data visualization - christina friedle...attribute data • many types of attribute data –...
TRANSCRIPT
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Data Visualization
Classifying & Symbolizing Data
Map Design
Map Layout
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UNDERSTANDING MAPS
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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
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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
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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
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General Map
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Thematic Map
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Topographic Map
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Topological Map
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UNDERSTANDING YOUR DATAQualitative v. Quantitative
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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
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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
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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
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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
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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
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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
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VISUALIZATION TOOLS IN ARCGIS
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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)
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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
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QUALITATIVE DATA
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Each geographic feature is represented by a single color
Single Value
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Each geographic feature is represented by a different color
Unique Value
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Geographic features are grouped and each group is represented by a color
Unique Values
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QUANTITATIVE DATAGrouping into Classes
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Quantitative Classifications
• Natural Breaks
• Quantile
• Equal, Defined & Geometric Interval
• Standard Deviation
• Manual
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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
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Quantile
• Each class contains approximately an equal number of features
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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)
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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
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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.
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Manual
• The user determines the classes
• Used when the user is looking for features that meet specific criteria
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DATA VISUALIZATION EXAMPLES
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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
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MAP DESIGN AND LAYOUT
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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
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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?
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Map Elements
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Visual Hierarchy – established by how the elements are positioned on the map, colors contrast, weights of lines, and amount of detail
Map Layout
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Improved Map Layout
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Improved Map Layout
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Refining Map Layout
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Poor Attention to Detail Good Attention to Detail
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Choosing Appropriate Map Projections
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Drop Shadow
Line Styles for frames
Background Patterns
Full Compass
Zoom Lines
Colorful Logos
Decorative Type Fonts
Geometric Shapes
Decorative Design Elements
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Same Map – Emphasizing important map content, not decorative elements
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LABELING MAP FEATURES
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Map Labels
• Fonts, type styles, font family, special characters
• Size & spacing (characters & lines)• Type effects – callouts, shadows, halos• Placement • Layer hierarchy
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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
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MAP DESIGN RESOURCES
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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
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MAP CRITIQUE
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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
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