Preface: In today’s world, where disasters—whether natural or man-made (technological)—are happening more often and with greater impact, it’s more important than ever to have solid, easy-to-access information on the risks we face. That’s where this monograph, "Comprehensive Databases on Natural and Man-Made (Technological) Hazards and Disasters: Mapping Risks and Challenges," comes in. Also, it pulls together a range of databases that cover all kinds of disasters, aiming to give a full picture of the risks out there. This publication represents a collaborative effort between disaster risk management experts from Serbia and Austria, each contributing their specialized expertise to enrich the work. The main goal is simple: to offer a valuable resource for anyone involved in disaster risk reduction—whether they’re researchers, policymakers, or on-the-ground practitioners. By mapping out the risks and challenges tied to different hazards, we hope to help create better strategies for reducing disaster impacts. On the other side, we’ve taken a broad approach, covering both natural hazards (like earthquakes, tsunamis, and storms) and man-made ones (like industrial accidents and nuclear incidents). This gives a complete view of the global risk landscape, so no major threat is overlooked. Each chapter focuses on specific types of hazards, breaking down the databases that track these events, how they gather data, and how that data is used. These databases are essential for understanding how often these events happen, where they tend to occur, and how severe they are. This info is critical for predicting future disasters and preparing for them. Furthermore, we don’t stop at just listing databases, we also dig into the challenges of gathering, sharing, and using disaster data. There’s a huge range of data sources, and with different standards and the need for real-time info, it can be tricky. We talk about these obstacles and suggest ways to make disaster data easier to access and more practical to use. Another big focus is the role of technology in disaster risk management. Techs like geospatial tools, remote sensing, and data analytics have changed the game when it comes to monitoring and responding to disasters. We highlight some of the coolest tools and platforms out there that are using these technologies to make disaster management better and faster. Collaboration is key in disaster risk management, and this monograph really pushes the importance of international cooperation. Sharing information and resources across borders helps everyone be better prepared and more resilient. When countries work together, they can better predict and handle the impact of disasters. In a nutshell, this monograph is your go-to guide for understanding the many databases that track both natural and human-made disasters. It takes a hard look at where we stand with disaster data, points out both the challenges and opportunities in the field, and emphasizes how crucial technology, teamwork, and education are in building a safer, stronger world. Our hope is that this work will be a helpful resource and spark more research and innovation in disaster risk management. The monograph starts with an introduction that sets the stage for exploring natural and human-made hazards. It explains why accurate, accessible data is so important for managing disaster risks and gives an overview of the content. From there, the monograph is split into two main sections: Natural Hazards and Man-Made (Technological) Hazards. The Natural Hazards section covers everything from geological events (like earthquakes and volcanic eruptions) to meteorological and biological hazards (like floods, storms, and disease outbreaks). We go deep into the databases that track these events, how they collect data, and how that data is used in risk assessment and disaster management. The Man-Made Hazards section focuses on things like industrial accidents, nuclear disasters, chemical spills, and building collapses. Just like with natural hazards, we break down the key databases and discuss how they help manage and reduce these risks. Introduction: Large-scale disasters, from naturally occurring events such as earthquakes and tsunamis through to man-made ones including industrial accidents and financial crises—have been increasing of late in frequency and intensity, with long-lasting effects on societies and infrastructures while bursting into the global economy. Some of the drivers underlying these challenges—such as climate change, rapid urbanization, technological changes, and geopolitical instability—are becoming increasingly urgent, hence making current risks more complex. This changing scenario requires much more sophisticated ways of managing risks and preventing disasters. Recently, much focus has been directed toward Disaster Risk Reduction, which focuses on reducing the impact of disasters through improved preparedness, mitigation strategies, and rapid response plans. Global frameworks, such as the Sendai Framework for Disaster Risk Reduction 2015–2030, draw attention to how data-driven risk assessments underpin resilience at levels ranging from the community to the nation-state and global levels. The increasing frequency and impact of disasters, further compelled by causes that are becoming increasingly interlinked, raise the need for accurate and comprehensive data to higher levels than ever before if risks are to be reduced effectively. The comprehensive mapping of risks and challenges of natural and artificial (technological) hazards and disasters, which was called for by the monograph entitled Comprehensive Databases on Natural and Man-Made (Technological) Hazards and Disasters: Mapping Risks and Challenges, discusses in some considerable detail the matter of pressing need for reliable data in disaster risk reduction. It goes on to give in-depth analysis regarding databases recording the occurrence of both natural hazards—such as earthquakes, floods, and storms—and human-made hazards that include industrial accidents and chemical spills. The effort here is to provide improved access to fundamental information necessary to reduce the impact of disasters and vulnerabilities worldwide by analyzing more than 50 of the most relevant databases. The authors would like to express their gratitude in this regard to Grammarly Premium and ChatGPT 4.0 for grammatical editing and reviewing this book chapter for clarity and quality in translation regarding English. Language improvement suggestions have been provided by the AI tools, but they have not been involved in the elaboration of the scientific content. Full responsibility for originality, validity, and integrity of the manuscript lies with the authors. The basis of any successful disaster risk management is having access to the right information at the right time. Forecasting natural disasters, monitoring environmental conditions that could cause industrial accidents, or tracking disease outbreaks—in all these areas, access to relevant information is key in making contextually informed decisions. However, this movement from pure response to proactive risk reduction has been prompted more than anything by leaps forward in the ways we can gather and integrate data and then analyze it. Data allows the professionals and the policymakers to predict when the events are likely to happen in the future owing to patterns from the past, weather trends, and geological insight in natural disasters. Seismic data, for example, informs the estimation of earthquake risk for areas around active fault lines; similarly, hydrologic models might forecast flood risk in heavy rain seasons. For man-made disasters, for instance, databases that track industrial process, hazardous material storage and safety protocols can find those most prone to accident and undertake precise preventative action before any accident occurs. Nevertheless, the availability and quality of disaster-related data still depend on the individual type of hazard, region, and local capacity for its collection. Whereas in most parts of the world certain risks, such as earthquakes or floods, are quantified, others—in particular, technological or economic hazards—are underreported, with no standardized data collection systems in place. The current monograph closes these gaps by means of a critical review of the diverse methodologies of the individual databases through pointing out strengths and weaknesses and by offering suggestions on how disaster data could be made more comprehensive and usable. Objectives of the Monograph: The primary goal of this monograph is to provide a thorough analysis of the available databases that track both natural and technological hazards. Specifically, it aims to: a) Offer a detailed overview of the most prominent databases that monitor various hazards, focusing on their scope, data collection methods, sources, and relevance to disaster risk management. b) Investigate the challenges associated with collecting, integrating, and utilizing disaster data, with a particular focus on issues of data quality, accessibility, and real-time application. c) Examine how technological advancements—such as satellite imagery, geospatial analysis, and real-time monitoring—are improving the way disaster data is collected and analyzed. d) Provide practical recommendations for enhancing disaster-related data systems, emphasizing the importance of data sharing, standardized reporting, and the incorporation of emerging technologies. e) Promote collaboration between researchers, policymakers, and disaster management professionals by creating a consolidated resource for understanding and utilizing disaster data effectively. Structure of the Monograph: The monograph is divided into two sections: Natural Hazards and Disasters and Man-Made (Technological) Hazards and Disasters. These contain several chapters covering specific kinds of hazards and the tracking and analysis databases for each. This is aimed at presenting the reader with a complete, systematic overview of the disaster data landscape for both natural and technological risks. This chapter, “Natural Hazards and Disasters,” presents a comprehensive analysis, of geological events like earthquakes and volcanic eruptions to hydrological and meteorological hazards, including floods, droughts, hurricanes, and biological hazards that affect human populations and ecosystems. Each chapter examines key databases for monitoring these hazards, discussing their role in disaster risk reduction, early warning systems, and response planning. a) Geological Hazards and Disasters: Seismic events, volcanic activity, and tsunamis are covered here, with databases like the USGS Earthquake Database and the Smithsonian Global Volcanism Program. These resources focus on assessing and improving early warning systems for geological hazards. b) Hydrological Hazards and Disasters: From floods to droughts, hydrological events can often be worsened by climate change. This section discusses databases like the Global Disaster Alert and Coordination System (GDACS) and the Netherlands Flood Database, which help monitor flood risks and improve water management. c) Meteorological Hazards and Disasters: Extreme weather events such as hurricanes, tornadoes, and heatwaves, influenced by climate change, are becoming more frequent and severe. This chapter reviews databases like the NOAA Storm Events Database and the World Meteorological Organization’s Severe Weather Database, which assist authorities in predicting and preparing for these atmospheric phenomena. d) Biological Hazards and Disasters: Epidemics, pandemics, and invasive species cause significant health crises and environmental damage. This chapter explores databases like the WHO’s Epidemic Data Platform and the Global Invasive Species Database (GISD), which monitor biological hazards and guide public health responses. This section “Man-Made (Technological) Hazards and Disasters” examines different man-made hazards that result from human activities, such as industrial operations, transportation systems, and urban development. These risks include industrial accidents, chemical spills, nuclear incidents, and urban disasters, all of which can cause significant harm to people, property, and the environment. a) Technological Hazards and Disasters: Industrial accidents, chemical spills, and nuclear incidents are explored in this chapter. It analyzes databases like the European Major Accident Reporting System (eMARS) and the International Atomic Energy Agency’s Nuclear Events Web-based System (NEWS), which provide insights into the causes, impacts, and preventive measures for technological disasters. b) Urban Hazards and Disasters: As cities grow, the risk of urban hazards—such as building collapses, fires, and traffic accidents—rises. This chapter looks at databases like the National Fire Incident Reporting System (NFIRS) and the Global Building Collapse Incident Database, which track urban risks and help shape urban planning and safety regulations. c) Social and Economic Hazards and Disasters: Social unrest, terrorism, and economic collapses are significant man-made hazards that can destabilize societies and economies. This chapter examines databases like the Global Terrorism Database (GTD) and the International Disaster Database (EM-DAT), which track incidents of terrorism, political instability, and economic crises, helping policymakers assess risks and develop mitigation strategies. This monograph uses a detailed, systematic approach, evaluating over 50 different databases that track disaster risks. We chose each database based on how relevant it is to specific hazards, its geographical coverage, how reliable the data is, and how easy it is to access. These databases cover a range of sectors, like public health, environmental science, industrial safety, and urban planning. We looked at each one closely, evaluating its effectiveness in disaster risk reduction, its strengths and weaknesses, and how well it could fit into larger data systems. We also dug deep into the challenges of collecting disaster-related data. Many of the issues stem from inconsistent standards across regions, difficulties with data sharing, and the hurdles of using real-time data. By identifying where current data systems fall short, we’ve made practical suggestions for improvement, aiming to add to the global conversation around disaster preparedness and resilience. Challenges and Opportunities in Disaster Data Collection: One of the biggest headaches with disaster data collection is the lack of consistency in how different regions, industries, and hazards report their information. Some databases provide detailed, real-time data, while others have significant gaps, outdated info, or cover only small areas. This monograph tackles these issues by pushing for standardized data collection methods that can work universally across different sectors and regions. On the flip side, new technologies like artificial intelligence (AI), machine learning, satellite imagery, and geospatial analysis are creating exciting opportunities. These tools improve the accuracy of disaster data, make real-time collection easier, and help create predictive models that aid decision-making. AI and machine learning, for instance, are changing how we identify risk patterns, forecast hazards more accurately, and issue timely alerts. Meanwhile, satellite imaging and remote sensing are game-changers for tracking natural disasters like floods, hurricanes, and wildfires, allowing emergency teams to respond more quickly. Geospatial analysis has become crucial for disaster risk reduction too, giving governments and organizations the insights they need to invest in the right mitigation efforts. Tools like Geographic Information Systems (GIS) layer multiple data sets to create detailed risk maps, showing vulnerable areas and forecasting how future disasters might play out. This tech is now widely used in disaster management, helping to better allocate resources and plan during crises. When it comes to managing disaster risks, international collaboration is crucial, especially because disasters often don’t respect borders and can impact several countries at once. Sharing data, research, and best practices among nations strengthens global efforts to improve early warning systems, disaster response strategies, and risk mitigation measures. This monograph emphasizes the importance of initiatives like the Sendai Framework for Disaster Risk Reduction, which promotes international cooperation in data collection and sharing. Platforms like the Global Disaster Alert and Coordination System (GDACS) combine data from various countries, offering real-time alerts and comprehensive risk assessments for all kinds of disasters. International organizations like the World Meteorological Organization (WMO) and the International Atomic Energy Agency (IAEA) are key players in setting global standards for data collection and encouraging cross-border cooperation. They offer platforms where disaster data can be shared transparently, making sure that countries have the information they need to respond effectively to emergencies. This monograph explores how these global efforts help build a more resilient world, especially for vulnerable populations.The monograph also looks at how integrating regional databases into global systems can improve disaster risk reduction. For example, databases like the European Major Accident Reporting System (eMARS) and the United States Geological Survey (USGS) provide localized data that, when integrated into global networks, enhance monitoring and response efforts. By combining regional and global insights, disaster preparedness becomes more coordinated, improving cross-border collaboration. Data Gaps and Future Directions Despite progress in disaster data collection, there are still big gaps, particularly in developing countries where resources for collecting and analyzing data are limited. This lack of accurate, timely data often leads to underreporting, incomplete datasets, and less capacity to address disaster risks globally. Certain hazards, like slow-onset disasters such as droughts, or complex risks involving technological failures, are also underrepresented in global databases because of the challenges in tracking and reporting them. This monograph highlights these gaps and suggests strategies to address them. Strengthening local capacity for data collection, investing in new technologies, and building international partnerships are critical steps toward filling these gaps. Additionally, non-traditional data sources, like social media and crowd-sourced information, can offer real-time, community-driven insights that complement traditional disaster monitoring systems. Looking ahead, there’s a lot of potential for new technologies to revolutionize disaster data systems. Blockchain, for instance, could improve secure data sharing, cloud computing could boost real-time data storage and analysis, and smart city technologies could integrate disaster risk management into urban planning. The Internet of Things (IoT) adds another layer of opportunity, with sensors monitoring environmental conditions and infrastructure in real-time, allowing preventive measures to be taken before disasters strike. Collecting and using disaster-related data comes with some serious ethical responsibilities. It’s crucial to make sure that the processes we use to gather this data respect people’s privacy and dignity, especially when we’re dealing with health-related information. For example, when tracking disease outbreaks, public health surveillance might need personal data, but it’s essential that this data is handled with care to protect individual privacy. International organizations, like the Global Health Security Initiative (GHSI), have set guidelines for how to ethically collect data during health emergencies, but these standards really need to be applied across all forms of disaster monitoring. Another big ethical issue is the gap between wealthy and poorer countries when it comes to accessing disaster-related data. Wealthier nations often have advanced systems to gather and analyze data, while developing countries might not have the infrastructure or resources to do the same. This imbalance puts vulnerable populations at even greater risk. Closing this gap will require international cooperation, capacity-building efforts, and data-sharing agreements that make sure all countries have the tools they need to manage disaster risks effectively. Lastly, we also need to think about who owns the data and how it’s controlled. With more private companies getting involved in data collection—whether it’s through satellite imagery, telecoms, or AI-powered analytics—there are valid concerns about who actually owns that data and how it’s being used. Governments and international organizations need to set clear rules to ensure that disaster-related data remains a public resource, available to all, and used for the good of society as a whole.