Introduction to Visual Analytics

You Have Done the Readings What is visual analytics? Why do we need visual analytics?

Look at an example of anti-terrorists Most 911 hijackers came to the US with a tourist or business visa. ISIS-backed terrorists may do the same thing. Suppose we need to know that among foreign visitors who is going to plot a terror attack, what the nature of the attack would be, and when and where the attack would happen. What information do we have to have? What do we need to find out? How?

What challenges do we face to achieve these goals?

How technologies can help?

Visual + Analytics Analytics Visual tools Why combining them?

Business Analytics

Why Visual? Would mathematical analytics be good enough? Analyzing the four data pairs

Finding? How can you know more about these data sets?

Are They the Same?

Another Example: John Snow Defeated Cholera. What can you do with this table?

Visual Analytics Figure from Mastering The Information Age

Data: death records Model: simple aggregation based on address Visualization: mapping aggregated numbers to map Interaction: zooming in and out the map Knowledge: death distribution is not random, centralized around an area, which has a well.

The whole process could be more complex. Machine Statistical Analysis Sematic-based approach Data Mining Data Management Compression & Filtering Graphics & Rendering Human Human Cognition Human-Centered Perception Computing Information Design Visual intelligence Decision Making Theory The Best of both sides information visualization

A little bit history of visualization, visual analytics

SciVis, InfoVis, VAST Visualization Visual analytics Scientific visualization (SciVis) Data model Visualization to see results Spatial mapping Information visualization (InfoVis) Visual tool design Tasks, data type, etc. Flexible data mapping Visual analytics More complex data, more complex tasks (uncertain, ambiguous, unknown) Pushed by the 911 attack. Protecting Our Homeland Enabling profound insight Visual analytics science and technology (VAST)

http://vis.pnnl.gov/ http://www.vismaster.eu

Figure from Illuminating the Path

Visual analytics vs. information visualization

Data Aspect

Data type 01010101010 Analytics tools

Data quality

From Bier, Ishak, and Chi

Task Aspect

What analytical tasks to support? Generic tasks Selection, filtering, etc. Domain specific tasks, such as in GIS. Location-based filtering, density mapping, etc.

Analytical Process Aspect

Analytical reasoning Don’t have a unified theory yet. Generic reasoning processes Deduction, induction

Visualization Aspect

What do we need to see in analytics?

Many Challenges Ahead!

Visualization and Analytics Centers

In this course, it is about knowing the theories, practices and skills of VA. High level issues (analytical level) What is visual analytics? How does it work? Two case studies from VAST contests Analytical reasoning processes Low level issues (cognition and interaction levels) Visual perception Visualization designs and interactive tasks Technologies Data graph presentations JavaScript + D3.js Data preparation Python

What is visual analytics? “Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces.” “Visual analytics combines automated analysis techniques with interactive visualizations for an effective understanding, reasoning and decision making on the basis of very large and complex data sets.”

Visualization as A Medium Human perception and action Visualization Data

A Theoretical Foundation: External Cognition Cognition is usually about internal activities. Memory, reasoning, encoding External cognition External artifacts that help/amplify cognition Examples Your first essay assignment Would a grid be helpful to solve the puzzle? Doing math problems on paper Would writing down intermediate steps help? Visualization works the same way. Visual graphs are external artifacts to help us Memory, reasoning, relation, etc.

Faster Cognition Leveraging our cognitive capacities Pop-out effects Good at recognizing objects (compared with recall) .

Lighter Cognitive Load Perception Fast Cognition Slow

More Working Space

Xerox Star

Benefits of Interactive Visualization Less efforts Searching and/or sense-making Enhanced recognition Taking advantage of human cognition (e.g., color) Shifting level of cognition (e.g., animation) More resources Space, working memory, etc.

Major Tasks in Visualization Overview task Zoom task Filter task Details-on-demand task Relate task History task Extract task Navigation

More Details Overview Zoom Filter Details-on-demand Relate History Gain an overview of the entire collection. Zoom Zoom in on items of interest. Filter Filter out uninteresting items. Details-on-demand Select an item or group and get details when needed. Relate View relations hips among items. History Keep a history of actions to support undo, replay, and progressive refinement. Extract Allow extraction of sub-collections and of the query parameters.

Primary Data Types 1-dimensional: list, menu items 2-dimensional: table, spread sheet 3-dimensional: 3D models Multi-dimensional: user profile Temporal: stock price Tree: documents on a disk Network: Facebook friends Text: online documents Categorical: types (gender, race, education backgrounds, etc.)

Wednesday D3.js basic and histograms in D3