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 floating-point 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 Stores numbers between -32,768 to 32,767 Size on hard disk: 2bytes Applications: Numeric values without fractional values within specific range; coded values

Numeric data types Long integer Stores number s from -2,147,483,648 to 2,147,483,647 Size on disk: 4bytes Applications: Numeric values without fractional values within specific range

Numeric data types Single-precision floating-point number (float) Stores numbers approximately from -3.4 X 1038 to 1.2 X 1038 Size on disk: 4bytes Application: Numeric values with fractional values within specific range

Numeric data types Double-precision floating-point number (double) Stores numbers approximately from -2.2X10 308 to 1.8X10308 Size on disk: 8bytes 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 Owner Zoning P101 Wang Residential (1) Chang P102 Smith Commercial (2) Jones P103 Costello P104 a. FLAT FILE ZONING b. HIERARCHICAL 1 2 P101 P104 P102 P103 Wang Chang Smith Smith Jones Costello

database model c. Network Zoning Owner 1 2 Wang Chang Smith Jones Costello P101 P102 P103 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 Acres Zonecode P101 1-10-98 1.0 1 P102 10-06-68 3.0 2 P103 3-07-97 2.5 P104 7-30-78 Primary key Zonecode Zoning 1 Residential 2 Commercial Foreign key