An emerging priority in information management is the need for smarter search engines tailored to specific types of end users. End-user-focused systems can provide immediate, precise and relevant results, cutting through extensive collections of potentially irrelevant items.

This project is using data science to develop an online tool that can search, filter and deliver existing sources of marine data, and aggregate and forward them to web services for reporting, mapping, modelling, or further analysis.

The search interface will be similar to Amazon.com in its capacity to search and retrieve products, classify product types, and recommend linked, user-specific items of interest. For example, search results for an environmental manager could be different than those of a researcher or industry specialist.

Phase one of the project will scope the needs of stakeholders and partners, identify the desired functionality of the interface, and ensure alignment with existing national environmental information initiatives (such as the National Plan for Environmental Information and the National Environmental Information Infrastructure).

Linked open data will be generated from sources held by Geoscience Australia, the Australian Institute of Marine Science, the Integrated Marine Observing System, the Australian Ocean Data Network, CSIRO, the Great Barrier Reef Marine Park Authority and possibly the Australian Bureau of Meteorology.

The new search tool will provide stakeholders such as the Department of the Environment, as well as the general public, with faster and easier access to marine data. This in turn will improve the value of existing data holdings through increased exposure, accessibility, and a better understanding of how they are being used by different user communities.

It will also enable IT innovation through the development of new websites, smartphone and tablet applications or GovHack initiatives. The use of the tool will be assessed through web hits, statistics and performance measures (such as response time) and the tracking of usage patterns.

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