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Geographic information systems (GIS) are already employed, or have the potential to be utilised, in a wide range of application areas within Northern Ireland. The overall effectiveness of GIS depends on the 'availability' of the various datasets that are required to enable it to carry out its intended function.

The GI Strategy for Northern Ireland states that key datasets are those which provide the highest strategic value to government and to the rest of the public service. In practice the key datasets are likely to be those data produced by one organisation and used by a number of other organisations within the Mosaic organisational framework.

A key spatial dataset in this context is defined by Mosaic as:
"A spatial dataset on which business functions rely, or for which there is a mandatory requirement and which is required by more than one organisation, or as required by INSPIRE."

Much of this data already exists, however to date there has been no coordinated attempt to identify key data, or its availability, ownership, currency or fitness for purpose. This project will ascertain the common data requirements across all GI strategic themes, such as Land & Property, Transport, Statistics, Environment and Agriculture etc., catalogue those data defined as key and crosscutting in nature, through appropriate and agreed metadata, and develop an e-enabled system to enable users to access the metadata resource.

There are three levels of metadata:
Discovery - "What datasets hold the data I am interested in?"
Exploration - "Do the identified datasets contain sufficient information to enable analysis to be carried out for my purposes?"
Exploitation - Enables the process of obtaining and using the data sourced from the owner.Throughout the pilot options the Discovery level of metadata will be proposed.
Project Objective
• To develop new access mechanisms for key datasets, together with standardised data formats, to enable the identification of key datasets and exchange of data between users.
culture and heritage
environment and agriculture
key datasets
land and property