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Geog. 314
Working with tables
Introduction
• GIS involves both spatial and
attribute data
• Spatial data is concerned with the
geometry (position & shape) of map
feature
• Attribute data describe a
characteristic of map feature
(colour, name, size, type, etc)
• Attribute data are stored in tables
Introduction
• Two types of vector data models:
• Georelational data model (dominant in
GIS) stores spatial and attribute data
separately and links them using the
feature ID. Before any analysis can be
performed , you must synchronize the two
datasets
• Object oriented data model combines the
spatial and attribute data in a single
database. Here each map feature has a
unique object ID and an attribute to store
its geometry.
Tables & Attribute data
• Tabular information is the basis of
geographic features. They allow you
to perform the following tasks:
• visualize
• Query
• analyze your data
Organization of Attribute data
• tables are made up of rows and
columns, and all rows have the
same number of columns
• Each row of a table represents a
map feature
• Each column represent a
characteristic
Organization of Attribute data
• rows are known as records or tuples
• columns are fields or items
• Each field can store a specific type of
data, such as a number, date, or piece
of text, etc
• Attribute tables are called feature
attribute tables (point attribute table
(PAT), arc attribute table (AAT), polygon
attribute table (PAT)
Organization of Attribute data
• Attribute data are managed using DBMS
• A database management systems
(DBMS) is a set of computer programs
for managing an integrated and shared
database (Laurini and Thompson, 1992)
• DBMS provide tools for data input,
search, retrieval, manipulation, and
ouput
Types of attribute data
• We can classify attribute data by (data type &
measurement scale
• Data type
- character or string, number (integer, float,
double), date, etc
• Measurement scale
- categorical (nominal &ordinal) and numeric
(ratio & interval)
• relationship between measurement scale
and data type
- ordinal and nominal – character strings
- interval & ratio – integer and real numbers
data types
• Numbers: Can be one of four numeric data types:
short integers, long integers, single-precision floatingpoint numbers (often referred to as floats) and
double-precision floating-point numbers (commonly
called doubles)
• Text or string: for storing textual or alphanumeric
data
• Date: storing date and time
• BLOB: Object linking and embedding (OLE) objects are
objects created in other applications that are linked
or embedded in Access. In this case, binary large
object (BLOB) and GEOMETRY data types don't exist
in Access, so the object is in ArcGIS and linked to the
Access database.
Numeric data types
• Short integer
I. Stores numbers between -32,768 to
32,767
II. Size on hard disk: 2bytes
III.Applications: Numeric values
without fractional values within
specific range; coded values
Numeric data types
• Long integer
I. Stores number s from -2,147,483,648
to 2,147,483,647
II. Size on disk: 4bytes
III. Applications: Numeric values without
fractional values within specific range
Numeric data types
• Single-precision floating-point
number (float)
I. Stores numbers approximately
from -3.4 X 1038 to 1.2 X 1038
II. Size on disk: 4bytes
III. Application: Numeric values with
fractional values within specific
range
Numeric data types
• Double-precision floating-point
number (double)
I. Stores numbers approximately
from -2.2X10 308 to 1.8X10308
II. Size on disk: 8bytes
III. Application: Numeric values with
fractional values within specific
range
database model
• A database is a collection of interrelated tables in
digital format.
• Four types of databases:
• Flat file: contains all data in a large table (e.g.
feature attribute table)
• Hierarchical: organizes the data at different levels
and uses only the one-to-many associations
• Network: builds connections across tables
• Relational: a collection of tables (also called
relations) which can be connected to each other
by keys
database model
PIN
P101
a. FLAT P101
FILE
P102
P102
P103
P104
Owner
Wang
Chang
Zoning
Residential (1)
Residential (1)
Smith
Jones
Costello
Smith
Commercial (2)
Commercial (2)
Commercial (2)
Residential (1)
ZONING
b. HIERARCHICAL
P101
Wang
Chang
1
2
P104
Smith
P102
Smith
P103
Jones
Costello
database model
c. NETWORK
Zoning
1
2
Owner
Wang
P101
Chang
P102
Smith
Jones
P103
Costello
P104
d. RELATIONAL
Zoning
Owner
PIN
Zonecode
P103
N.B: a problem hierarchical and network data model is the linkages b/n
tables must be known in advance and built into the computer code
Keys of relational databases
• Primary keys: represents one or more
attributes whose values can uniquely
identify a record in a table
• Foreign keys: a counterpart of primary key
in another table (i.e. the destination table)
• In the parcel and zoning tables below, the
key to connect the two is zone code.
• Note: the key fields may have different
names but must be of the same data type
and contain the same kind of info.
Primary and foreign keys
PIN
Sale
Date
1-10-98
10-06-68
3-07-97
7-30-78
P101
P102
P103
P104
Foreign key
Acres Zonecode
1.0
3.0
1
2
2.5
1.0
2
1
Zonecode
1
Zoning
Residential
2
Commercial
Primary key