January 2013 - Helping QLD government make data accessible to the public

Fisheries Queensland is the lead agency in developing the policy framework to protect and conserve fisheries resources while maintaining profitable commercial and enjoyable recreational fishing sectors.

The future of profitable commercial and enjoyable recreational fisheries relies on our natural resources being used in a sustainable way. This requires keeping a close eye on fish stocks and the performance of management arrangements for each fishery. By routinely collecting information from commercial and recreational fisheries using a range of monitoring programs, and assessing that information, they can make objective decisions to ensure the future of our resources.

Time based data has been collected from all of the industry sectors including catch and effort (or in the case of aquaculture, production and inputs to production) and this data has accumulated in internal data stores. The Department also collects data relating to:

  • Observations of commercial fishing operations,
  • Statistical sampling of fish populations to gauge their viability; and
  • Custodianship of a number of administrative boundaries such as Regulated Waters (also known as closures), zones associated with fishery quotas and zones associated with different jurisdictions.

While this data is fundamental to the Department's policy and monitoring operations, there has also been long standing demand, both from the public and external research and governmental agencies for access to the data itself. There is an increasing expectation from all parties interested in this data, that it is timely, accurate and relevant to particular locations (or spatially enabled).

Business Aspect has been engaged to deliver the Department’s QFish initiative which will meet this expectation by delivering timely, authoritative data through an online web portal. QFish is based upon a multi-dimensional database that aggregates and summarises data from the fisheries Data Mining Environment (DME). By using a multi-dimensional database in this way, complex queries over large datasets are extremely fast, with no impact on the underlying databases or applications.