Know4 drr poster_ws_bolzano_public_sector_plus

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Transcript of Know4 drr poster_ws_bolzano_public_sector_plus

  • 1. S. Kienberger, R. Spiekermann Knowledge fragmentation in the public sector Department of Geoinformatics Z_GIS, University of Salzburg 1. Introduction 2. The role of the public sector 3. Barriers and bridges deterring/supporting knowledge production, implementation, and sharing 4. Examples from Case Studies Stakeholders: Who is likely to be directly or indirectly involved with disasters and have to make decisions? Knowledge production: What data and information is used and produced by stakeholder groups? Communication and transfer of knowledge: Are data, information, and knowledge shared by and with other stakeholders? If so, how is it shared? Basis for decisions and co-production of knowledge: How are decisions taken? Are other stakeholder groups also involved? Is sufficient information and evidence available to make appropriate decisions? Information knowledge vs. orientation knowledge: If information is sufficiently available, to what degree does orientation knowledge support or hinder DRR and CCA measures and decisions as well as the understanding of priorities? Stakeholders affected by decisions: Who is likely to be affected by decisions taken? An indication of wisdom: Does the knowledge that is produced, i.e., do the decisions taken (in particular by the public sector) actually lead to DRR and CCA? If not, why not? 5. Key questions guiding future work Organisations and institutions from the public sector play the most important role for protecting society from natural hazards and leading the recovery efforts, thus preventing or reducing the impact of disasters. Many instruments are available for the public sector and include risk governance through implementation of appropriate policies by governing bodies. A major issue is that the provision of additional scientific information and understanding of natural processes does not necessarily lead to more effective DRR and CCA. International UN (e.g. UNISDR, UNEP) EU (e.g. Flood Directive) National Ministries, Agencies, Armed forces Public institutes (e.g. Meteorological Service) Provincial Emergency response authority Technical Services (Hydrology, Geology, Forestry etc) Local Mayor, Rescue organisations Local land use planning Policy making/implementation and interaction at various levels FunctionalStructuralSocial Communication Co-operation Co-ordination Institutionalised guidelines Clearly defined competencies Standards Consultations Efficient exchange of information Successful relationships (trust and respect) Factors of uncertainty: Divergent priorities Relevance of information Is the information understood? Impact of insufficient resources False expectations and great dependency Factors of uncertainty: Applicability of policies Changing relevance and significance of standards Impact of pressures and influences on decision-making Factors of uncertainty: Recognition Objectives Understanding of information made available Salzburg flood event 2013 The expectations towards meteorologists and hydrologists have risen drastically. The information being shared has a high degree of uncertainty. Updates concerning the predicted flood event were communicated to the media and emergency response teams at regular intervals: the media had trouble understanding how to deal with the information and delayed the transfer of up-to-date information to the public. There is great dependency on the journalists personal knowledge of weather forecasts as to whether or not the meaning is understood. Typhoon Xangsane 2006, Vietnam The focus is still very much on response and recovery. In this way improvements to DRM are difficult to achieve. The policy of government is too focused on protecting the population upon the occurrence of an event rather than preparing with mitigation measures such as land planning and building codes. Specific information, including indigenous knowledge, is not considered relevant by consulting scientists. The theory of how DRM is to be coordinated is not applied at local level due to lack of resources. Lack of financial resources available at local level remains the most significant obstacle to an effective prevention policy. Most important terms from the analysis of knowledge fragmentation in the public sector based on the case studies.