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Royal Australian Navy: navigating our way into navigational data (presentation)
Abstract: In the past few years evidence based decision making has become one of the catch cries of the big data phenomenon. This has seen both Google and Facebook efforts leading to open source software to analyse big data sets as part of the Hadoop ecosystem. Additionally, the role of data scientist has been declared as the sexiest job of the 21st century.
The Royal Australian Navy (RAN) has a vast array of information available via electronic navigational display systems. Amongst other things, this includes: position; velocity; water depth; weather information; and maritime traffic information. With recent Navy 2-star sponsorship, all vessels are required to submit their navigational log files to the Defence Science and Technology Organisation for analysis; this could amount to 1 terabyte of plain text data each year.
Demonstrating the value of this data, we have undertaken three rapid studies. The first study provided the RAN with analysis of patrol boat speed profiles categorized by activity. The second study concerned patrol boat wharf-space usage in Darwin. And the final study (ongoing) seeks correlations between navigational and meteorological data and precursors of hull damage. These studies contribute to evidence-based decision making for patrol boat replacement.
These examples lead to a discussion of military big data challenges in Australia, and the techniques we propose to overcome them. These include the use of big data techniques, heuristic methods for pattern recognition and statistical data exploration. Finally, we share our vision of how RAN’s future could be enhanced by embracing big data.
(based on work with Justin Beck, Katrina Kelleher and Timothy J. Surendonk, talk given at the 2014 Defence Operations Research Symposium, October 2014, and the 83rd Symposium of the Military Operations Research Society, June 2015, title and abstract approved for public release – won Gus Schaeffer Award for best paper at DORS 2014)