Gov 1008 Introduction to Geographical Information Systems

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1 Gov 1008 Introduction to Geographical Information Systems Lecture 5: Creating Data and Maintaining Databases Sumeeta Srinivasan References include: Bolstad; Worboys; NCGIA Core Curriculum: csiss.org/learning_resources/content/giscc/giscc_contents.html; Longley et al;

2 Recall: Data is key GIS Tools Graphical manipulation software Data Base Management System Spatial data Attribute data ID Coordinates ID attributes 1001 (x1,y1) 1001 John 1002 (x2,y2) 1002 David

3 Stages in Database Design

4 Definitions A database is a collection of files, an integrated set of data on a particular subject A file is a collection of records A record is a set of items An item is a description of an object or an event Items, records, and files are usually linked according to some well defined structure

5 Database Management System (DBMS) DBMS is a Database (collection of files), and the associated Programs that operate on the files An organizational structure supporting the files and their use Typically provides: Backup/recovery Transaction management Retrieval Manipulation Data definition

6 Basic DBMS Functions Query and search: search database to answer user s question Sort: reordering the data in a particular way Updates: attributes change through time Join: combine two a more tables according to a primary key Verification: example if you enter 110 for percentage data, the computer won t accept the data reduce errors Applications CASE tools Forms builder Reportwriter Internet Application Server Programmable API

7 Role of DBMS

8 How to Create a Database?: Step 1: Investigation 1. To identify the characteristics of data to be managed 2. Whether the data is numerical, or nominal or categorical numerical: income, travel cost, travel time categorical: gender, ethnicity nominal: name, ID# 3. Data quality and quantities 4. Who are the users? Single user PC based or multiple user workstation based? User knowledge level?

9 Step 2: Data Model A data model is central to a DBMS. It is the conceptual model that represent the relationship between the characteristics of entities and its attributes For example: For a household survey database two options 1. Separate households into: Location Street Address 2. Put all households together and treat Location, Street Address as information associated with the household

10 Step 3: Database design Creating the structure of a database depending on the software available: 1. Should we refer to every household member by their names? 2. Should we refer every household member by birth-date? 3. Decisions on type of variables: numerical: data range (minimum to maximum) to assign memory blocks (bytes) character: number of characters needed

11 Step 4: Database implementation

12 Database Architecture Strategy Centralized Database all database components reside at a single computer all data can be accessed remotely Distributed Database database located in different places: current trend database components are connected through networks e.g. the university branch each maintains a separate database, yet it is connected to all branches

13 Types of DBMS Model Hierarchical Network Relational - RDBMS Object-oriented OODBMS Object-relational - ORDBMS

14 Relational Data Model A collection of data items organized as a set of formally-described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables

15 Relational DBMS Most popular type of DBMS Over 95% of data in DBMS is in RDBMS Commercial systems IBM DB2 Informix Microsoft Access Microsoft SQL Server Oracle Sybase

16 Attribute-Based Operations Entities Attributes Entities Attributes Operations

17 ER Model The entity relationship model is a conceptual data modeling technique where An entity type represents a collection of similar objects An entity instance is an occurrence of a particular entity An attribute type is a property associated with an entity An attribute type that serves to uniquely identify an entity type is called an identifier Identifiers are usually underlined entity type attribute type identifier Worboys and Duckham (2004) GIS: A Computing Perspective, Second Edition, CRC Press

18 ER Diagrams Entity types are connected using relationships A relationship type connects one or more entity types A relationship occurrence is a particular instance of a relationship Relationships may have their own attributes independent of entities Entity, attribute, and relationship types are shown in an entity relationship diagram (E-R diagram) relationship type Worboys and Duckham (2004) GIS: A Computing Perspective, Second Edition, CRC Press

19 Extended ER Model An entity type E 1 is a subtype of E 2 if every occurrence of E 1 is also an occurrence of E 2. In this case, E 2 is a supertype of E 1 The operation of forming subtypes is called specialization; the inverse operation of forming supertypes is called generalization For specialization (and conversely for generalization) A subtype has the same identifying attribute(s) as the supertype A subtype has all the attributes of the supertype, and possibly some more A subtype enters into all the relationships in which the supertype is involved, and possibly some more. Subtypes and supertypes are organized into an inheritance hierarchy Worboys and Duckham (2004) GIS: A Computing Perspective, Second Edition, CRC Press

20 Table Column = property Table = Object Class Row = object Object Classes with Geometry called Feature Classes

21

22 Joining Tables

23 Relation Rules (Codd, 1970) Only one value in each cell (intersection of row and column) All values in a column are about the same subject Each row is unique No significance in column sequence No significance in row sequence

24 Normalization Process of converting tables to conform to Codd s relational rules Split tables into new tables that can be joined at query time The relational join Several levels of normalization Normalization creates many expensive joins De-normalization is OK for performance optimization

25 Relational Join Fundamental query operation Occurs because Normalization Data created/maintained by different users, but integration needed for queries Table joins use common keys (column values) Table (attribute) join concept has been extended to geographic case

26 Object Oriented Data Model An Object Oriented model uses functions to model spatial and non-spatial relationships of geographic objects and the attributes. An object is an encapsulated unit which is characterized by attributes, a set of orientations and rules. An object oriented model has the following characteristics. 1. Generic properties: there should be an inheritance relationship 2. Abstraction: objects, classes and super classes are to be generated by classification, generalization, association and aggregation 3. Ad hoc queries: users can order spatial operations to obtain spatial relationships of geographic objects using a special language

27 Object Oriented Data Model example

28 Joining Tables Tables can be linked by a relational join A primary key of a table is linked to another key on another table Joins can be: one-to-one one-to-many many-to-one many-to-many

29 Types of Joins: Example 1 One to one Census block groups Transportation commute times by block group

30 Types of Joins: Example 2 Many to one Land use 1999 Lookup table for land uses

31 Types of Joins: Example 3 One to Many Towns Census Block Groups

32 Types of Joins: Example 4 Many to Many: Towns may have many types of crimes Same type of crimes may happen in many towns

33 Keys All attributes or sets of attributes that have the property of row uniqueness are candidate keys Primary keys should not repeat and should not have values that can have other interpretations Foreign keys do not assure uniqueness they define associations between tables

34 Key Example Many to one Land use 1999 Lookup table for land uses Primary Key Foreign Key

35 Some Operations between Tables Union All Intersection Only those in common Difference Only in first and not in second Join Joined by a common key

36 A B

37 Query Languages A query language is a computer language used in database management systems to retrieve, add, modify, or delete data SQL (Structured Query Language) is a standard language used with relational databases to build complex logical expressions to access data RQBE (Relational Query by Example) is a simpler method of describing a query and is facilitated by the software

38 Examples

39 SQL Query SELECT * FROM Off WHERE Context = BURGLARY ORDER BY Crnumber;

40 GIS RQBE

41 Result

42 Spatial SQL Query: List the ID, population, and area of each block group listed in a table with data about census block groups (B) SELECT B.ID,B.Pop, Area(B.Shape)AS "Area" FROM B Query: Find the names of all blockgroups which are neighbors of the Blockgroup which includes 808 Comm Ave in the table SELECT B1.Name AS "Neighbors of 808" FROM B1, B2 WHERE Touch(B1.Shape,B2.Shape)=1 AND B2.Name = 808 Comm Av Block group

43 Spatial Relations Equals same geometries Disjoint geometries share common point Intersects geometries intersect Touches geometries intersect at common boundary Crosses geometries overlap Within geometry within Contains geometry completely contains Overlaps geometries of same dimension overlap Relate intersection between interior, boundary or exterior

44 Structuring a Database Conceptual User view Define objects and relationships Geographic representations Logical Match objects to GIS supported data types Organize geographic database structure Physical Define database schema SQL with geographic extension

45 Structuring Geographic Information Topology Normalized Physical (on-the-fly topology) Indexing Grid Index, Quad Tree Index, etc

46 Normalized Database Topology Model

47 Physical Database Topology Model

48 Indexing Used to locate rows quickly RDBMS use simple 1-d indexing (R-tree, B-tree, etc.) Spatial DBMS need 2-d, hierarchical indexing Grid Quadtree R-tree Others Multi-level queries often used for performance (MBR)

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