In every field ,we need large number of information to be analyzed and study the behaviors of certain processes. Numerical simulations in supercomputers ,satellite cameras and other sources are amassing large amount of data files faster they can be interpreted. Scanning these huge amount of data files to determine their nature and relationships is a tedious job. But if the data are converted to a visual form it is very easier to infer various conclusions immediately. Producing graphical presentations for scientific, engineering and medical data sets and processes is generally referred to as scientific visualization. If the data sets are concerned with commerce , industry and other non scientific areas , it is called business visualization.
Definitions
- Visualization is the graphical presentation of information, with the goal of providing the viewer with a qualitative understanding of the information contents.
- Information may be data, processes, relations, or concepts.
- Graphical presentation may include manipulation of graphical entities (points, lines, shapes, images, text) and attributes (color, size, position, shape).
- Understanding may involve detection, measurement, and comparison, and is enhanced via interactive techniques and providing the information from multiple views and with multiple techniques.
Characteristics of Data
- Numeric, symbolic (or mix)
- Scalar, vector, or complex structure
- Various units
- Discrete or continuous
- Spatial, quantity, category, chronological , relational, structural
- Accurate or approximate
- Dense or sparse
- Ordered or non-ordered
- Disjoint or overlapping
- Binary, enumerated, multilevel
- Independent or dependent
- One dimensional or Multidimensional
- Single or multiple sets
- May have similarity or distance metric
- May have intuitive graphical representation (e.g. temperature with color)
- Has semantics which may be crucial in graphical consideration
Graphical entities and attributes
- Entity: point, line, polyline, glyph, surface, solid, image, text etc.
- Attribute: color/intensity, location, style, size, relative position/motion
- Example: Attribute of line may be color, style(dotted, solid, dashed ) , thickness etc.
What do we see and how well do we see it?
- Different viewers perceive different graphical/spatial/color in different degrees
- Context varies our sensitivity
- According to one researcher (Cleveland), in increasing inaccuracy
- Position along a common scale
- Position along identical, non-aligned scales
- Length
- Angle/slope
- Area
- Volume
- Shade/Saturation/intensity (informally derived)
- detection is proportional to percent change, not scale
- Stevens' law - perceived scale is proportional to a power of the actual scale.
What makes a good visualization?
- Effective: the viewer gets it (ease of interpretation)
- Accurate: sufficient for correct quantitative evaluation. Lie factor = size of visual effect/size of data effect
- Efficient: minimize data-ink ratio and chart-junk, show data, erase redundant data-ink
- Aesthetics: must not offend(hurt) viewer's senses (e.g. moire patterns)
- Adaptable: can adjust to serve multiple needs
Mapping data to graphics
- Examine cardinality of dimension with detectible variations in graphics
- Use scaling and offset to fit in range
- Use derived values (residuals, logs) to emphasize changes
- Use projections, other combinations, to compress information, get statistics
- Use random jiggling to separate overlaps
- Use multiple views to handle hidden relations, high dimensions
- Use effective grids, keys and labels to aid understanding
Interacting with the data
- Dynamically adjust mapping
- Tour data by varying views
- Labeling to get original data
- Deleting to eliminate clutter (disorder)
- Brushing/Highlighting to see correspondence in multiple views
- Zooming to focus attention
- Panning to explore neighborhoods
Common Techniques
- Charts: bar or pie
- Graphs: good for structure, relationships
- Plots: 1- to n-dimensional
- Maps: one of most effective
- Images: use color/intensity instead of distance (surfaces)
- 3-D surfaces and solids
- isosurfaces/slices
- transparency
- stereopsis : Taking picture in different viewpoint and combine.
- animation --
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