Note: Intro -- Preface -- About This Book -- Contents -- Editors and Contributors -- 1 Science, Technology, and People-Centered Society -- 1.1 Introduction -- 1.2 People-Centric Process for People-Centered DRR -- 1.3 Digital Transformation for Science and Technology for Human Security and Social Inclusion -- 1.4 Human Security and Well-Being on SDG3: Health and Well-Being for All -- 1.5 About the Book -- References -- 2 Science, Technology, Innovation and Sendai Framework for Disaster Risk Reduction -- 2.1 Introduction -- 2.2 Multiple Hazards -- 2.3 Complex Risk Landscape -- 2.4 Science for Finding Causes and Providing Solutions -- 2.5 Community Research with Science Technology -- 2.6 Science Technology for Co-Designing Solutions -- 2.7 Science Technology for Personalized Choices -- 2.8 Postscript -- References -- 3 Systemic Risk and System-Based Approach for Society 5.0 -- 3.1 Introduction -- 3.2 All Hazard Approach -- 3.3 Methods of Disaster Response: Decision Making in the Face of Uncertainty -- 3.4 Stages of Disaster Response -- 3.5 Utilization of Information in Disaster Response -- 3.5.1 Management and Recovery of Critical Infrastructure -- 3.5.2 Post-Disaster Information Utilization -- 3.6 Way Forward -- Reference -- 4 Emerging Issues and Japan's Milestones in Science and Technology for Disaster Risk Reduction -- 4.1 Introduction -- 4.2  Lesson Learned from Disaster Responce and Information Management by DRR3.0 × Society 4.0 in  Japan -- 4.2.1 Systematization of Sharing Data -- 4.2.2 Collection, Design and Data Uncertainty -- 4.2.3 Processing of Information into Usable Information -- 4.2.4 Importance of Monitoring Over Time -- 4.2.5 Systematic Implementation of Information Collection and Organization -- 4.2.6 From Statistical Thinking to the Utilization of Non-Aggregated Data -- 4.2.7 Message Distribution. , 4.2.8 Consensus Building: Decision-Making, Accountability, and Collaboration -- 4.3 Observation to Orient, Decide, and Act: Demand Based Innovation on Emergency -- 4.4 The Role of Local Institute: Co-Creation of Care Science for Disaster Risk Reduction -- 4.5 Way Forward: To Distributed Sheltering and Communication and Care -- References -- 5 Evidence-Based Policymaking of Smart City: The Case of Challenge in Maebashi City, Japan -- 5.1 Introduction -- 5.1.1 What is "EBPM"? -- 5.1.2 Challenges in Promoting EBPM in Japan -- 5.2 Micro Geodata (MGD) to Support EBPM Promotion and Available MGD in Japan -- 5.3 Application Example of MGD: High-Definition Damage Simulation of a Large-Scale Disaster -- 5.4 The Super City Concept and Its Challenges in Maebashi City -- 5.4.1 The Super City Concept of Japan -- 5.4.2 Background of the Super City Concept of Maebashi City -- 5.4.3 Overall Picture and Challenges of the Super City Concept in Maebashi City -- 5.5 Maebashi City's Approach to EBPM Using Municipal MGD: An Example of Estimating the Spatial Distribution of Vacant Houses -- 5.6 Toward the Realization of a Super City Using Maebashi ID -- 5.7 Prospects for EBPM Promotion in Japan -- References -- 6 Personal Life Records for Health Decision-Making in Disaster Situations Society 5.0 and Implications for Resilient Community -- 6.1 Introduction -- 6.2 Issues of Information Sharing During Disasters -- 6.2.1 Personal Information as the Basis for Information Sharing and Cooperation -- 6.2.2 List of People Requiring Support for Evacuation and Disaster Survivor Register -- 6.2.3 Evacuation List -- 6.2.4 How to Associate the Three Lists -- 6.2.5 Case Study: Machi Care Commons -- 6.2.6 Consensual Bias -- 6.3 Proposals for Data Altruism in Europe -- 6.3.1 Data Governance Bill -- 6.3.2 Data Altruism in Health Care -- 6.3.3 How to View Data Altruism. , 6.4 Examination of Specific Cases -- 6.4.1 Personal Information Protection Act 2000 Issues: Information Sharing Issues -- 6.4.2 Safety Issues: Information Disclosure Issues -- 6.5 Consider Data Altruism: A Break from Consensus Parochialism -- 6.5.1 Validity of Data Altruism -- 6.5.2 Move Away from a Consensus Bias -- 6.5.3 How to Develop the Information Infrastructure, Interoperability -- 6.6 Conclusion -- References -- 7 Digital Transformation and Disaster Risk Reduction -- 7.1 Introduction: What is Digital Transformation and How? -- 7.2 Why Digital Transformation for DRR? -- 7.3 Technologies Supporting Digital Transformation -- 7.3.1 Utilization of Geographic Information Systems -- 7.3.2 Data Management and Sharing -- 7.4 Do It Yourself! Participatory Digital Transformation -- 7.4.1 Service Design for PGIS -- 7.4.2 Data Accuracy -- 7.4.3 Prototyping Process: Rapid Prototyping for Disasters -- 7.5 Challenges in Digital Transformation for DRR -- References -- 8 XR and Implications to DRR: Challenges and Prospects -- 8.1 Introduction -- 8.2 Disaster Literacy and Current Education on Disaster Preparedness -- 8.3 Disaster Literacy on Society 5.0 -- 8.4 XR and the Potential for Disaster Management Application -- 8.5 Feasibility Study on School Education -- 8.5.1 AR Flooding Experience App Disaster Scope® Floods -- 8.5.2 AR Smoke Experience App Disaster Scope® Fire& -- Smoke -- 8.5.3 The Utilization of the System -- 8.5.4 Evaluation -- 8.5.5 Considerations and Future Issues -- 8.6 Implementation and Promotion on Community by Local Government -- 8.6.1 Yokohama City: Yokohama Evacuation Navigation System -- 8.6.2 Kobe City Urban Innovation Challenge -- 8.6.3 Kochi: Gaining the Literacy for Emergency and Resilience -- 8.6.4 Metaverse Disaster Training -- 8.7 Way to Forward -- References -- 9 Open Governance and Disaster Risk Reduction -- 9.1 Introduction. , 9.2 Understanding Open Science and Different Components -- 9.3 Growing Relevance of Open Data for DRR and Governance -- 9.4 Open Governance for DRR: Case Study Examples -- 9.4.1 Open Data in Drought Management-Case of Cape Town, South Africa -- 9.4.2 Open Data in Urban Flood Mitigation-Case of Cameron -- 9.4.3 Case of Typhoon Haiyan 2013 in the Philippines -- 9.4.4 Case of Hurricane Sandy 2012 in the United States -- 9.5 Key Challenges in Operationalizing Open Governance -- 9.5.1 Digital Divide in the Disaster Management -- 9.5.2 Technical Difficulties -- 9.5.3 Insufficient Data Application Capacity -- 9.5.4 Limitations of Social Media -- 9.6 Key Lessons and Opportunities -- 9.6.1 Bridging the Digital Divide -- 9.6.2 Government Support for Technical Issues -- 9.6.3 Multi-Partnership Collaboration Toward Emergency Response -- 9.6.4 Capitalizing on the Social-Media Big Data -- 9.7 Conclusions -- References -- 10 Open Governance and Disaster Planning, Recovery, and Response: Lessons from the United States -- 10.1 Introduction -- 10.2 Theory of Open Governance in Disaster Management -- 10.3 Leveraging Digital Technologies to Communicate and Interact with the Public -- 10.4 Leveraging Crowdsourced Data for Improved Decision Making -- 10.5 Three Examples of Open Government Technologies for Managing Disasters in the United States -- 10.5.1 Background on the United States' Emergency Management System -- 10.5.2 Leveraging Digital Technologies to Communicate and Interact with the Public: The Use of NextDoor in Hurricane Recovery -- 10.5.3 Leveraging Crowdsourced Data for Improved Decision Making: Damage Assessment After Hurricane Sandy -- 10.5.4 Leveraging Open Data, Big Data, and Data Analytics for Intra- and Inter-Governmental Collaboration in Disaster Management: The Hazus Risk Estimation Program -- 10.6 Conclusions -- References. , 11 Technology Landscape in Post COVID-19 Era: Example from China -- 11.1 Introduction -- 11.2 Background of China's COVID-19 Response -- 11.2.1 Fighting the Virus in Wuhan City -- 11.2.2 Information Concealment and Initial Response by Local Governments -- 11.2.3 Causes of Infection Explosion in Wuhan City -- 11.3 Initial Response of the Central Government to COVID-19 Response System -- 11.3.1 Central Government's Initial Response -- 11.3.2 COVID-19 Measures of the Central New Pneumonia Control Guidance Subgroup -- 11.3.3 Formation of a National System for COVID-19 Response -- 11.4 Institutionalizing the "Community" Function -- 11.4.1 Institutionalization of Community Management -- 11.4.2 Institutionalization of Community Housing Blockade and Personnel Structure -- 11.5 Institutionalizing Use of Information Technology in COVID-19 response -- 11.5.1 Infection Cluster Discovery Using Big Data -- 11.5.2 Health Code -- 11.6 Dalian's COVID-19 Response -- 11.6.1 Features of Dalian COVID-19 Response -- 11.6.2 COVID-19 Measures and Use of Information Technology in Dalian Community -- 11.6.3 Overcoming Database Problems -- 11.6.4 Surveillance and Drones -- 11.7 Conclusion -- References -- 12 Jugaad Innovation: Concept and Lessons of Social Innovation in India -- 12.1 Introduction -- 12.2 Jugaad: A Review of the Concept -- 12.2.1 Manifestations and Measures of Frugal Innovations -- 12.3 Theory and Framework -- 12.4 Research Methodology -- 12.5 Case Studies -- 12.5.1 Mobile Money as a Jugaad Innovation for the Bottom of the Pyramid -- 12.5.2 Addressing Sustainable Development Goals: Eat Raja -- 12.5.3 Addressing Sustainability and Inclusion: Mitticool -- 12.5.4 Addressing Inclusion: Padman -- 12.5.5 Addressing Women Empowerment: Laxmi Asu Making Machine -- 12.6 Discussion-Future Trajectories from the Lens of Bricolage Theory -- References. , 13 Towards a People-Centered, Technology-Driven Society.