any case, decision-makers may not understand the uncertainties inherent in modelling. A risk model can produce very precise results. It may show, for example, that a 1-in-100-year flood will affect 388,123 people. In reality, however, the accuracy of the model and input data may provide only an estimate of the order of magnitude. At the same time, given the continued focus on managing disasters rather than disaster risk, demand for risk information from governments may be weak. Many risk assessments are one-off projects, particularly in the context of post-disaster recovery operations, and even the maintenance of national disaster loss databases faces sustainability issues (Wirtz et al., 2014; Gall et al., 2014). While international organizations have supported risk assessments in many high-risk, low-income contexts (GFDRR, 2014a), these assessments are rarely appropriated by national institutions and seldom contribute to risk awareness in the country, simply because the underlying research infrastructure to sustain such efforts does not exist (Gall et al., 2014b). The capacity to produce and use risk information varies enormously from country to country. Unsurprisingly, the HFA Monitor highlights that high-income countries with strong scientific and technical communities have been able to make significant progress in monitoring and forecasting hazards and developing national and local risk assessments, whereas many low-income countries simply do not have the capacities to do so. As such, the coverage of risk information is patchy from a geographical perspective, responding more to project opportunities than to real needs. And even when risk information is available in national institutions, mechanisms to ensure that the information is available and usable at the local level are often missing, especially given the weak capacity of most local governments outside of major cities (CDKN, 2014). Linked open data, social media and crowdsourcing could potentially bridge this gap. But there
remain tensions between data as a power source, as an income generator and as a social good. Legal obstacles often remain regarding the extent to which proprietary data needs to be transformed to become free and open (GFDRR, 2014a). Another problem identified by the HFA Monitor is the absence of agreed standards or normalized approaches. This means that large volumes of studies and research carried out by universities, research institutions and others at the national level do not provide standardized results. In Padang, Indonesia, for example, no less than twelve different tsunami risk assessments were carried out, each producing different results (Løvholt et al., 2014). In many other tsunamiprone locations, not a single detailed assessment has been carried out. Shared language, terminology and translation are other barriers to sharing and using risk information. While international efforts under UNISDR and the Intergovernmental Panel on Climate Change (IPCC) have developed standard terminologies, words such as vulnerability, resilience and mitigation are used in widely differing ways in different communities. When such words are translated into other languages, this divergence multiplies even further. In practice, national meteorological and geological institutions are rarely integrated and frequently use different concepts and methods to assess risk. This makes multi-hazard assessment particularly challenging. Multiple or concatenated risks from cascading and technological hazards are increasingly common, meaning that a single-hazard risk assessment is often not relevant to the decisionmakers responsible for broader risk management. Moreover, failing to consider the full risk spectrum can actually increase risk. For example, heavy concrete structures with a groundlevel soft story for parking can protect against cyclone wind, but can be deadly in an earthquake (GFDRR, 2014a). 147