1. Geography 463 GIS Workshop
April 10, 2006

2. Outlines Project management principles Issues in system requirements
Consider issues intrinsic to spatial data
Choose a logical data model
UML Class Diagram

3. Project management principles
Part I.
Project management principles

4. What is project? What is not?
Projects
Ongoing operations
Definite beginning and end
No definitive beginning and end
Temporary in nature
Ongoing
Produces a unique product or service
Produces the same product or service over and over
Ending is determined by specific criteria
Processes are not completed

5. The Triple Constraint Every project is constrained by its:
Scope: what’s included and what’s not
Schedule: anticipated time to complete goals
Cost: budget allocated for project completion
Project manager’s primary duty is to balance these competing constraints, while satisfying intended business need

6. The Triple Constraint of Project Management
System requirements report helps you define the scope, cost, and timing constraints in advance.
The image is retrieved from Tom Nolan’s lecture note

7. Issues in system requirements
Part II.
Issues in system requirements

8. System requirements and project management
Can be thought of as implementation plan that allows the triple constraints to be recognized and balanced given information products identified from needs assessment report
System requirements report will be composed of
Data requirement
Software requirement
Hardware requirement
Staffing requirement
Timing requirement

9. Master Input Data List How is MIDL useful?
Help you recognize requirements for data, software, hardware, staffing, and timing.
Data: accuracy, data ready? Options for putting data into system (Buy? Outsourcing? In-house data creation?)
Software: which functions are needed to put data into system?
Hardware: decision on which workstation purchase is determined by data volume and computing complexity ….
From p. 88 in Tomlinson (2005)

10. Data availability vs. data readiness
Data availability: the date on which you can receive data from its source
Data readiness: the date on which the data is in your system, processed, and ready for use in the creation of an information product
Identify functions needed to put data available into the system (data readiness)
Examples: to be ready for the system
Satellite image requires file transfer and ID creation
Paper map requires scanning, digitizing, topology editing, attribute editing, and so on
Digital data would require a very little work

11. Priorities Help you manage the scope of projects
What are important and what are less important information products and data?
Occurs due to time/cost constraints
This decision will be affected by the organization’s strategic plan/goals, thus consultants are not usually invited for this process

12. Before you estimate timing requirements, consider
Data input timing
Various options for putting data into system will affect timing
Information product application programming timing
Any scripting effort, what are steps involved? Required work hours?
System acquisition timing
Some hardware should be purchased/waited
Training and staff issues
Any training need?
Make the use of existing staff or hire new persons

13. Consider issues intrinsic to spatial data
Part III.
Consider issues intrinsic to spatial data

14. Choosing the appropriate map projection
Intended uses of information products
Be aware of distortion of geometric properties (e.g. area, direction, distance) due to map projections
Geographic area of interest
Location of standard line/parallels
Difference in datum?
e.g. NAD27 vs. NAD83
Difference in measurement units?
e.g. SPC vs. UTM

15. Choosing the appropriate map scale
The appropriate map scale can be chosen based on resolution and error tolerance
Resolution: the minimum amount of detail that can be mapped at a given scale; related to data requirements for information products
Error tolerance: how much do your clients tolerate error? related to cost
See p. 115 for the matrix for the choice of map scale

16. Topology editing Arc/info coverage Shapefiles Geodatabase
Stored in feature attribute table
Use BUILD/CLEAN command
Shapefiles
Non-topological model
Geodatabase
Topological rules are assigned to feature data set
Topological rules within/between feature class can be defined
Use topological editing tool; help you identify potential topological errors given predefined rules

17. Choose a logical data model
Part IV.
Choose a logical data model

18. Relational A collection of table (simple, ad-hoc)
Table (entity) has attributes
The relation between tables is created through a common attribute (remember how you perform table join?)
Logical linkage: which keys needed?
Most common logical model in GIS as well as hybrid form (file for features + relational table for attribute): e.g. arc/info coverage, shapefile

19. Object-oriented A collection of object (complex, natural)
Object has attributes and operations
Class is a collection of similar objects
Database can be built using class hierarchy (e.g. some attributes of city database can inherit from supper class such as spatial objects)
Model complex relationships
Association: any
Aggregation: weak form of whole-part relation
Composition: strong form of whole-part relation
Generalization: (e.g. secretary and employee)

20. Object-relational Compromise between relational model and OO model
Extend relational data model so that good thing about OO (e.g. complexity, integrity) can be incorporated
Maintain table with abstract data type
Can use SQL
E.g. Geodatabase

21. Choosing a logical data model
Given continuous popularity of relational data model, relational data model can support the information products that involves a simple conceptual design
If database requires handling of complex relationship, integrity and versioning, OO or OR will work better (e.g. facilities management)
See p. 145 for which logical data model is suggested given data modeling situation

22. Part V.
UML Class Diagram

23. What is UML? Acronym for Unified Modeling Language
Standardized efforts that combine many years’ work on object-oriented analysis and design
Use graphic notations (e.g. diagram)
Intuitive; somewhere between natural language and programming language
Anything to do with project management? Yes, user requirements modeling, planning, system design, database design, and so on whose tasks can be chosen from different kinds of diagram

24. Class Diagrams Associations Physical location (e.g., is next to)
Direct actions
(e.g., drives)
Communication
(e.g., talks to)
Ownership
(e.g., has)
Satisfaction of a
condition
(e.g., works for)

25. Class Diagrams
Association class
Aggregation

26. Class Diagrams
Generalization / Inheritance

27. Class Diagrams Class name Attributes Operations aggregation
association
generalization

28. UML Resources Software to use in the department
Microsoft Visio or other drawing tools
ESRI’s “Building Geodatabases with Visio”
IBM Rational Rose literature on design w/ UML
Introduction to UML
Entity-relationship modeling with UML
UML tutorials on the web