Science data sets concerning the Polar regions are currently underutilized relative to their potential value. This is largely due to the domains highly data diverse nature, in both form (satelite data, manual single samples, model outputs) and domains (oceanography, atmospheric sciences, geology, botony). This diversity requires data analysis processes that utilise unique combinations of, high powered data processing tools, information retrieval methods, and data visualization technologies, in orchestrated combinations for each of many diverse end users. As a result it is exceedingly difficult to ask concise and scientific questions of this information.
Improving the use and value of existing polar region data sets is crucial to understanding the polar regions variability over different timescales, with consequent associated benefits for society. One of the critical first steps towards realising such improvements involves fostering effective collaborations, communications and meetings between those community experts in data visualization; big data processing, information retrieval, and polar scientists. Consequently, funcded by the U.S. National Science Foundation, in November 2014 forty polar scientists, data engineers, and design scholars, from a diverse set of institutions, gathered for a 2 day hackathon.
Along with many lessons learnt as regards multi-disciplinary interactions, participants were overwhemingly positive about the event, indicating that the cross-disciplinary networking, learning, and devlopment opportunities afforded were highly valued and would be sought after in the future. The most dominant negative review concerned the limited time duration and need for greater focus when tackling an issue with so many avenues for work. Finally, utilising Github as a public shared collaboration venue, the hackathon produced trackable code and system design developments that were carried on into the future.