The geospatial sciences face grand information technology (IT) challenges in the twenty-first century: data intensity, computing intensity, concurrent access intensity and spatiotemporal intensity. These challenges require the readiness of a computing infrastructure that can: (1) better support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries; (2) provide real-time IT resources to enable real-time applications, such as emergency response; (3) deal with access spikes; and (4) provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge. The emergence of cloud computing provides a potential solution with an elastic, on-demand computing platform to integrate Á observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support, and to provide social impact and user feedback Á the essential elements of the geospatial sciences. We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles, the kernel of the geospatial sciences, could be utilized to ensure the benefits of cloud computing. Four research examples are presented to analyze how to: (1) search, access and utilize geospatial data; (2) configure computing infrastructure to enable the computability of intensive simulation models; (3) disseminate and utilize research results for massive numbers of concurrent users; and (4) adopt spatiotemporal principles to support spatiotemporal intensive applications. The paper concludes with a discussion of opportunities and challenges for spatial cloud computing (SCC).

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A submarine is routinely required to return to periscope depth; however, a transition from deep to shallow waters is one the most dangerous operations due to the potential to collide with surface vessels. Submarine operations are not particularly well understood outside the immediate submarine community, particularly from a sociotechnical perspective. A submarine sounds and control room simulator was used to examine the work of ten teams. The Event Analysis of Systematic Teamwork method was used to model the social, task and information networks in order to describe team performance. Results showed that the sonar controller and operations officer are the busiest in the command team. Communication between these operators was revealed as a potential bottleneck in the command team, particularly during higher demand scenarios. The information communicated and tasks completed centred on the processing and understanding of sonar data. Implications are discussed alongside suggestions for future work.

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Objective: The aim of this study was to use multiple command teams to provide empirical evidence for understanding communication flow, information pertinence, and tasks undertaken in a submarine control room when completing higher- and lower-demand inshore operation (INSO) scenarios. Background: The focus of submarine operations has changed, and submarines are increasingly required to operate in costal littoral zones. However, submarine command team performance during INSO is not well understood, particularly from a sociotechnical systems perspective. Method: A submarine control-room simulator was built. The creation of networked workstations allowed a team of nine operators to perform tasks completed by submarine command teams during INSO. The Event Analysis of Systematic Teamwork method was used to model the social, task, and information networks and to describe command team performance. Ten teams were recruited for the study, affording statistical comparisons of how command-team roles and level of demand affected performance. Results: Results indicated that the submarine command-team members are required to rapidly integrate sonar and visual data as the periscope is used, periodically, in a “duck-and-run” fashion, to maintain covertness. The fusion of such information is primarily completed by the operations officer (OPSO), with this operator experiencing significantly greater demand than any other operator. Conclusion: The OPSO was a bottleneck in the command team when completing INSO, experiencing similar load in both scenarios, suggesting that the command team may benefit from data synthesis tasks being more evenly distributed within the command team. Application: The work can inform future control-room design and command-team ways of working by identifying bottlenecks in terms of information and task flow between operators.