cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-1kpb-dv70
title: NSF Belmont Forum Collaborative Research: Advancing Resilience in Low-Income Housing Using Climate-Change Science and Big Data Analytics

description: Project Overview:
This NSF-funded project (Award #2019754) is part of the Belmont Forum’s Disaster Risk, Reduction, and Resilience (DR3) initiative, a global effort to assess and mitigate disaster risks through transdisciplinary collaboration. The study investigates strategies to enhance the resilience of low-income communities living in flood-prone and climate-vulnerable regions, with a geographic focus on Brazil, East Africa, and the southeastern United States. The U.S. component centers on coastal and urban communities in Florida, particularly those at risk from flooding and extreme weather events.

Research Objectives:
Through a transdisciplinary approach, the project integrates machine learning, geospatial analytics, and socio-economic data to:
- Assess community-level vulnerabilities to flooding and extreme heat,
-Identify barriers to adopting disaster-resilient housing,
- Co-design affordable, climate-resilient housing prototypes using sustainable, locally sourced materials.
The research aims to support community-informed design strategies and policy recommendations that are adaptable across different socio-economic and geographic contexts.

Dataset Description:
The dataset contains responses from approximately 500 residents aged 18+ living in low-income, flood-prone neighborhoods in Florida. The survey captures detailed information on:
- Housing conditions and infrastructure,
- Disaster preparedness and flood risk perception,
- Access to services during and after disasters,
- Health and economic impacts of extreme weather events,
- Community cohesion and recovery strategies.
This dataset serves as a resource for researchers, urban planners, emergency response agencies, and policymakers seeking data-driven insights to inform resilient housing design, climate adaptation, and disaster recovery planning.

Data Collection and Anonymity:
Survey distribution and data collection were conducted in partnership with Centiment, a third-party research company that recruits demographically targeted panels for academic and applied research. For this study, Centiment distributed the survey to residents of low-income, flood-prone communities in Florida, based on geographic and socio-economic criteria specified by the research team.
All personally identifiable information (PII), such as IP addresses, email addresses, and precise geolocation data, was removed prior to uploading the dataset to DesignSafe. The dataset has been reviewed to ensure participant anonymity in accordance with DesignSafe data protection policies and applicable ethical standards.
DOI: 10.17603/ds2-agn5-fp46
title: A literature review of Identifying Barriers in the Entrepreneurial Ecosystem

description: This systematic review uses the PRISMA approach to address the technologies used in mentorship and some specific needs of entrepreneurs, such as mental health services in the sports field. In order to develop supportive resources to help entrepreneurs to build resilience capacity, a topic-based rapid literature review is needed. For example, what community-based resources could support the entrepreneurs and their team’s mental health and overall well-being, especially in the context of extreme events (e.g., COVID-19, hurricanes, and floods). Additionally, how can those in incubators and accelerators inform entrepreneurs of information to access the necessary resources to build their capacity for entrepreneurial resilience.
DOI: 10.17603/ds2-bx73-1893
title: Natural Hazards Research Summit 2024: Enhancing Urban Seismic Resilience: Integrating AI and Monte Carlo Methods for Real-Time Hazard Prediction

description: This poster presents an innovative approach to enhance the seismic resilience of urban water distribution systems by integrating Artificial Intelligence (AI) and Monte Carlo (MC) simulations. The primary goal is to develop an AI-driven framework that can process real-time seismic data to rapidly assess potential impacts on water distribution infrastructure. This framework utilizes machine learning models, trained on extensive datasets of seismic activity, geological information, and detailed characteristics of water systems, to predict the effects of seismic events as they unfold.
    A distinctive feature of this research is the application of Monte Carlo methods to introduce a probabilistic dimension to the predictions, quantifying uncertainties inherent in real-time seismic analysis. This feature is crucial in understanding the range of potential impacts on water distribution, thereby aiding emergency response planning with more nuanced, data-driven insights. The proposed research seeks to make a significant contribution to the field of seismic hazard analysis and emergency preparedness for urban water systems. By combining advanced AI modeling with probabilistic simulation techniques, the goal is to create a tool that enhances the capacity of urban centers to maintain water distribution services more effectively during seismic events, ultimately leading to more resilient and better-prepared urban environments.
DOI: 10.17603/ds2-e1yq-0s20
title: ISROC Dataset for: Using UAV and Structure-From-Motion Photogrammetry for the Detection of Boulder Movement by Storms on a Rocky Shore Platform in Laghdira, Northwest Morocco
title: in Inundation Signatures on Rocky Coastlines (ISROC) Global Coastal Boulder Deposits Datasets Version 1

description: This document contains standardized data as an Excel and NC file and explanatory notes for "Using UAV and Structure-From-Motion Photogrammetry for the Detection of Boulder Movement by Storms on a Rocky Shore Platform in Laghdira, Northwest Morocco." The project surveys 28 coastal boulder deposits in northwest Morocco. The study used unmanned aerial vehicles to highlight the possibilities of determining storm conditions to deposit and transport boulders.
description: This project is a collection of datasets on studies about coastal boulder deposits worldwide. Each document is a unique dataset that contains data from a published study. The document's name reflects the name of the associated paper, and all authors of papers are given credit in the respective document. Each dataset's data is standardized into an ISROC-formatted Excel and NC File. Also, every dataset has explanatory notes, which contain a data dictionary explaining data parameters and appropriate units, Some datasets have the raw data given to ISROC by the paper's authors. By creating a database in the public domain, ISROC hopes to promote academic collaboration in the field. ISROC, an NSF-funded research network, funds this project.
DOI: 10.17603/ds2-g8r1-gg85
title: Natural Hazards Research Summit 2024: Pulse-period–moment-magnitude relations derived with wavelet analysis and their relevance to estimate structural deformations

description: Motivated from the quadratic dependence of peak structural displacements to the pulse period, 𝑇𝑝, of pulse-like ground motions, this paper revisits the pulse-period – moment-magnitude (𝑇𝑝–𝑀w) relations of ground motions generated from recorded near-source ground motions with epicentral distances, 𝐷 ≤20 km. A total of 1260 ground motions are interrogated with wavelet analysis to identify energetic acceleration pulses (not velocity pulses) and extract their optimal period, 𝑇𝑝, amplitude, 𝑎𝑝, phase, 𝜙 and number of half-cycles, 𝛾. The interrogation of acceleration records with wavelet analysis is capable of extracting shorter duration distinguishable pulses with engineering significance, which override
the longer near-source pulses and they are not necessarily of random character. Our wavelet analysis identified 109 pulse-like records from normal faults, 188 pulse-like records from reverse faults and 125 pulse-like records from strike-slip faults, all with epicentral distances 𝐷 ≤ 20 km. Regression analysis on the extracted data concluded that the same 𝑇𝑝–𝑀w relation can be used for pulse-like ground motions generated either from strike-slip faults or from dip-slip normal faults; whereas, a different 𝑇𝑝–𝑀w relation is proposed for dip-slip reverse faults. The study concludes that for the same moment magnitude, 𝑀w, the pulse periods of ground motions generated from strike-slip faults are on average larger than these from reverse faults—a result that is in agreement with findings from past investigations. Most importantly, our wavelet analysis on acceleration records produces 𝑇𝑝–𝑀w relations with a slope that is lower than the slopes of the 𝑇𝑝–𝑀w relations presented by past investigators after merely fitting velocity pulses. As a result, our proposed 𝑇𝑝–𝑀w relations yield lower 𝑇𝑝 values for larger-magnitude earthquakes (say 𝑀w > 6), allowing for the estimation of dependable peak structural displacements that scale invariably with 𝑎𝑝𝑇𝑝^2.
DOI: 10.17603/ds2-j9hc-xy24
title: 2020 Hurricanes Laura and Marco predictive and post-storm survey instruments
title: in Public longitudinal panel surveys collected during and after hazardous weather threats: Hurricanes

description: These are novel datasets of longitudinal panel survey data (i.e., repeated surveys of the same people) when a hurricane is threatening and approaching landfall in the mainland U.S. and after the hurricane has dissipated. Three survey waves were collected pre-landfall when the hurricane was threatening (the threat / predictive phase), and one survey wave was collected post-storm (post landfall or dissipation). The three waves of data collected during the predictive phase measured what forecast and other risk information respondents were getting, respondents' risk perceptions, and respondents' protective behavioral responses, all pertaining to the hurricane risks at that time. The data collected during the post-storm wave correspondingly measured what forecast and other risk information was most useful and what people's actual experiences were with the hurricane. Such rapidly deployed, event-based, repeated-measure data for hurricanes are novel. This project includes datasets for the following hurricane events: Hurricanes Laura and Marco in 2020, Hurricane Henri in 2021, and Hurricane Ian in 2022.
description: These two survey instruments were developed and used to collect longitudinal panel survey data (i.e., repeated surveys of the same people) for Hurricanes Laura and Marco in 2020. The predictive waves survey instrument was rapidly deployed and fielded three times over the course of a few days as the hurricanes were threatening and approaching landfall. Each wave was fielded for approximately 18 to 24 hours with an 18- to 24-hour interval in between. The post-storm wave survey instrument was fielded one time after the hurricanes dissipated. It was fielded 8 days after the final predictive survey wave, and it was fielded for 11 days.
DOI: 10.17603/ds2-q5x1-4t21
title: Hurricane Irene 1999
title: in FCMP Ground Level Hurricane Wind Data (1999 - 2008)

description: The Florida Coastal Monitoring Program (FCMP) is a collaborative experimental effort to measure ground level hurricane surface winds. This publication provides data files of ground level wind speed and direction measured along the east coast of Florida during landfall of Hurricanes: Irene 1999,  Gordon 2000, Lili 2002, Charley 2004, Ivan 2004, Jeanne 2004, Dennis 2005, Katrina 2005, Rita 2005, Wilma 2005, Gustav 2008, Hanna 2008 and, Ike 2008. Urbanists, social scientists, structural engineers, and meteorologists, among others, can use these real wind speed measurements and directions in myriad disaster research and planning projects.
description: Portable weather stations were deployed along the coast to collect wind observations. This publication provides data files of ground level wind speed and direction measured along the coast during landfall of Hurricane Irene 1999.
DOI: 10.17603/ds2-vsz3-ar63
title: 2023 GeoCongress Meeting
title: in GEER 1-day training

description: Training RTC360 dataset created at the 2023 GeoCongress meeting at UCLA.
description: RTC360 training data collected at the 2023 GeoCongress meeting at UCLA.
DOI: 10.17603/ds2-w533-0n80
title:  2D ADCIRC simulation of tidal flow in Shinnecock Inlet, NY parameterized by bottom friction coefficient
title: in A neural operator-based emulator for regional shallow water dynamics

description: This dataset curates a series of ADCIRC simulations of tidal hydrodynamics in the vicinity of Shinnecock Inlet, a geographical feature located along the outer shore of Long Island, New York. The simulation utilizes a finite element grid containing 5780 elements and 3070 nodes, with the grid discretization varying from approximately 2 km offshore to around 75 m near the inlet and near-shore areas. The model uses an off-shore open boundary with prescribed elevations and a mainland boundary with zero normal flow. The model is forced using tidal elevations at the open boundary from 5 tidal constituents (M2, S2, N2, O1, K1), ramped up over the first two days from a state of rest. Quadratic friction forcing is applied and wetting/drying is neglected. The simulation duration is 60 days with a 6-second time step, while water level and velocity fields are output every 30 minutes. The simulation data is parametrized by varying the scalar bottom friction coefficient between 0.0025 and 0.1.

This dataset accompanies the paper published with the title "A neural operator-based emulator for regional shallow water dynamics". 
description: Coastal regions are particularly vulnerable to the impacts of rising sea levels and extreme weather events. Accurate real-time forecasting of hydrodynamic processes in these areas is essential for infrastructure planning and climate adaptation. In this study, we present the Multiple-Input Temporal Operator Network (MITONet), a novel autoregressive neural emulator that employs dimensionality reduction to efficiently approximate high-dimensional numerical solvers for complex, nonlinear problems that are governed by time-dependent, parameterized partial differential equations. While MITONet is applicable to a wide range of problems, we demonstrate its capabilities by forecasting regional tide-driven dynamics described by the two-dimensional shallow-water equations. This approach incorporates initial conditions, boundary conditions, and varying domain parameters. We demonstrate MITONet's performance in a real-world application, highlighting its ability to make accurate predictions by extrapolating both in time and parametric space.
DOI: 10.17603/ds2-zb94-7998
title: Interview protocols for interviews
title: in Interviews with residents of the Southeast U.S. to understand perceptions of evolving probabilistic tornado forecasts

description: The interview protocols used in the interviews. The Non-warn-on version was used for two scenarios of the interviews and the Warn-on version was used in one of the scenarios. The protocols were the same across the four locations used. 
description: We employed qualitative interview methods and a quantitative survey, as a follow-up to previously completed behavioral-experimental studies, to understand interpretation and use of evolving probabilistic tornado forecast information by members of the public in the southeastern U.S. This project includes all materials used for the interviews: The interview protocols with our internal notes, the graphics used, and the full questionnaire. 

Note, this study used a conditional design that included three different forecast scenarios and four different hypothetical locations. There are two different protocols, one for the scenario that included three types of forecast information and one for the scenarios that included two types of forecast information. The graphics for all scenarios and locations are also included in one file.
DOI: 10.17603/ds2-7mtk-sy78
title: Research Experiences for Undergraduates (REU), NSF NHERI 2024: Vertical Pressure Distribution of Tsunami-like Wave Impact on an Impervious Column

description: The purpose of this paper is to further understand the forces that tsunami waves exert on coastal structures and the subsequent scour that occurs in the surrounding sediment bed, as this is often the main source of failure during or following a tsunami event. Due to the inherent gap in tsunami research caused by the difficulty of scaled experimentation as well as the danger and unpredictability of field data collection, there is a knowledge gap in scour mechanisms. Understanding scour allows the development of new protections and modification of existing coastal structures to boost overall resiliency in susceptible communities. In this study the impact of waves on a structural column was experimentally evaluated and compared based on varying wave heights. This project is unique in the fact that it is a large scale representation of a square cross-section structure. Many studies focus on cylindrical structures, however scour interacts differently with sharp corners. The ultimate goal of the project is to create public domain data regarding scour interactions in an effort to provide resources to coastal communities. The pressure data evaluated in this paper can be further studied in combination with the multiple data types collected during experimentation in order to fully understand the relationship between force of wave impact, scour mechanisms, and potential foundation failure.
DOI: 10.17603/ds2-8ywr-y655
title: Survey Instrument for Decision-Making and Evacuation for Hurricane Ida with Variations Used for Hurricanes Florence, Michael, Barry, Dorian, Ian, and Idalia

description: This survey is designed to capture information about people's behavior in hurricane evacuation across 4 sections: location at the time of the disaster, evacuation behavior, evacuation decisions and related reasoning, and household attributes. This survey can be reused by other researchers looking to capture similar data across other hurricanes. This work is unique in capturing this range of data related to decision making and timing for investigation in individual hurricanes and for comparison there with other types of data, as well as for comparison across different hurricanes. The goal of such efforts is to support better understandings of evacuation decision making, movement, and timing by researchers and practitioners.
DOI: 10.17603/ds2-hgvq-6m15
title: Axial resistance of pipelines with enlarged joints
title: in Geotechnical Demands for Characterizing Performance of Pipeline Systems with Enlarged Components

description: The project included a series of centrifuge experiments performed at CU Boulder's Center for Infrastructure, Energy, and Space Testing. The 15 g-ton centrifuge was used to test n=12.5 reduced scale pipelines with enlarged joints that act as anchors in the ground. Axial movement was applied to the pipelines with various geometric variables adjusted to characterize the additional frictional resistance of enlarged joints common in hazard resilient pipeline systems.
description: Axial pipe pull tests were conducted on pipe and joint models to investigate the influence of key variables (burial depth and joint diameter) on the pull force. Model pipes were assembled with multiple joint diameters, buried at various burial depths, and pulled through the soil mass to measure the passive pressures that develop at the joint face. These results demonstrated the relationship between burial depth and joint diameter with the developed passive pressures. The data, force-displacement curves, can be reused to know the magnitude of passive pressures accumulating for a specific combination of burial depth and joint diameter.
DOI: 10.17603/ds2-xrre-y741
title: Experimental Study of Wave Runup Variability on a Dissipative Beach
title: in Runups of Unusual Size: Predicting Unexpectedly Large Swash Events

description: This project investigated the effects of wave sequencing on wave runup on a dissipative beach. Multiple bichromatic waves conditions varying in carrier wave height, carrier wave period, and group wave period were tested on a 1:36 sloped flume. Water surface elevations at offshore and nearshore regions were collected. In addition, video footage of the nearshore region were captured. The data in this project can be reused for various analysis of bichromatic waves and/or wave runup on dissipative beach. The project is unique in that each scenario contains a wide range of wave sequencing within each wave group, and that the component wave frequencies were chosen so that the infragravity waves can be precisely isolated. This project's ideal audience are researchers interested in nearshore hydrodynamics leading to wave runup.
description: We generated bichromatic waves of varying wave heights, carrier wave periods, and group wave periods on a mostly 1:36 sloped bottom, and measured water surface elevations at offshore and nearshore locations. In addition to the majority bichromatic scenarios, we also tested a few random waves scenarios. Video footages were also taken at the nearshore to facilitate extraction of wave runup time series. 'Preliminary tests' denote the first phase of the experiment, during which we tested the feasibility of creating bore-merging events, which were a focus of this study. The 'final scenarios' consist of measurements used in the data analysis associated with the manuscript.
DOI: 10.17603/ds2-zzv9-vb11
title: Research Experiences for Undergraduates (REU), NSF NHERI 2024: Rate of Consolidation in Fine-Grained Willamette Silt

description: This project is about the rate of consolidation in fine-grained Willamette Silt and how this affects permeability of the silt, along with consolidation time. This data can be reused if others wish to also test silt within the centrifuge and need to see if they will have enough time to spin. This data will also be used in later research by Earl Parrott for his testing within the centrifuge. This project is unique as there is limited research on silt done in the 9m centrifuge and this develops testing on time needed for consolidation needed within the centrifuge. The audience are those that wish to have silt within their model containers for testing in the 9m centrifuge
DOI: 10.17603/ds2-2kh8-f472
title: Camp Wildfire Reconnaissance - Spring 2019
title: in Camp Wildfires Reconnaissance-Spring 2019

description: This project collected data on the damage of schools and the hospital in Paradise, CA due to the 2018 Camp Fire. The project further evaluated the impact of that damage on the town itself. The goals of this project was to understand how to use drones, LiDAR, and field measurements to evaluate the impact of wildfire on engineered buildings. The data from this project can be used to measure deformations of buildings - local and global - due to fire, extent of damage and rate of recovery can be evaluated from the google street view data, and evaluating the burn severity of mitigated and unmitigated forests can be calculated using drone footage.  The data within this project is just the engineering data.
description: Data on damage to metal buildings, timber buildings, and concrete buildings was collected to quantify the local and global damage of the structure. This data was collected through a combination of LiDAR and UAS. UAS was then used to collect data on the wildland that surrounded Pine Ridge Elementary school to show the difference in burn severity between mitigated and unmitigated forest. Specifically, the following methods were used to gather data:

LiDAR and UAS data captured at Achieve Charter High School (metal building structure); LiDAR data of a Safeway in Paradise, CA;  UAS data collected at Pine Ridge Elementary School; LiDAR and UAS data captured at Adventist Health Hospital; LiDAR data of a residential concrete structure on Berkshire Way (previously Burke Ln); and LiDAR and UAS data captured at Ponderosa Pine Elementary School. LiDAR was collected by means of Terrestrial Laser Scanning (TLS) and UAS data was created through the use of SfM (Structure from Motion) by drones.