Metadata is a vital tool for management of spatial data and plays a key role in any spatial data infrastructure (SDI) initiatives. It provides users of spatial data with information about the purpose, quality, actuality and accuracy and many more of spatial datasets. More importantly, metadata performs crucial functions that make spatial data interoperable, that is, capable of being shared between systems. However, current metadata models and standards are complex and very difficult to handle. Also, metadata for spatial datasets is often missing or incomplete and is acquired in heterogeneous ways.
Besides, metadata is commonly viewed by organisations as an overhead and extra cost. Typically it is acquired after the spatial data itself, through lengthy, complex efforts. Metadata is usually created and stored separately to the actual data set it relates to, and is often managed by people with a limited knowledge of its value. Separation of storage creates two independent data sets that must be managed and updated - spatial data and metadata. These are often redundant and inconsistent. Thus the reliability of spatial information and the extent it can be used are unclear.
To respond to this issue, this research project investigates the importance of having an integrated system for both spatial data and metadata information in which that metadata and spatial data can be integrated, so that when spatial data is updated, metadata related to that data is also automatically updated. To achieve the aim of the project, the following objectives will be considered:
- Study on metadata ontology
- Study on current practices in Spatial Metadata Tools
- Case Study within project partners
- Development of the concept of Metadata Automation
- Investigation on technological trends and their impact on metadata: web 2.0, semantic web…..
- Design and development of a prototype system for metadata automation