Conceptual Design
Data design
The key data element of address dataset
that would be logically linked with community facility table would be EZI_ADD.
The reason this element is crucial is because EZI_ADD is used to geocode the
facility address. For this linkage to be successful, the addresses of the
community table must be identical of format and address representation.
The minimum map area is 0.01 hectares,
based on CCD .The error tolerance for this project is 10%, to match the error
tolerance of dataset’s positional accuracy. The map scale desired for the
project would be 1: 1000. The map projection that should be employed for the
project area is MGA Zone 55 as this projection minimizes distortions for the
region. Temporal resolution would be every year to cater annual needs of the
city.
Data sources for this information
product come from DSE (public source). The lineage of address dataset starts
from derivation from address information found in Vicmap Property and Vicmap
transport. The addresses were later analysed and categorised and channelled the
results to address dataset. This address dataset has address match rate of 92%
(2008/09). The data standard I will employ in this project would be ANZLIC
Metadata Product Guidelines VER 1.2 July 2011. The reason I chose this standard
is because the metadata format for the DSE datasets are based on this and
applying the same standard would fasten the process of writing product
description. Since the datasets found are readily available in ESRI shapefiles,
there will no need for data format conversion.
Logical Data Model
Most or all the dataset structure for
the project would be vector-based. Below-here is an example the characteristics
of vector transportation dataset.
Fields
|
Data
Type
|
FID
|
Object
ID
|
Shape
|
Geometry
|
PHYS_COND
|
Text
|
ROTATION
|
Float
|
ROAD_REL
|
Text
|
FTYPE_CODE
|
Text
|
CRDATE_PFI
|
Date
|
PFI
|
Long
Integer
|
NAME
|
Text
|
The suitable structure for the data is
object-relational data model. It allows addition of specialized behaviour to
the relational data model which is close to real world behaviour.
The advantages of this model would be it
maintain high data integrity, multiple users are able to update simultaneously
and allows use of legacy and GIS databases. For the project, this model is
chosen because ArcGIS software uses this model and it allows wide range of
relational and objects rules to be applied. Disadvantages would be it is
compromise of two previous models and difficulty of modelling complex
relationships.
For attributes to be linked with the administrative
dataset, the geo-relational data model is most appropriate model for storage
and manipulation of the data. This is because the parcel boundaries are able to
be linked easily with other tables containing data of population
characteristics.
The model (incorporating relational and
objected orientated models) allows relational data model to have
object-orientated extensions. This means various relational and
object-orientated rules are applicable which are needed for the project dataset
(parcel layers and network datasets). Secondly, its ability to allow multiple,
simultaneous updates would maximise GIS analyst working efficiency. For
example, one GIS analyst would be using series of datasets to analyse
accessibility to clinics while another analysts would use the same datasets for
another analysis.
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