DATA VISUALIZATION

By

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S.V.V.D.Jagadeesh

Sr. Assistant Professor

Dept of Artificial Intelligence & Data Science

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LAKIREDDY BALI REDDY COLLEGE OF ENGINEERING

• Session Outcomes
• Visualization as part of Graphics
• Scientific Data Vs Information Visualization

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S.V.V.D.Jagadeesh

Saturday, July 5, 2025

Previously Discussed Topics

LBRCE

DATA VISUALIZATION

At the end of this Session, Student will be able to:

• Understand the visualization process (Understand-L2)

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

Session Outcomes

LBRCE

DATA VISUALIZATION

• To visualize data, one needs to define a mapping from the data to the display.
• There are many ways to achieve this mapping.
• The user interface consists of components, some of which deal with data needing to be entered, presented, monitored, analyzed, and computed.

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Process

LBRCE

DATA VISUALIZATION

• These user interface components are often input via dialog boxes, but they could be visual representations of the data to facilitate the selections required by the user.
• Visualizations can provide mechanisms for translating data and tasks into more visual and intuitive formats for users to perform their tasks.
• This means that the data values themselves, or perhaps the attributes of the data, are used to define graphical objects, such as points, lines, and shapes; and their attributes, such as size, position, orientation, and color.

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Process

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Process

LBRCE

DATA VISUALIZATION

• Another significant, yet often overlooked, component of the visualization process is the provision of interactive controls for the viewing and mapping of variables (attributes or parameters).
• While early visualizations were static objects, printed on paper or other fixed media, modern visualization is a very dynamic process, with the user controlling virtually all stages of the procedure, from data selection and mapping control to color manipulation and view refinement.

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Process

LBRCE

DATA VISUALIZATION

• Visualization is often part of a larger process, which may be exploratory data analysis, knowledge discovery, or visual analytics.
• In this discovery process, the preparation of data depends upon the task and often requires massaging erroneous or noisy data.
• Visualization and analysis go hand in hand with the goal of building a model that represents or approximates the data.
• Visualization in data exploration is used to convey information, discover new knowledge, and identify structures, patterns, anomalies, trends, and relationships.

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Process

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Computer Graphics Pipeline

• Modeling. A three-dimensional model, consisting of planar polygons defined by vertices and surface properties, is generated using a world coordinate system.
• Viewing. A virtual camera is defined at a location in world coordinates, along with a direction and orientation (generally given as vectors). All vertices are transformed into a viewing coordinate system based on the camera parameters.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Computer Graphics Pipeline

• Clipping. By specifying the bounds of the desired image (usually given by corner positions on a plane of projection placed in front of the camera), objects out of view can be removed, and those that are partially visible can be clipped. Objects may be transformed into normalized viewing coordinates to simplify the clipping process. Clipping can actually be performed at many different stages of the pipeline.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Computer Graphics Pipeline

• Hidden surface removal. Polygons facing away from the camera, or those obscured by others, are removed or clipped. This process may be integrated into the projection process.
• Projection. Three-dimensional polygons are projected onto the twodimensional plane of projection, usually using a perspective transformation. The results may be in a normalized 2D coordinate system or device/screen coordinates.
• Rendering. The actual color of the pixels associated with a visible polygon depends on a number of factors, including the material properties being synthesized (base color, texture, surface roughness, shininess), the type(s), location(s), color, and intensity of the light source(s), the degree of occlusion from direct light exposure, and the amount and color of light being reflected off of other objects onto the polygon

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Pipeline

• Data modeling. The data to be visualized, whether from a file or a database, has to be structured to facilitate its visualization. The name, type, range, and semantics of each attribute or field of a data record must be available in a format that ensures rapid access and easy modification.
• Data selection. Similar to clipping, data selection involves identifying the subset of the data that will be potentially visualized. This can occur totally under user control or via algorithmic methods, such as cycling through time slices or automatically detecting features of potential interest to the user.

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LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Pipeline

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Pipeline

• Data to visual mappings. The heart of the visualization pipeline is performing the mapping of data values to graphical entities or their attributes. Thus, one component of a data record may map to the size of an object, while others might control the position or color of the object. This mapping often involves processing the data prior to mapping, such as scaling, shifting, filtering, interpolating, or subsampling.
• Scene parameter setting (view transformations). As in traditional graphics, the user must specify several attributes of the visualization that are relatively independent of the data. These include color map selection (for different domains, certain colors have clearly defined meaning), sound map selection (in case the auditory channels will be conveying information as well), and lighting specifications (for 3D visualizations).

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Visualization Pipeline

• Rendering or generation of the visualization. The specific projection or rendering of the visualization objects varies according to the mapping being used; techniques such as shading or texture mapping might be involved, although many visualization techniques only require drawing lines and uniformly shaded polygons. Besides showing the data itself, most visualizations also include supplementary information to facilitate interpretation, such as axes, keys, and annotations.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Knowledge Discovery Pipeline

• Data. In the KD pipeline there is more focus on data, as the graphics and visualization processes often assume that the data is already structured to facilitate its display.
• Data integration, cleaning, warehousing and selection. These involve identifying the various data sets that will be potentially analyzed. Again, the user may participate in this step. This can involve filtering, sampling, subsetting, aggregating, and other techniques that help curate and manage the data for the data mining step.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Knowledge Discovery Pipeline

• Data mining. The heart of the KD pipeline is algorithmically analyzing the data to produce a model.
• Pattern evaluation. The resulting model or models must be evaluated to determine their robustness, stability, precision, and accuracy.
• Rendering or visualization. The specific results must be presented to the user. It does not matter whether we think of this as part of the graphics or visualization pipelines; the fact is that a user will eventually need to see the results of the process.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Knowledge Discovery Pipeline

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Role Of Perception

• In all visualizations, a critical aspect related to the user is the abilities and limitations of the human visual system.
• If the goal of visualization is to accurately convey information with pictures, it is essential that perceptual abilities be considered.
• A well-drawn picture can be stimulating, but if we are presenting a conclusion.
• Consider a collection of black squares spaced slightly apart.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Role Of Perception

• Note the effect these squares have as you stare at them.
• There are, of course, no moving black dots at the intersections of the white lines, but clearly such a presentation of data would create instabilities.
• It thus makes little sense to map a variable to a graphical attribute that humans have limited ability to control or quantify, if the goal is to communicate a numeric value with accuracy.

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Role Of Perception

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Saturday, July 5, 2025

The Role Of Perception

• Users interact with visualizations based upon what they see and interpret.
• Understanding how we see should help us produce better displays, or at least avoid producing very poor ones.
• About half of the human brain deals with visual input, and much of the processing is parallel and effectively continuous.
• Texture, color, and motion are examples of primitive attributes that we perceive.

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LBRCE

DATA VISUALIZATION

• Session Outcomes
• The Visualization Process
• Computer Graphics Pipeline
• Visualization Pipeline
• Knowledge Discovery Pipeline
• Role of Perception

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S.V.V.D.Jagadeesh

Saturday, July 5, 2025

Summary

LBRCE

DATA VISUALIZATION