Course Title: Integrate spatial datasets

Part A: Course Overview

Program: C5237 Diploma of Spatial Information Services

Course Title: Integrate spatial datasets

Portfolio: SEH Portfolio Office

Nominal Hours: 60

Regardless of the mode of delivery, represent a guide to the relative teaching time and student effort required to successfully achieve a particular competency/module. This may include not only scheduled classes or workplace visits but also the amount of effort required to undertake, evaluate and complete all assessment requirements, including any non-classroom activities.

Course Code




Learning Mode

Teaching Period(s)


City Campus


130T Vocational Engineering


Term1 2009,
Term1 2010,
Term1 2011

Course Contact: Program Manager

Course Contact Phone: +61 3 9925 4468

Course Contact Email:

Course Description

This unit of competency specifies the outcomes required to integrate spatial datasets including linking spatial, aspatial and attribute data for the purpose of providing spatially referenced information. It requires the ability to apply theoretical spatial concepts to a range of situations in order to correctly identify and integrate the appropriate information. Functions would be carried out within organisational guidelines.

Pre-requisite Courses and Assumed Knowledge and Capabilities


National Competency Codes and Titles

National Element Code & Title:

CPPSIS5006A Integrate spatial datasets


2 Obtain spatial and attribute data.

3 Create resultant spatial dataset.

4 Link spatial and attribute data.

5 Test and validate spatial datasets.

1 Confirm task 

Learning Outcomes

Refer to elements

Overview of Assessment

A person who demonstrates competency in this unit must be able to provide evidence of:
• accurate record keeping
• applying solutions to a range of problems
• devising and implementing a cost-effective, functional solution
• examining suitability of existing arrangements
• measuring outcomes against specifications
• operational knowledge in a broad range of areas relating to linking
  datasets and knowledge management
• organising and prioritising activity
• performing a range of tasks where choice between a substantial
  range of options is required
• taking responsibility for own outputs in work and learning.