Attribute Data
Attribute data describes the characteristics of spatial features:
Each row (record) represents a spatial object and each column (field) describes a characteristic of that object
Two types of attribute data: textual or numerical
Attribute data is managed by relational database. It is a collection of tables (relations) that are defined for each class of objects describing the same subject
Allows to organize, update, and interrogate data of different subjects
Each table can be managed separately from other tables, but can be connected when needed (i.e. for queries)
There are two types of attribute tables in ArcGIS:
Feature attribute tables: has access to the spatial data and uses a FID to link the spatial data with the attribute data
Non-spatial attribute table: stores additional information and has one field in common with the feature attribute table
The connection between tables is made though a key (i.e. an ID), which is a common field whose values can uniquely identify a record in a table. They cannot be linked through the FID.
Types of relationship between tabular data
One-to-One relationship
One-to-Many relationship
Many-to-One relationship
Many-to-Many relationship
There are 4 measurement levels associated with attribute data:
Ratio - has an absolute 0
Interval - distance between numbers is meaningful
Ordinal - can be ordered
Nominal - only named variables
Level | Summary | Possible Operations | Statistics | Examples |
|---|---|---|---|---|
Nominal | Categories only. Data cannot be arranged into an ordering scheme | =, <, > | Counting : mode, amplitude | Name, State, gender, color |
Ordinal | Categories are ordered, but differences can’t be found or are meaningless | <, >, =, <> | Median, quartile | Type of car (compact, mid- size, full-size) |
Interval | Differences are meaningful, but there is no natural zero starting point and ratios are meaningless | <, >, =,<>, +, -, x, / | Mean, variance, correlation, etc. | Temperature |
Ratio | There is a __natural zero__starting point and ratios are meaningful | <, >, =,<>, +, -, x, / | Mean, variance, correlation, etc. | Computing distance |
Attribute analysis is done by spatial queries which search for and select a subset of features and table records. All query expressions in ArcGIS use SQL to formulate these search specifications. The purpose of this is to:
Explore the data
Focus on a data subset of interest
Basic structure in SQL (i.e. syntax) is: SELECT <column> FROM <table> WHERE <expression using map operators>
Logical operators: =, >, <, >=, <=, <>
Arithmetic operators: +, -, *, /, ^
Boolean operators: AND, OR, NOT, XOR
Mathematical functions (trigonometric functions (e.g. sin, tan), logarithms, etc.)
EXAMPLE: Select* (=all columns) From ContaminatedSites Where “Toxicity” > 8
Attribute data describes the characteristics of spatial features:
Each row (record) represents a spatial object and each column (field) describes a characteristic of that object
Two types of attribute data: textual or numerical
Attribute data is managed by relational database. It is a collection of tables (relations) that are defined for each class of objects describing the same subject
Allows to organize, update, and interrogate data of different subjects
Each table can be managed separately from other tables, but can be connected when needed (i.e. for queries)
There are two types of attribute tables in ArcGIS:
Feature attribute tables: has access to the spatial data and uses a FID to link the spatial data with the attribute data
Non-spatial attribute table: stores additional information and has one field in common with the feature attribute table
The connection between tables is made though a key (i.e. an ID), which is a common field whose values can uniquely identify a record in a table. They cannot be linked through the FID.
Types of relationship between tabular data
One-to-One relationship
One-to-Many relationship
Many-to-One relationship
Many-to-Many relationship
There are 4 measurement levels associated with attribute data:
Ratio - has an absolute 0
Interval - distance between numbers is meaningful
Ordinal - can be ordered
Nominal - only named variables
Level | Summary | Possible Operations | Statistics | Examples |
|---|---|---|---|---|
Nominal | Categories only. Data cannot be arranged into an ordering scheme | =, <, > | Counting : mode, amplitude | Name, State, gender, color |
Ordinal | Categories are ordered, but differences can’t be found or are meaningless | <, >, =, <> | Median, quartile | Type of car (compact, mid- size, full-size) |
Interval | Differences are meaningful, but there is no natural zero starting point and ratios are meaningless | <, >, =,<>, +, -, x, / | Mean, variance, correlation, etc. | Temperature |
Ratio | There is a __natural zero__starting point and ratios are meaningful | <, >, =,<>, +, -, x, / | Mean, variance, correlation, etc. | Computing distance |
Attribute analysis is done by spatial queries which search for and select a subset of features and table records. All query expressions in ArcGIS use SQL to formulate these search specifications. The purpose of this is to:
Explore the data
Focus on a data subset of interest
Basic structure in SQL (i.e. syntax) is: SELECT <column> FROM <table> WHERE <expression using map operators>
Logical operators: =, >, <, >=, <=, <>
Arithmetic operators: +, -, *, /, ^
Boolean operators: AND, OR, NOT, XOR
Mathematical functions (trigonometric functions (e.g. sin, tan), logarithms, etc.)
EXAMPLE: Select* (=all columns) From ContaminatedSites Where “Toxicity” > 8
