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Information sharing for coordinated self-organisation in disasters
An agent-based modelling study
Fostering disaster resilience depends on effective coordination between diverse groups. At the same time, the volatile conditions of a disaster require different actors to self-organize in a decentralized way. While information sharing has been described as central to both coordination and self-organization, effective information management remains challenging during disasters, given shifting organizational patterns, evolving roles, changing information needs, and the high information load caused by volatility. This thesis addresses these challenges by analyzing coordinated self-organization through effective inter-group information exchange between communities and professional responders during disasters (1).
This thesis puts forward a way to systematically study disaster information sharing from an actor-centered perspective through a combination agent-based modeling and empirical case study research. It does so by developing a methodology to create Agent-Based Models (ABMs) for studying disaster information sharing through qualitative inquiry (2). This approach is chosen given the challenges of gathering quantitative data about disaster response (e.g., through surveys and disaster simulation exercises).
The methodology was applied to the case of Jakarta to develop an empirical descriptive ABM. Findings from case study research and simulations with this ABM show that, when actors are unaware of the information they need (i.e., their needs are latent), delivering information on time to them becomes particularly challenging. Further, the results show that communities tend to address a higher portion of their information needs compared to professional responders (3,2). Communities’ highly localized situational awareness needs to be combined with a more global perspective concerning a disaster and its development to foster effective coordination. To achieve this, a two-way communication between professional response organizations and communities is essential.
The empirical ABM was then extended and abstracted from the Jakarta case to develop a theoretical ABM to study the emergence of Informational Boundary Spanners (IBSs); i.e. of actors that facilitate inter-group information exchange. Findings from simulations with this ABM suggest that individually learning who provides high-quality information is a mechanism that fosters the emergence of IBSs (4). This collectively intelligent behavior is contingent on stable information sources and a high number of trusted inter-group connections among communities and professional response organizations, especially at high levels of volatility (4).
The methodology proposed in this thesis provided the means to systematically study actor-centered disaster information sharing. First, the methodology was found to be rigorous in translating qualitative data into ABMs, and to provide a way to balance cross-case comparability with the flexibility to capture the nuances of specific cases (1,2). Second, the methodology was found to be versatile in developing both empirical and theoretical ABMs to study actor centered disaster information sharing, including mechanisms leading to the emergence of intergroup information exchange during disasters (2,4).
Future research will focus on exploring synergies among coordinated self-organization, collective intelligence, and resilience beyond the context of disaster response, concentrating on how collective learning, sensing, and remembering can foster adaptive, transformative, and absorptive resilience capacities in both the short and long term.
...
This thesis puts forward a way to systematically study disaster information sharing from an actor-centered perspective through a combination agent-based modeling and empirical case study research. It does so by developing a methodology to create Agent-Based Models (ABMs) for studying disaster information sharing through qualitative inquiry (2). This approach is chosen given the challenges of gathering quantitative data about disaster response (e.g., through surveys and disaster simulation exercises).
The methodology was applied to the case of Jakarta to develop an empirical descriptive ABM. Findings from case study research and simulations with this ABM show that, when actors are unaware of the information they need (i.e., their needs are latent), delivering information on time to them becomes particularly challenging. Further, the results show that communities tend to address a higher portion of their information needs compared to professional responders (3,2). Communities’ highly localized situational awareness needs to be combined with a more global perspective concerning a disaster and its development to foster effective coordination. To achieve this, a two-way communication between professional response organizations and communities is essential.
The empirical ABM was then extended and abstracted from the Jakarta case to develop a theoretical ABM to study the emergence of Informational Boundary Spanners (IBSs); i.e. of actors that facilitate inter-group information exchange. Findings from simulations with this ABM suggest that individually learning who provides high-quality information is a mechanism that fosters the emergence of IBSs (4). This collectively intelligent behavior is contingent on stable information sources and a high number of trusted inter-group connections among communities and professional response organizations, especially at high levels of volatility (4).
The methodology proposed in this thesis provided the means to systematically study actor-centered disaster information sharing. First, the methodology was found to be rigorous in translating qualitative data into ABMs, and to provide a way to balance cross-case comparability with the flexibility to capture the nuances of specific cases (1,2). Second, the methodology was found to be versatile in developing both empirical and theoretical ABMs to study actor centered disaster information sharing, including mechanisms leading to the emergence of intergroup information exchange during disasters (2,4).
Future research will focus on exploring synergies among coordinated self-organization, collective intelligence, and resilience beyond the context of disaster response, concentrating on how collective learning, sensing, and remembering can foster adaptive, transformative, and absorptive resilience capacities in both the short and long term.
...
Fostering disaster resilience depends on effective coordination between diverse groups. At the same time, the volatile conditions of a disaster require different actors to self-organize in a decentralized way. While information sharing has been described as central to both coordination and self-organization, effective information management remains challenging during disasters, given shifting organizational patterns, evolving roles, changing information needs, and the high information load caused by volatility. This thesis addresses these challenges by analyzing coordinated self-organization through effective inter-group information exchange between communities and professional responders during disasters (1).
This thesis puts forward a way to systematically study disaster information sharing from an actor-centered perspective through a combination agent-based modeling and empirical case study research. It does so by developing a methodology to create Agent-Based Models (ABMs) for studying disaster information sharing through qualitative inquiry (2). This approach is chosen given the challenges of gathering quantitative data about disaster response (e.g., through surveys and disaster simulation exercises).
The methodology was applied to the case of Jakarta to develop an empirical descriptive ABM. Findings from case study research and simulations with this ABM show that, when actors are unaware of the information they need (i.e., their needs are latent), delivering information on time to them becomes particularly challenging. Further, the results show that communities tend to address a higher portion of their information needs compared to professional responders (3,2). Communities’ highly localized situational awareness needs to be combined with a more global perspective concerning a disaster and its development to foster effective coordination. To achieve this, a two-way communication between professional response organizations and communities is essential.
The empirical ABM was then extended and abstracted from the Jakarta case to develop a theoretical ABM to study the emergence of Informational Boundary Spanners (IBSs); i.e. of actors that facilitate inter-group information exchange. Findings from simulations with this ABM suggest that individually learning who provides high-quality information is a mechanism that fosters the emergence of IBSs (4). This collectively intelligent behavior is contingent on stable information sources and a high number of trusted inter-group connections among communities and professional response organizations, especially at high levels of volatility (4).
The methodology proposed in this thesis provided the means to systematically study actor-centered disaster information sharing. First, the methodology was found to be rigorous in translating qualitative data into ABMs, and to provide a way to balance cross-case comparability with the flexibility to capture the nuances of specific cases (1,2). Second, the methodology was found to be versatile in developing both empirical and theoretical ABMs to study actor centered disaster information sharing, including mechanisms leading to the emergence of intergroup information exchange during disasters (2,4).
Future research will focus on exploring synergies among coordinated self-organization, collective intelligence, and resilience beyond the context of disaster response, concentrating on how collective learning, sensing, and remembering can foster adaptive, transformative, and absorptive resilience capacities in both the short and long term.
This thesis puts forward a way to systematically study disaster information sharing from an actor-centered perspective through a combination agent-based modeling and empirical case study research. It does so by developing a methodology to create Agent-Based Models (ABMs) for studying disaster information sharing through qualitative inquiry (2). This approach is chosen given the challenges of gathering quantitative data about disaster response (e.g., through surveys and disaster simulation exercises).
The methodology was applied to the case of Jakarta to develop an empirical descriptive ABM. Findings from case study research and simulations with this ABM show that, when actors are unaware of the information they need (i.e., their needs are latent), delivering information on time to them becomes particularly challenging. Further, the results show that communities tend to address a higher portion of their information needs compared to professional responders (3,2). Communities’ highly localized situational awareness needs to be combined with a more global perspective concerning a disaster and its development to foster effective coordination. To achieve this, a two-way communication between professional response organizations and communities is essential.
The empirical ABM was then extended and abstracted from the Jakarta case to develop a theoretical ABM to study the emergence of Informational Boundary Spanners (IBSs); i.e. of actors that facilitate inter-group information exchange. Findings from simulations with this ABM suggest that individually learning who provides high-quality information is a mechanism that fosters the emergence of IBSs (4). This collectively intelligent behavior is contingent on stable information sources and a high number of trusted inter-group connections among communities and professional response organizations, especially at high levels of volatility (4).
The methodology proposed in this thesis provided the means to systematically study actor-centered disaster information sharing. First, the methodology was found to be rigorous in translating qualitative data into ABMs, and to provide a way to balance cross-case comparability with the flexibility to capture the nuances of specific cases (1,2). Second, the methodology was found to be versatile in developing both empirical and theoretical ABMs to study actor centered disaster information sharing, including mechanisms leading to the emergence of intergroup information exchange during disasters (2,4).
Future research will focus on exploring synergies among coordinated self-organization, collective intelligence, and resilience beyond the context of disaster response, concentrating on how collective learning, sensing, and remembering can foster adaptive, transformative, and absorptive resilience capacities in both the short and long term.
Qualitative research is a powerful means to capture human interactions and behavior. Although there are different methodologies to develop models based on qualitative research, a methodology is missing that enables to strike a balance between the comparability across cases provided by methodologies that rely on a common and context-independent framework and the flexibility to study any policy problem provided by methodologies that focus on capturing a case study without relying on a common framework. Additionally, a rigorous methodology is missing that enables the development of both theoretical and empirical models for supporting policy formulation and evaluation with respect to a specific policy problem. In this article, the authors propose a methodology targeting these gaps for ABMs in two stages. First, a novel conceptual framework centered on a particular policy problem is developed based on existing theories and qualitative insights from one or more case studies. Second, empirical or theoretical ABMs are developed based on the conceptual framework and generic models. This methodology is illustrated by an example application for disaster information management in Jakarta, resulting in an empirical descriptive agent-based model.
...
Qualitative research is a powerful means to capture human interactions and behavior. Although there are different methodologies to develop models based on qualitative research, a methodology is missing that enables to strike a balance between the comparability across cases provided by methodologies that rely on a common and context-independent framework and the flexibility to study any policy problem provided by methodologies that focus on capturing a case study without relying on a common framework. Additionally, a rigorous methodology is missing that enables the development of both theoretical and empirical models for supporting policy formulation and evaluation with respect to a specific policy problem. In this article, the authors propose a methodology targeting these gaps for ABMs in two stages. First, a novel conceptual framework centered on a particular policy problem is developed based on existing theories and qualitative insights from one or more case studies. Second, empirical or theoretical ABMs are developed based on the conceptual framework and generic models. This methodology is illustrated by an example application for disaster information management in Jakarta, resulting in an empirical descriptive agent-based model.
Agent-based models (ABM) for policy design need to be grounded in empirical data. While many ABMs rely on quantitative data such as surveys, much empirical research in the social sciences is based on qualitative research methods such as interviews or observations that are hard to translate into a set of quantitative rules, leading to a gap in the phenomena that ABM can explain. As such, there is a lack of a clear methodology to systematically develop ABMs for policy design on the basis of qualitative empirical research. In this paper, a two-stage methodology is proposed that takes an exploratory approach to the development of ABMs in socio-technical systems based on qualitative data. First, a conceptual framework centered on a particular policy design problem is developed based on empirical insights from one or more case studies. Second, the framework is used to guide the development of an ABM. This step is sensitive to the purpose of the model, which can be theoretical or empirical. The proposed methodology is illustrated by an application for disaster information management in Jakarta, resulting in an empirical descriptive ABM.
...
Agent-based models (ABM) for policy design need to be grounded in empirical data. While many ABMs rely on quantitative data such as surveys, much empirical research in the social sciences is based on qualitative research methods such as interviews or observations that are hard to translate into a set of quantitative rules, leading to a gap in the phenomena that ABM can explain. As such, there is a lack of a clear methodology to systematically develop ABMs for policy design on the basis of qualitative empirical research. In this paper, a two-stage methodology is proposed that takes an exploratory approach to the development of ABMs in socio-technical systems based on qualitative data. First, a conceptual framework centered on a particular policy design problem is developed based on empirical insights from one or more case studies. Second, the framework is used to guide the development of an ABM. This step is sensitive to the purpose of the model, which can be theoretical or empirical. The proposed methodology is illustrated by an application for disaster information management in Jakarta, resulting in an empirical descriptive ABM.
Towards coordinated self-organization
An actor-centered framework for the design of disaster management information systems
Traditionally, disaster management information systems have been designed to facilitate communication and coordination along stable hierarchical lines and roles. However, to support coordination in disaster response, disaster management information systems need to cater for the emerging roles, responsibilities and information needs of the actors, often referred to as self-organization. To address this challenge, this paper proposes a framework for disaster management information systems that embraces an actor-centered perspective to explicitly support coordination and self-organization. The framework is designed and validated to (i) analyze the current practice of disaster information management, including the way changes occur through self-organization, and (ii) study how to design disaster management information systems that support coordination and self-organization within the current practice. A case study in Jakarta is used to modify and validate the framework, and to illustrate its potential to capture self-organization in practice. The analysis showed that analyzing the actors’ activities through the framework can provide insights on the way self-organization occurs. Moreover, networking, preparedness and centralization were found to be key elements in the design of disaster management information systems with an actor-centered perspective.
...
Traditionally, disaster management information systems have been designed to facilitate communication and coordination along stable hierarchical lines and roles. However, to support coordination in disaster response, disaster management information systems need to cater for the emerging roles, responsibilities and information needs of the actors, often referred to as self-organization. To address this challenge, this paper proposes a framework for disaster management information systems that embraces an actor-centered perspective to explicitly support coordination and self-organization. The framework is designed and validated to (i) analyze the current practice of disaster information management, including the way changes occur through self-organization, and (ii) study how to design disaster management information systems that support coordination and self-organization within the current practice. A case study in Jakarta is used to modify and validate the framework, and to illustrate its potential to capture self-organization in practice. The analysis showed that analyzing the actors’ activities through the framework can provide insights on the way self-organization occurs. Moreover, networking, preparedness and centralization were found to be key elements in the design of disaster management information systems with an actor-centered perspective.
Designing Disaster Information Management Systems 2.0
Connecting communities and responders
Information and supporting information systems is a key element in an effective emergency response. From creating situational awareness to informed decision making, information enables responders to optimize their decisions and operations. Today, with the increased availability of information technology around the globe, a new active player in the field of information management is emerging as communities are becoming increasingly active in the field of information gathering, analyzing and sharing. However, communities may have specific requirements and approaches to using information systems in crisis situations. Moreover, connecting information systems between communities and responder pose specific challenges due to the different information needs, capacities and incentives to use them. In this paper we build on the DERMIS premises and explore through a case study if and how these principles apply to inclusive information systems. We present the initial findings of this work of designing information systems involving both communities and formal responders.
...
Information and supporting information systems is a key element in an effective emergency response. From creating situational awareness to informed decision making, information enables responders to optimize their decisions and operations. Today, with the increased availability of information technology around the globe, a new active player in the field of information management is emerging as communities are becoming increasingly active in the field of information gathering, analyzing and sharing. However, communities may have specific requirements and approaches to using information systems in crisis situations. Moreover, connecting information systems between communities and responder pose specific challenges due to the different information needs, capacities and incentives to use them. In this paper we build on the DERMIS premises and explore through a case study if and how these principles apply to inclusive information systems. We present the initial findings of this work of designing information systems involving both communities and formal responders.
The profusion of information technology has created new possibilities for local communities to self-organize and respond to disruptive events. Along with the opportunities, there is also a series of challenges that need to be addressed in order to improve societal resilience. One of these challenges is to make sense of the continuous stream of information to create a coherent understanding and improve coordination. The research presented in this paper focuses on the socio-technical requirements of IT platforms that support sensemaking and coordination. Using a comprehensive evaluation exercise based on real data from the 2017 Kenyan elections, we examine the development, workflows and use of this shared situational awareness in a group decision making process. In this manner, we identify requirements for resilience platforms and identify further research directions.
...
The profusion of information technology has created new possibilities for local communities to self-organize and respond to disruptive events. Along with the opportunities, there is also a series of challenges that need to be addressed in order to improve societal resilience. One of these challenges is to make sense of the continuous stream of information to create a coherent understanding and improve coordination. The research presented in this paper focuses on the socio-technical requirements of IT platforms that support sensemaking and coordination. Using a comprehensive evaluation exercise based on real data from the 2017 Kenyan elections, we examine the development, workflows and use of this shared situational awareness in a group decision making process. In this manner, we identify requirements for resilience platforms and identify further research directions.
The introduction of new information and communication technologies enables communities to share information and self-organize in the response to disasters. Crowd-sourcing approaches enable professional authorities to capture information from the ground in real-time. However, there is a gap between the professional and community-driven response: locally emergent initiatives may lack the overview needed for efficient coordination, while decisions taken by professionals may not consider the actual situation on the ground.
We study this information sharing and coordination gap through the lens of urban flood early warning and response systems. Based on a literature review combining academic articles as well as guidelines and reports from practice, we derive design principles for these systems. Considering the case study of Accra, specific requirements are individuated. The design principles are then used to address the requirements, resulting in a set of functionalities for a collaborative flood warning and response system. These functionalities provide the basis for further development and evaluation.
...
The introduction of new information and communication technologies enables communities to share information and self-organize in the response to disasters. Crowd-sourcing approaches enable professional authorities to capture information from the ground in real-time. However, there is a gap between the professional and community-driven response: locally emergent initiatives may lack the overview needed for efficient coordination, while decisions taken by professionals may not consider the actual situation on the ground.
We study this information sharing and coordination gap through the lens of urban flood early warning and response systems. Based on a literature review combining academic articles as well as guidelines and reports from practice, we derive design principles for these systems. Considering the case study of Accra, specific requirements are individuated. The design principles are then used to address the requirements, resulting in a set of functionalities for a collaborative flood warning and response system. These functionalities provide the basis for further development and evaluation.
Hurricane Harvey Report
A fact-finding effort in the direct aftermath of Hurricane Harvey in the Greater Houston Region
On August 25, 2017, Hurricane Harvey made landfall near Rockport, Texas as a Category 4 hurricane with maximum sustained winds of approximately 200 km/hour. Harvey caused severe damages in coastal Texas due to extreme winds and storm surge, but will go down in history for record-setting rainfall totals and flood-related damages. Across large portions of southeast Texas, rainfall totals during the six-day period between August 25 and 31, 2017 were amongst the highest ever recorded, causing flooding at an unprecedented scale. More than 100,000 residential properties are estimated to have been affected in southeast Texas. It is likely that Harvey will rank among the costliest storms in U.S. history.
In the wake of Hurricane Harvey, Delft University of Technology has initiated a Harvey Research Team to undertake a coordinated multidisciplinary investigation of the events with a focus on the greater Houston area. This ‘fact-finding’ research is based on information available from public sources during and in the first weeks after the event. Results are therefore preliminary, but aim to provide insight into lessons that can be learned for both Texas and the Netherlands. As part of the investigations, a hackathon with more than 80 participants was organized to collect and analyze available public information.
Houston was especially hard hit by flooding. During the event, all 22 watersheds in the greater Houston area experienced flooding. Many of Houston’s creeks and bayous exceeded their channel capacities, reaching water levels never before recorded. Across large portions of Harris County, rainfall totals exceeded the 1000-year return period. In addition, the water from the two reservoirs protecting downtown Houston (Addicks and Barker) were opened on August 28 to prevent catastrophic damages to the dams and further flooding in upstream communities. The releases exacerbated flooding in the areas downstream of the dams and an estimated 4,000 homes in neighborhoods downstream of the dams were impacted by flooding.
The consequences of the event in the greater Houston area have been characterized in terms of economic damages, loss of life and impacts on critical infrastructure, airports and industry. In total, more than 100,000 homes were affected more than 70 fatalities were reported in the greater Houston area. The event highlighted the vulnerability of industrial facilities, as several cascading impacts (releases of toxic materials and explosions) were reported.
Emergency response has been assessed. No large-scale mandatory evacuation was ordered before or during Harvey. However, it appeared that several local evacuations were ordered for areas with specific risks and circumstances. During the event, many people were trapped by rising waters necessitating a major rescue operation. In total, more than 10,000 rescues were made by professional and volunteer rescuers. Social media played an important role during the event and recovery, as an additional source of information, to inform emergency managers and as a means to organize community response e.g. for clean-up. Also, messages were conveyed through social media, e.g. a report of a levee breach that appeared to be incorrect afterwards.
Major flooding is a problem that has multiple causes from both physical and social origin. Based on the investigations, recommendations for future research and lessons for flood management have been formulated. A better understanding of the issues studied in this report is expected to contribute to a knowledge basis for further in-depth investigations and future directions for flood risk reduction.
Data collection and Report production funded by DIMI and DSys
Special Case 'Houston Galveston Bay Region, Texas, USA'
Project 'Harvey hackathon' and follow-up research
...
On August 25, 2017, Hurricane Harvey made landfall near Rockport, Texas as a Category 4 hurricane with maximum sustained winds of approximately 200 km/hour. Harvey caused severe damages in coastal Texas due to extreme winds and storm surge, but will go down in history for record-setting rainfall totals and flood-related damages. Across large portions of southeast Texas, rainfall totals during the six-day period between August 25 and 31, 2017 were amongst the highest ever recorded, causing flooding at an unprecedented scale. More than 100,000 residential properties are estimated to have been affected in southeast Texas. It is likely that Harvey will rank among the costliest storms in U.S. history.
In the wake of Hurricane Harvey, Delft University of Technology has initiated a Harvey Research Team to undertake a coordinated multidisciplinary investigation of the events with a focus on the greater Houston area. This ‘fact-finding’ research is based on information available from public sources during and in the first weeks after the event. Results are therefore preliminary, but aim to provide insight into lessons that can be learned for both Texas and the Netherlands. As part of the investigations, a hackathon with more than 80 participants was organized to collect and analyze available public information.
Houston was especially hard hit by flooding. During the event, all 22 watersheds in the greater Houston area experienced flooding. Many of Houston’s creeks and bayous exceeded their channel capacities, reaching water levels never before recorded. Across large portions of Harris County, rainfall totals exceeded the 1000-year return period. In addition, the water from the two reservoirs protecting downtown Houston (Addicks and Barker) were opened on August 28 to prevent catastrophic damages to the dams and further flooding in upstream communities. The releases exacerbated flooding in the areas downstream of the dams and an estimated 4,000 homes in neighborhoods downstream of the dams were impacted by flooding.
The consequences of the event in the greater Houston area have been characterized in terms of economic damages, loss of life and impacts on critical infrastructure, airports and industry. In total, more than 100,000 homes were affected more than 70 fatalities were reported in the greater Houston area. The event highlighted the vulnerability of industrial facilities, as several cascading impacts (releases of toxic materials and explosions) were reported.
Emergency response has been assessed. No large-scale mandatory evacuation was ordered before or during Harvey. However, it appeared that several local evacuations were ordered for areas with specific risks and circumstances. During the event, many people were trapped by rising waters necessitating a major rescue operation. In total, more than 10,000 rescues were made by professional and volunteer rescuers. Social media played an important role during the event and recovery, as an additional source of information, to inform emergency managers and as a means to organize community response e.g. for clean-up. Also, messages were conveyed through social media, e.g. a report of a levee breach that appeared to be incorrect afterwards.
Major flooding is a problem that has multiple causes from both physical and social origin. Based on the investigations, recommendations for future research and lessons for flood management have been formulated. A better understanding of the issues studied in this report is expected to contribute to a knowledge basis for further in-depth investigations and future directions for flood risk reduction.
Data collection and Report production funded by DIMI and DSys
Special Case 'Houston Galveston Bay Region, Texas, USA'
Project 'Harvey hackathon' and follow-up research