Transcript No Slide Title

Specific Steps in Data Modeling
(1) Conceptualize the user's view of data
– what are the basic features needed to solve the
problem?
(2) Select the geographic representation
– points, lines, areas, rasters, TINs
(3) Define objects, features, and relationships
– draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements
– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
( 1 ) User’s View of Data
( 1 ) User’s View of Data cont.
(2)
Select
geographic
rep.
Steps in Data Modeling
(1) Conceptualize the user's view of data
– what are the basic features needed to solve the
problem?
(2) Select the geographic representation
– points, lines, areas, rasters, TINs
(3) Define objects and relationships
– draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements
– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
Unified Modeling Language
• Entity-relationship diagrams
• Design methodologies, diagram
notations
• UML
– Not a design methodology
– Just a diagrammatic notation based on methods
– Endorsed by leading software and database
companies
• HTML
Unified Modeling Language
UML
• Diagrammatic notation = “visual
language”...
• For constructing a data model
– Explains, documents on object-oriented structure
• Drawings, relationships constructed in
Visio
– Like CAD for Civil Engineering
• Tools to input a drawing to ArcGIS
– input data to the data model
Basic UML Grammer
• Things
– “Classes” sometimes grouped in “Packages”
• Relationships
• Diagrams
UML Things
UML Notation
Zeiler pp. 97-99
• a class is shown as a
box
• top part contains the
name of the class
• lower part contains
the attributes
• methods associated
with the class
• lines connect boxes
and indicate
relationships
UML Notation ( cont. )
• Abstract class
– specify subclasses
underneath
– Mammals w/human or
dog feature classes
– no new instances
• Feature Class
– Specify subtypes
underneath
– Human, dog, cat
Example: Chicken Object Model
Graphic courtesy of Maidment et al., ArcHydro team
Objects and Features
• Object (real world)
– in ArcGIS an object is non-spatial
– it is NOT a point, line, or area
– it has no geographic location
– it has no shape attribute in its table
– Drainage network, ship, vehicle, … customer,
lake, house, etc.
• Feature (spatial context)
– an object that has geographic location
– a point, line, area, TIN, raster
Relationships
• Links between
classes, shown as
lines
• One to one
• One to many
• Many to many
Relationships (cont.)
• 1:1 - solid line
– one record in Class A linked to one record in
Class B
• “is married to”
• the class of state capitals linked to the class of
states
• 1:n - solid line with * at one end
– one record in Class A linked to any number of
records in Class B
• "owns"
• the class of states linked to the class of area codes
Relationships (cont.)
• m:n - solid line with * at both ends
– any number of records in Class A linked to any
number of records in Class B
• "has visited”
• "was never married to"
• the class of mountain lions linked to the class of
wilderness areas
Graphic courtesy of Maidment et al., ArcHydro team
Type Inheritance
• White triangle
• Class B inherits the
properties (attributes,
methods) of Class A
• the class street inherits
from the class
transportation network
• Solid diamond
• the parts and the whole
depend on each other
Graphic courtesy of Maidment et al., ArcHydro team
InstantaneousPoint (ex: CTD)
Michael Blongewicz
X
InstantaneousPoints
MarineID
1
2
3
MarineCode
AAA
BBB
CCC
SeriesID
1
1
1
IPointType
1
1
1
RecordedTime
05/04/58 12:00 00
05/04/58 12:30 00
05/04/58 13:00 00
TimeStamp
Y
Measurement
MeasureID
1
2
3
4
5
MarineID
1
1
1
2
2
ZLoc
-0.8
-1.5
-3.5
-0.8
-1.5
Xloc
Yloc
ServiceTrip
SeviceDesc
Measurement
MeasuringDevice
MeasuringDevice
MDeviceID
1
2
3
4
5
Name
Bob
Poncho
Juanita
Mia
Anita
MeasuredType
MTypeID
VarName
1
2
3
4
5
Type
VarDesc
MeasurementID
1
1
1
2
2
VarUnits
Oranges
Bananas
Cubic cm
Rocks
Limes
Z
MDeviceID
1
1
2
2
3
MeasuredData
MDeviceID
1
1
1
1
1
East
12.1
11.3
9.3
14.0
7.3
North
10.8
12.5
-3.5
15.1
12.0
Speed
8.6
7.9
7.5
3.9
9.1
Direction
121
220
130
234
115
ArcMarine Geodatabase
Overall Geodatabase
Feature
Class
Feature Class
Feature Dataset
Table
Relationship
Class
Steps in Data Modeling
(1) Conceptualize the user's view of data
– what are the basic features needed to solve the
problem?
(2) Select the geographic representation
– points, lines, areas, rasters, TINs
(3) Define objects and relationships
– draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements
– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
Data Model Levels
Humanoriented
Reality
Conceptual Model
Increasing
Abstraction
Logical Model
Computeroriented
Physical Model
Modeling Process
Conceptual Model
Lists, flow diagrams, etc
Real World
Objects and
relationships
Logical Model
Diagram in
CASE Tool
Physical
Model
Database
Schema
(Object state)
Graphic courtesy of ESRI
Steps in Data Modeling
(1) Conceptualize the user's view of data
– what are the basic features needed to solve the
problem?
(2) Select the geographic representation
– points, lines, areas, rasters, TINs
(3) Define objects and relationships
– draw a UML diagram, specify relationships,
“behaviors”
(4) Match to geodatabase elements
– Refine relationships, “behaviors”
(5) Organize geodatabase structure, add data
– e.g., Marine Data Model tutorial
Arc Marine Data Model Exercise
• Exercise and data at
dusk.geo.orst.edu/djl/arcgis/ArcMarine_Tutorial/
• What to turn in:
– Screen snapshot of what your ArcMap session looks like
at the end of Section 4 (including dynseg referencing)
– Answers to 2 simple questions at end of Section 4 (which
cruise? which vehicle?)
– Can put all of the above in a single MS-Word document,
labeled with your NAME please!
• Due in Dropbox, May 3rd, 6:00 p.m.
Gateway to the Literature
•
•
•
•
Arctur, D. and Zeiler, M., 2004, Designing Geodatabases, ESRI Press
Lowe, J.W., 2003. Flexible data models strut the runway. Geospatial
Solutions, 13(2): 44-47.
Maidment, D.R., 2002. Arc Hydro: GIS for Water Resources, ESRI
Press, 203 pp. w/CD.
Li, X. and M.E. Hodgson, 2004. Vector field data model and operations.
GISci. Rem. Sens., 41(1): 1-24.
• Wright, D., Blongewicz, M., Halpin, P., and Breman, J., A new
object-oriented data model for coasts, seas, and lakes, in Green,
D.R. (ed.), Coastal and Marine Geospatial Technologies, London:
Springer, in press.
•
– dusk.geo.orst.edu/djl/arcgis/coastgis_book_final.pdf
Wright, D.J., Halpin, P.N., Blongewicz, M.J., and Breman, J.B.,
Arc Marine: GIS for a Blue Planet, Redlands, CA: ESRI Press, in
prep and review, due out 2006/7.
– dusk.geo.orst.edu/djl/arcgis/book
Resulting Analysis - ArcHydro
From Arctur and Zeiler, Geodatabase Design, ESRI Press.