Data Visualization

Classifying & Symbolizing Data

Map Design

Map Layout

UNDERSTANDING MAPS

Maps as Tools

• Why do we use maps?– Spatially visualize data as opposed to charts,

graphs, tables– Communicate information to others– Explore, query, and analyze information– Used to generate hypothesis; GIS used to conduct

analysis to test hypothesis– Synthesize layers of information– Inform decision making

Cartographer “Code of Ethics”• Always have a straightforward agenda and have a defining

purpose or goal for each map• Always strive to know your audience• Do not intentionally lie with data• Always show all relevant data whenever possible• Data should not be discarded simply because they are

contrary to the position held by the cartographer• At a given scale, strive for an accurate portrayal of the data• The cartographer should avoid plagiarizing; report all data

sources• Symbolization should not be selected to bias the

interpretation of the map• The mapped result should be able to be repeated by other

cartographers• Attention should be given to differing cultural values and

principles

Map Types

• General Maps– Intended for a general audience and contain a variety

of data

• Thematic Maps– Geared towards a specific audience and focused on a

specific, single, geographic theme

• Topographic Maps– Describes physical features and terrain of a place

• Topological Maps– Focused on spatial relationships or a route

General Map

Thematic Map

Topographic Map

Topological Map

UNDERSTANDING YOUR DATAQualitative v. Quantitative

Attribute Data

• Many types of attribute data– Physical and environmental– Social, economic, political

• The type of data can have a large effect on the interpretation of the resulting values– Name of classes, such a soil types– Something that weighs 100lbs is 1/3 as much as something

that weighs 300lbs– Someone who came in 1st place may not have done 3x as

well as someone in 3rd place– Soil with a pH of 3 is not half as acidic as soil that has a pH

of 6

Symbolizing Qualitative v. Quantitative data

• Qualitative data:– Data classified or shown by category, rather than by

amount or rank.

– Example: Soil type, animal by species

– Nominal data

• Quantitative data:– Data grouped or shown by measurement of number or

amount.

– Example: population density

– Ordinal, Ratio, Interval, Cyclic data

Nominal Data

Identify one instance from another

Establish the group, class, member, or category with which the object is associated

These values are qualities, not quantities

Coding schemes for land use or soil types qualify as a nominal attribute

Ordinal or Rank Data

Determine position Show place, such as 1st, 2nd, or

3rd, but they do not establish magnitude or relative proportions

How much better, worse, healthier, and stronger, cannot be demonstrated

Median is a useful value with ordinal data

Ratio Data

Show you the relationship between two quantities

Values are derived relative to a fixed zero point

Examples of ratio measurement are age, distance, weight and volume, densities

Mathematical operations can be used on these values with predictable and meaningful results

Interval & Cyclic Data

Values not relative to a true zero point in time or space

Most temperature scales, pH value (interval)

Time of day, Months of year, aspect (cyclic)

Because there is no true zero point, only relative comparisons can be made between the measurement; mathematical operations do not produce meaningful results

VISUALIZATION TOOLS IN ARCGIS

Symbology Tools

• Once you know what kind of data you have, you can decide how to represent it on a map– Features

– Unique Values

– Categories (Usually qualitative – i.e grouping states into regions, NW, SW, etc.)

– Quantities (Quantitative)

David Theobald

ArcMap Method Point Line Area Raster

Feature (shows location) Nominal OrdinalInterval CyclicRatio

Nominal Ordinal Interval Cyclic Ratio

Nominal Ordinal Interval Cyclic Ratio

Categories- Unique values

Nominal Nominal Nominal Nominal

Quantities-Graduated color-Graduated symbols-Proportional symbols

OrdinalIntervalCyclicRatio

OrdinalIntervalCyclicRatio

OrdinalIntervalCyclicRatio

OrdinalIntervalCyclicRatio

Charts Ratio Ratio Ratio

Multiple Ratio Ratio Ratio

Displaying data types in ArcMap

QUALITATIVE DATA

Each geographic feature is represented by a single color

Single Value

Each geographic feature is represented by a different color

Unique Value

Geographic features are grouped and each group is represented by a color

Unique Values

QUANTITATIVE DATAGrouping into Classes

Quantitative Classifications

• Natural Breaks

• Quantile

• Equal, Defined & Geometric Interval

• Standard Deviation

• Manual

Natural Breaks

• Classes are based on natural groupings of data values

• Class breaks are set where there is a jump in values

• Groups with similar values are place in the same class

Quantile

• Each class contains approximately an equal number of features

Intervals

• Equal: Data is divided equally into a set number of intervals (specifies # of classes)

• Defined: User sets an interval value that equally divides range of values (specifies interval range)

Geometric Intervals

Determines the range of values and breaks data based on a geometric series

Approx. the same # of values with each class

Using the coefficient to ensure change between values is fairly consistent

Specifically for continuous data

Minimum Maximum Interval Coefficient

0.026539462 0.046593756 0.020054

0.046593757 0.059616646 0.013023 1.539927

0.059616647 0.068073471 0.008457 1.539927

0.068073472 0.081096361 0.013023 0.649382

0.081096362 0.101150655 0.020054 0.649382

0.101150656 0.132032793 0.030882 0.649382

0.132032794 0.179589017 0.047556 0.649382

Standard Deviation

• Features are placed in classes based on how much their values vary from the mean.

SD: measures how widely spread the values in a data set are. If many data points are close to the mean, then the standard deviation is small; if many data points are far from the mean, then the standard deviation is large. If all data values are equal,

then the standard deviation is zero.

Manual

• The user determines the classes

• Used when the user is looking for features that meet specific criteria

DATA VISUALIZATION EXAMPLES

Symbolizing Data

• Choosing how to symbolize geographic data is based on our ability to understand spatial distributions and patterns

• J. Bertin’s Semiology of Graphics– Location in space, size, shape, color, texture,

orientation, arrangement and focus

MAP DESIGN AND LAYOUT

Map Design

• “Involves all major decision-making having to do with specification of scale, projection, symbology, typography, color and so on”

• Essentials of Map Design– Purpose

– Audience

– Layout

– Export / Final Product

Purpose & Audience

• What information is being mapped?• Who is using the map?• How knowledgeable are the users about the

map info?• Is it stand alone or accompanied by

documents, tables, etc.?• How will the map be displayed?

Map Elements

Visual Hierarchy – established by how the elements are positioned on the map, colors contrast, weights of lines, and amount of detail

Map Layout

Improved Map Layout

Improved Map Layout

Refining Map Layout

Poor Attention to Detail Good Attention to Detail

Choosing Appropriate Map Projections

Drop Shadow

Line Styles for frames

Background Patterns

Full Compass

Zoom Lines

Colorful Logos

Decorative Type Fonts

Geometric Shapes

Decorative Design Elements

Same Map – Emphasizing important map content, not decorative elements

LABELING MAP FEATURES

Map Labels

• Fonts, type styles, font family, special characters

• Size & spacing (characters & lines)• Type effects – callouts, shadows, halos• Placement • Layer hierarchy

General Rules for Labels

• No more than 2 font families on maps– Characteristics used to establish different

categories of features: color, posture (italics, bold,

roman), size, arrangement (straight v. curved), CASE, leading, character spacing

• Serif for physical features– Small finishing strokes on letters

• Sans Serif for cultural features– Fonts without serif

MAP DESIGN RESOURCES

Additional Resources for Map Design

• Designing Better Maps, Cynthia Brewer

• How to Lie With Maps, Mark Monmonier

• Making Maps: A Visual Guide to Map Design for GIS, John Krygier

• How Maps Work: Representation, Visualization, and Design, Alan M. MacEachren

• The Power of Maps, Denis Wood

MAP CRITIQUE

Map Critique

• Map elements - title, name, legend, north arrow, scale bar, neatline

• Map layout

• Appropriate data representation – color, symbols, labels

• Consideration of purpose and audience

• Map scale & Projection

• Attention to detail