In Bureaucratizing the Good Samaritan, Waters (2001) ' (Thomas, 2003, p. 4). This article is an invitation for others to engage in creative humanitarian data management.

No abstract

Like other wars, recent Western military interventions have entailed loss of civilians in the affected countries. As a result of the ‘Revolution in Military Affairs’, Martin Shaw makes two claims likely to recur in debates on such wars. The first is that those losses were much smaller than the loss of life as a result of previous misrule and oppression. The second is that during these interventions civilians suffered only accidental ‘small massacres’. Using victim figures from 600 local communities exposed to hostilities during Operation Enduring Freedom in Afghanistan, the authors test Shaw’s claims. They model community victim counts as a function of potential explanatory factors via zero-inflated Poisson regression. Several historic as well as concurrent factors are significant. Moreover, totals work out considerably higher than those offered by previous researchers. These findings are important to several aspects of the new way of war: as a reminder that harm comes not only from direct violence but from indirect effects of munitions; underreporting of civilian losses as a likely systemic feature; and distributions of victims as mediated by histories of war of which Western interventions may be final culminations.

Geographic information systems (GIS) are increasingly used for integrating data from different sources and substantive areas, including in humanitarian action. The challenges of integration are particularly well illustrated by humanitarian mine action. The informational requirements of mine action are expensive, with socio-economic impact surveys costing over US$1.5 million per country, and are feeding a continuous debate on the merits of considering more factors or 'keeping it simple'. National census offices could, in theory, contribute relevant data, but in practice surveys have rarely overcome institutional obstacles to external data acquisition. A positive exception occurred in Lebanon, where the landmine impact survey had access to agricultural census data. The challenges, costs and benefits of this data integration exercise are analysed in a detailed case study. The benefits are considerable, but so are the costs, particularly the hidden ones. The Lebanon experience prompts some wider reflections. In the humanitarian community, data integration has been fostered not only by the diffusion of GIS technology, but also by institutional changes such as the creation of UN-led Humanitarian Information Centres. There is a question whether the analytic capacity is in step with aggressive data acquisition. Humanitarian action may yet have to build the kind of strong analytic tradition that public health and poverty alleviation have accomplished.

Humanitarian agencies struggle with high uncertainty. The focus here is on uncertainty that grows out of the internal complexity of the agencies themselves, rather than simply emanating from their war-ridden environments. This is illustrated with a study of uncertainty management and information processing in two UN agencies working for the victims of the conflict in southern Sudan. Data from 1995 relief distributions are used to simulate aspects of uncertainty; paradoxically, uncertainty increased with growing success of the relief operation. The findings is in tune with observations from the same region that Jok (1996) reported in this journal. While uncertainty may remain difficult to reduce, co-operation among agencies and public confidence in their work provide functional equivalents for certainty.