EAE5052 · Spatial data interoperability and integration

Overview

Spatial data interoperability is the ability to access, share, exchange and manipulate spatial data stored in heterogeneous distributed repositories. It is a cornerstone tenet of a spatial data infrastructure and enables the sharing and integration of spatial data between systems in different organisations and across applications and industries. This unit introduces the concept of spatial data infrastructure, international standards enabling spatial data interoperability, spatial data structures and file formats, the common approaches to spatial data exchange including the Extract, Transform and Load (ETL) method, and tools for spatial data exchange and integration such as Feature Manipulation Engine (FME) and the ArcGIS Data Interoperability extension. It has a strong practical element, encompassing a set of hands-on practicals and projects in which you undertake spatial data transformation and integration for various applications using the taught approaches and tools.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Understand the importance of spatial data interoperability;
2. Be familiar with international spatial data standards;
3. Describe common spatial data structures and file formats
4. Comprehend the concept, principles and components of spatial data infrastructure;
5. Grasp the common methods and skills for the spatial data exchange;
6. Obtain skills for spatial data integration.

Workload

• 1-hour lecture videos; • 2-hour workshops; • 3-hour practicals/projects and • 6-hour independent study per week

Student experience, not official rules. Nothing here changes what the Handbook says.