statistical analyses of war and peace


which uses Systat to analyse similarities and differences between ethno-social boundaries on the ground and the linear divisions of Voronoi diagrams plotted from conflict data. Ethnic and religious interfaces as a factor


in the course of conflict or pacification development are a fertile area of data analytic research, and not one which is yet methodologically tamed; Shellman et al, for example, demonstrate11


that the different


approaches to definition of those interfaces can profoundly affect the inferences drawn and ‘have myriad implications for the study of civil conflict and conflict processes’. Voronoi plots are also, in a separate but


conceptually related context, the chosen visualisation of a Russian army intelligence Colonel whose brief is to analyse the correlation between conflict escalation or resolution and intercommunal or extracommunal communication patterns. His results strongly suggest that changes in the levels of tension which precede and influence instances of armed conflict are modified by the extent and nature of communication around them. Both facilitation and suppression of information flows can on occasion either assist or detract from attempts at non-military defusing of conflicts, he argues, running Voronoi animations from


past successes and failures across a monitor to illustrate the point, but the patterns are different. While facilitated communications are associated with greater amplification in both directions than suppression, they favour a significantly higher incidence of successes and reduced cases of failure. ‘But,’ he adds ruefully, ‘facilitation comes less easily to military structures than suppression.’ This fracture plane between military


functions and political aims is echoed by numerous commentators in various specialisms. A French academic serving as a statistical intelligence advisor to his country’s defence ministry argues that data analysis is often ‘based on different views of the past, predicated on different perceptions of the present, and applied to different demands of the present and future, within different versions of reality’. An example of this, given by a French academic with links to his country’s defence ministry, is the interface between civilian engineering industries, government procurement economics, and military users, whose whole operating philosophies are often mutually contradictory over considerable areas of practice. Michael Blair, a quality assurance analyst working for Dynamic Research Corporation,


commented on this recently12 in relation


to how to ‘reduce billions of dollars in our military budget while improving our ability to meet the needs of the military in a time of war’. Observing that ‘after all the training and government financing, the military has only small, isolated pockets of success and must still create a sustained CPI [continuous process improvement] mentality’ he points to the fact that, within the US, command and control management structures are regarded as outmoded by business yet are central to military organisation. Whether one is prosecuting a war,


trying to avert one, or navigating the consequences of one, scientific computerised analytic approaches to large and complex data sets are increasingly vital. They are equally essential in assessing the effects on increasingly globalised socioeconomics, and vice versa. Perhaps most important of all, they are the only hope for managing the fuzzy domain of complex transactional vectors which span the narrow gap between wasteful conflict and productive harmony.


References and Sources For a full list of the references and sources cited in this article, please visit www.scientific-computing. com/features/referencesapr11.php


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