Data Visualization: Adding Spatial Components to Data

Data Visualization

What is Spatial Data Visualization?
In the context of this paper, Spatial Data Visualization is drawing a picture to represent information, often in the form of a map. It could be printed on paper, or displayed on a screen. The goal is to furnish data in a way that easily conveys information. Often, a desired message is difficult to see when presented in the form of a report or database table. When a spatial, or mapping component is added, the old cliché that “a picture is worth a thousand words” comes to life. Adding a mapping component is known as Spatial Data Integration: “Combining spatial and often, tabular data from different sources into a usable format.” Usable is emphasized because there are numerous ways to combine and process data, though only some methods produce beneficial results.

Why Spatially Enable?
Think of all of the legacy database systems in use today, and the typical deluge of reports generated for corporate management and other “decision support” functions. Is there a better way to view and analyze some of the information? Often, the answer is “yes.” When the data contains positional information, a map may be used to show the relative locations of items and assist with making make sensible decisions.

At a major database conference, the following statement was made: “Approximately 85% of the data used in commerce, industry and government has a spatial component. Usually, it is unused.” This represents a tremendous potential for the addition of spatial analysis.

Some examples of “location” information that might be found in existing tabular data include:

A full address
A ZIP code
City and/or state
A particular dealer or store where a sale was made or service performed
Telephone area-code and exchange
Job address
The club chapter where a membership is held
Social security number (first three digits are taken from the ZIP code where applied for)

Some types of problems that might be well suited to using data visualization techniques and spatial analysis include:

Where Do MV Customers Live?

Targeting a direct mail campaign
Opening a new store
Near a solid customer base
Avoid cannibalizing sales from existing stores
Select locations relative to competitors
Ask how far most customers actually travel to visit a business
Find the location of active or potential policyholders
Relative to a natural disaster which has taken place
Relative to a potential emergency such as a forest fire or flood plain

Routing or Drive Time

Delivery of items such as pizza, furniture, flowers or express packages
Commuting distance when writing an auto insurance policy
Distance to the nearest fire department when writing home or business insurance
Driving directions
To bring a client to your business
From the airport to a hotel in an unfamiliar city to assist a car rental customer
Trip routing for a vacation

Territory / Polygonal Calculations

Identify which rating territory a new insurance client is located in
Describe dealer service areas
Direct a consumer to the nearest repair depot
Identify field service office responsible for responding to a call
911 emergency calls
Identify which police, fire or ambulance covers a specific incident location