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Lecture-8-The-GIS-Database-Part-1.ppt
- 1. The GIS Database Chapter8 – Part 1 Lecture 8 1
- 2. Entity Bangor – Penobscot County, Maine, UnitedStates – Centroid - 44.801N , -6778W – Area 34.4 square miles – Elevation – 158 feet – Population 31,473 Lecture 8 2
- 3. What is adatabase? A database is any organized collection of data. Some examples common examples: – a telephone book – T.V. Guide – airline reservation system – motor vehicle registration records – papers in your filing cabinet – files on your computer hard drive. Lecture 8 3
- 4. Database Definitions What isa database? It’s an organized collection of data, it need not be a computer based system. What is a database management system (DBMS)? A software system designed to: – Organize that data in a flexible manner, – Provide tools to add, modify or delete data from the database, – Query the data, – Produce reports summarizing selected contents. Lecture 8 4
- 5. What is theultimate purpose of a database management system? Data Information Knowledge Action Is to transform Lecture 8 5
- 6. Features of aDBMS Database Management Systems provide features to maintain database: – Data independence - It refers to the immunity of user applications to make changes in the definition and organization of data. – Integrity and security - refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle Lecture 8 6
- 7. Features of aDBMS Database Management Systems provide features to maintain database: – Transaction management - A transaction comprises a unit of work performed within a DBMS against a database, and treated in a coherent and reliable way independent of other transactions. Transactions in a database environment have two main purposes: • To provide isolation from other transactions. • To have an “all or nothing” effect. Transactions must pass the ACID test (atomic, consistent, isolated and durable Lecture 8 7
- 8. Features of aDBMS Database Management Systems provide features to maintain database: – Concurrency control - ensures that correct results for concurrent operations are generated, while getting those results as quickly as possible. – Backup and recovery – Provides a language for the creation and querying of the database. – A language for writing application programs Lecture 8 8
- 9. Selecting a Database ManagementSystem Database management systems (or DBMSs) can be divided into two categories: – Desktop databases are oriented toward single-user applications and reside on standard personal computers (hence the term desktop). – Server databases contain mechanisms to ensure the reliability and consistency of data and are geared toward multi-user applications. Lecture 8 9
- 10. Relational Databases • Therelational database model is the most dominant model in both the corporate and GIS world, due to its flexibility, organization, and functioning.. • It was defined by Edgar F. Codd (1970). • It can accommodate a wide range of data types. • It is not necessary to know beforehand the types of processing that will be performed on the database. Lecture 8 10
- 11. Relational Database Terminology •Each table contains the data for a single entity. • Each instance of an entity is a row/record/tuple in the table. This is a specific instance of the entity. • Columns contain attributes/fields that describe the entity. – Attributes in a column must be from the same domain (text, integer, date). – An attribute may have a range (e.g.; 0 ≤ integers ≤ 100) – Column order has no significance. • Tables are related through keys. Lecture 8 11
- 12. Attributes • An entityis represented by a set of attributes, that is descriptive properties possessed by all members of an entity set. Domain – the set of permitted values for each attribute • Attribute types: – Simple and composite attributes. – Single-valued and multi-valued attributes • E.g. multivalued attribute: phone-numbers – Derived attributes • Can be computed from other attributes • E.g. age, given date of birth Lecture 8 12
- 13. Relational Database Terminology Lecture8 13 Record, row, tuple A specific instance of the entity Attribute, column Entity
- 14. Keys • A superkey of an entity set is a set of one or more attributes whose values uniquely determine each entity. • A candidate key of an entity set is a minimal super key – Customer-id is candidate key of customer – account-number is candidate key of account • Although several candidate keys may exist, one of the candidate keys is selected to be the primary key. Lecture 8 14
- 15. Super Key Lecture 815 ID, RollNumber, RegNo, Name, Place, Standard ID, RegNo, Name RegNo, Name, Place, Standard RollNunmber, Name Place ID, Place RegNo
- 16. Candidate Keys Lecture 816 ID RollNumber RegNo
- 17.
- 18. Keys • A compositekey/concatenated is a key with more than one attribute. Lecture 8 18 http://ecomputernotes.com/images/Composite%20Key.jpg
- 19. Keys • A foreignkey is an attribute that is a key of one or more relations other than the one in which it appears. Lecture 8 19
- 20. Foreign Key Primary KeyForeign Key Primary Key Foreign Key Primary Key Foreign Key 20 Lecture 8
- 21. Keys • Given theimportance of keys, there are usually some restrictions on them: e.g., null values are not allowed. • Keys are also used to index a database. – Too few keys may result in difficulty in searching and sorting the database. Lecture 8 21
- 22. Physical Database Structure Thephysical design of the database specifies the physical configuration of the database on the storage media. – This includes detailed specification of data elements, data types, indexing options and other parameters residing in the DBMS data dictionary. – It is the detailed design of a system that includes modules & the database's hardware & software specifications of the system. Lecture 8 22 https://en.wikipedia.org/wiki/Database_design
- 23. Logical Database Structure •Several logical data structures are used to express the relationships between individual data elements or records in a database. • Common logical data structures are hierarchical, network, and relational, with relational being predominant. Lecture 8 23
- 24. Conceptual Structure • Theconceptual structure is often represented as a schema. • A schema describes the database structure in a shorthand notation. • One example is the entity-relationship (ER) diagram. Lecture 8 24
- 25. Entity Relationship Diagram ENTITY RELATIONSHIP ATTRIBUTE Rectanglesrepresent entity sets. Diamonds represent relationship sets. Lines link attributes to entity sets and entity sets to relationship sets. Ellipses represent attributes Double ellipses represent multivalued attributes. Dashed ellipses denote derived attributes. Underline indicates primary key attributes. Lecture 8 25
- 26. Entity Relationship Diagram StudentEnrolls In Courses ID Name Address Phone Major Advisor Credits GPA Number Name Credits Time Room Instructor Lecture 8 26
- 27. Entity Relationship Model •The result is a diagram of all of the entities, their attributes, and the relationships between entities – Each entity becomes a table. • Student table • Course table – Each relationship (usually) becomes a table. • Enrolls, which allows you to join information from both tables. Lecture 8 27
- 28. Types of Relationshipsbetween Entities • 1:1 – one faculty member is assigned to one office. • 1:M (M:1) – one faculty member teaches many courses. • M:N – many students take many courses. • All of these relationships can exist between attribute tables. Lecture 8 28
- 29.
- 30. Table Joins • Tablejoins depend on the data not the attribute name. • There are many different types of table joins. • Tables can be joined regardless of the relationship EXCEPT: – When joining to the feature attribute table in a GIS, the relationship must be 1:1 or M:1 – Other relationships must use the relate. Lecture 8 30
- 31. One-to-One Join Employee-id Job 1Digislave 2 Useless Supervisor Employee-id name 1 Tom 2 John Join Employee-id to Employee-id After join Employee-id Job Name 1 Digislave Tom 2 Useless Supervisor John A join does not permanently alter the table structure Lecture 8 31
- 32. Many-to-One Join Symbol Description QaQuaternary Alluvium Qe Quaternary Eolian Pa Permian Abo Polygon Id Symbol 1 Qa 2 Qa 3 Pa 4 Qe Polygon ID Symbol Description 1 Qa Quaternary Alluvium 2 Qa Quaternary Alluvium 3 Pa Permian Abo 4 Qe Quaternary Eolian After Join on Symbol Lecture 8 32
- 33. Lecture 8 Relate ina GIS 33 https://courses.washington.edu/gis250/lessons/tables/images_av3/relate _table1.gif
- 34. Relational Algebra • Codd’sspecification of a relational database relied on relational algebra. • Relational algebra takes tables/relations as inputs and returns tables as outputs. • The algebra combines or splits tables by rows or by columns to generate either a subset of tables or an expanded tables. Lecture 8 34
- 35. Tables comprise thefundamental building blocks of any database. The table above contains the employee information for an organization -- characteristics like name, date of birth and title. Fundamental Building Blocks Lecture 8 35
- 36. Relational Algebra • Fivebasic operators – select: – project: – union: – difference: – – Cartesian product: x • The operators take one or two relations as inputs and produce a new relation as a result. Lecture 8 36
- 37. Relational Algebra • DerivedRelational operators – Intersection – Divide (not used very often) – Join • These can be expressed using different combinations of the fundamental operators. Lecture 8 37
- 38. Select Operation –Example Relation r A B C D 1 5 12 23 7 7 3 10 A=B ^ D > 5 (r) A B C D 1 23 7 10 Select from relation r where A=B AND D>5 Lecture 8 38
- 39. Database Queries • Queriesmay be made of one table or several tables at the same time. • In many systems querying is facilitated by icons, or menus, or queries by example (QBE – a graphical query language ). Lecture 8 39
- 40. Structured Query Language (SQL) •DDL – Data Definition Language; used to create and manage the database. • DDM – Data Manipulation Language; used to query the database. Lecture 8 40
- 41. SQL • SQL: widelyused non-procedural language – E.g. find the name of the customer with customer-id 192-83- 7465 select customer.customer-name from customer where customer.customer-id = ‘192-83-7465’ • Application programs generally access databases through one of – Language extensions to allow embedded SQL – Application program interface (e.g. ODBC/JDBC) which allow SQL queries to be sent to a database Lecture 8 41
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- 44.
- 45. The ArcGIS AttributeQuery Interface State’s Table is Open Lecture 8 45
- 46.
- 47. Options Related tables Select byattributes Switch selection Clear selection Zoom to selected Delete Selected Table is Open Lecture 8 47
- 48. No Table isOpen Selection- >Select by Attributes from the Menu Bar Lecture 8 48
- 49. A Spatial Queryin SQL SELECT city.name, city.geometry FROM city, county WHERE county.name=‘Penobscot’AND city.geometry INSIDE county.geometry city.population>30000; Lecture 8 49
- 50.
- 51. Spatial Data • Spatialdata has a structure that does not necessarily fit with tabular structure. • To construct a spatial object requires several table joins. • Spatial indexing is very different from the type of indexing used in a relational database. Lecture 8 51
- 52. Geometry Point Curve Surface LineStringPolygon MultiSurface Line LinearRing MultiCurve MultiPolygon MultiLineString Composed Type Relationship SpatialReferenceSystem GeometryCollection MultiPoint Spatial Types – OGC Simple Features Lecture 8 52
- 53. Standard GIS DataModel Linked spatial and attribute (tabular) data. Lecture 8 53
- 54. File-based Data Models •Coverages – Developed for workstation Arc/Info ~ 1980 – Complex structure, proprietary format – Attributes in Info tables • Shapefiles – Developed for ArcView ~ 1993 – Simpler structure in public domain – Attributes in dBase (.dbf) tables Geographic coordinates and attributes are stored in separate but linked files Arc Info Lecture 8 54
- 55.
- 56. Coverages and Shapefiles –Coverages are stored partially in their own folder and partially in the common INFO folder. – Shapefiles are stored in three to five files (with extensions .shp, .shx, .dbf, .sbx and .sbn). – Coverages store common boundaries between polygons only once, to avoid redundancy. – Shapefiles store all the geometry of each polygon regardless of redundancy. – Coverage features are single lines or single polygons. – Shapefiles allow features to have multiple, disconnected, intersecting and overlapping components. Lecture 8 56
- 57. Geodatabase Model • Storesgeographic coordinates as one attribute (shape) in a relational database table • Uses MS Access for “Personal Geodatabase” (single user) • Uses a file system for a “File Geodatabse” (FGDB). • Uses Oracle, Sybase, Ingress or other commercial relational databases for “Enterprise Geodatabases” (many simultaneous users) Lecture 8 57
- 58. • There aresome differences in queries between shapefiles and geodatabases – "STATE_NAME" LIKE 'Miss%' * in a geodatabase – "OWNER_NAME" LIKE '_atherine smith' ? – UPPER("LAST_NAME") = 'JONES' – UCASE ("LAST_NAME") = 'JONES' geodatabase – "POP2000" IS NULL – "POP2000" IS NOT NULL – "HOUSEHOLDS" > "MALES" * ("POP90_SQMI" + "AREA") Lecture 8 58
- 59. The ArcGIS Geodatabase Lecture8 59 Key Characteristics ArcSDE File Geodatabase Personal Geodatabase Number of Users Multiuser Single user & small workgroups Single userS Storage Format Oracle Microsoft SQL Server IBM DB2 IBM Informix Each dataset is a separate file Microsoft Access File Versioning Support Supported Not supported Not supported Database Administration Tools Full DBMS functions File system management Windows file system management
- 60. Elements of aGeodatabase Feature Dataset Feature Class Relationship Class Geometric Network Annotation Class Object Class Lecture 8 60
- 61. Elements of aGeodatabase • Objects , Object Classes • Features , Feature Classes • Feature Datasets • Validation Rules, Domains • Relationships , Relationship Classes • Spatial References • Geometric Networks Lecture 8 61
- 62. Objects and ObjectClasses • An object is an instance of an object class • All objects in an object class have the same properties and behavior • An object can be related to other objects via relationships Lecture 8 62
- 63. Attribute Object Object class Feature Feature class Relationship Relationshipclass Network Column, Field Row Table Row with geometry column Table with geometry column Row with two foreign keys Table with two foreign key columns Tables linking elements to features Relational view Object view Lecture 8 63
- 64. Features • Spatial object •Location • Attribute of type Geometry • Spatial relationships • Instance of a feature class Lecture 8 64
- 65. FeatureClasses • Same typeof geometry • Same type of spatial reference system • Store spatial objects (features) Lecture 8 65
- 66. Feature Datasets • Container •Same spatial reference • Analogous to a coverage Lecture 8 66
- 67. Assignment • Read Chapter8 • Problems: 1, 2, 4, 5, 9, 10, 11, 12, 15 Lecture 8 67