cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-e09d-1988
title: Conducting Interviews with Individuals Living with Intellectual Disabilities—CONVERGE Extreme Events Research Check Sheets Series

description: This check sheet emphasizes the importance of making research inclusive of individuals with intellectual disabilities. Considerations for ensuring effective and accessible interviews are provided, including a description of the Evaluation to Sign Consent tool for determining an individual’s capacity to provide consent.  About the CONVERGE Extreme Events Research Check Sheets Series: The National Science Foundation-supported CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder has developed a series of short, graphical check sheets that are meant to be used as researchers design their studies, prepare to enter the field, conduct field research, and exit the field. The series offers best practices for extreme events research and includes check sheets that are free to the research community. More information is available at: https://converge.colorado.edu/resources/check-sheets.
DOI: 10.17603/ds2-krz5-ej22
title: ARIO: Automated Reconnaissance Image Organizer

description: The Automated Reconnaissance Image Organizer (see link above) is an AI-based tool to rapidly organize post-event images collected by reconnaissance teams. In just a few minutes, our tool, a sort of "Netflix for Disaster Images" can organize thousands of images and make a structured inspection report for a concrete building to support reconnaissance teams. Generated reports are private, and they can also be shared with the rest of the users in the platform and unshared at any time.
DOI: 10.17603/ds2-z5ra-2260
title: SimCenter Labeled Building Facades from Street View

description: We present an annotated dataset to advance the efficacy of object recognition of building facades in the context of street scene understanding for analysis of natural hazards on the built environment. We gathered images of complex street scenes containing building objects in their natural context. To aid in precise object localization, per-instance bounding boxes are used to label building components, including windows, doors, garages, chimneys, and stairs, which are easily recognizable. A total of 167,366 instances are labeled in 15,233 images. We present a detailed analysis of the dataset.
DOI: 10.17603/ds2-01j1-0n51
title: A deep learning approach for rapid detection of soil liquefaction using time–frequency images
title: in A deep learning approach for rapid detection of soil liquefaction using time-frequency images

description: Soil liquefaction – a common hazard during earthquakes – can cause severe damage to infrastructure systems. The excessive pore water pressure induced by underground shaking can result in a sudden loss of soil stiffness and strength, which renders the soil–water mixture to behave temporarily as “liquid”. Identifying liquefaction events and extracting their time of initiation and duration from recorded data are critical capabilities for validating and improving predictive models, and ultimately, effectively mitigating this hazard. The current approach is to conduct on-site investigations or simplified statistical analyses, which are generally time-consuming and bear high uncertainties, except for the most obvious cases. In this study, we utilize a convolutional neural network (CNN), a deep learning method, to predict both the occurrence of a liquefaction event and its triggering time (if it occurred). For this purpose, first, more than one million high-fidelity nonlinear site response simulations with different soil profiles and ground motions are performed. The surface acceleration time-histories are then converted into time–frequency distribution images, which are fed into a CNN as the training inputs. The trained CNN exhibits high prediction accuracy for both training and validation sets, another suite of independent site response simulations, as well as real-life earthquake data.
description: In this project, we utilize a convolutional neural network (CNN), with the help of time-frequency images of surface accelerations, to predict both the occurrence of a liquefaction event and its triggering time (if it occurred). The trained CNN exhibits high prediction accuracy for both training and validation sets, another suite of independent site response simulations, as well as real-life earthquake data. User can simply apply our trained CNN model to the rapid liquefaction prediction and post-event hazard assessment.
DOI: 10.17603/ds2-1wrw-3631
title: EERI 2023
title: in EERI 2023

description: TLS training dataset collected during the 2023 EERI meeting.
description: RAPID training at the 2023 EERI meeting in San Francisco. This training focused on TLS data collection in an urban environment with the RTC360 and P50.
DOI: 10.17603/ds2-5g4s-0d41
title: X-ray fluorescence and specific gravity
title: in Characterization and Geotechnical Properties of Wildfire Ashes

description: X-ray fluorescence testing was performed at Boral Resources (Taylorsville, GA) by fusing ignited ash with a flux. To remove organics and volatile materials from the sample, samples were ignited in a muffle furnace to 950°C for two hours before infusing with a fusion matrix and testing. Then the samples were exposed to x-rays, and the fluorescence allowed for the measurement of the relative percentage of the inorganic constituents (e.g., calcium, magnesium, iron, and silica). Specific gravity of ash was tested using a helium pycnometer.
description: This project summarizes the geotechnical engineering properties of eight samples of wildfire ash sampled from three different wildfire sites in central and southern California. This data can be used in conjunction with data collected from others to provide a database of the physical, chemical, hydrological, and engineering properties of wildfire ashes. Extensive engineering testing of wildfire ashes is not readily available in literature, so this work will supplement the supply currently available. This work would be information and educational for those researching wildfire ashes, fire-exposed slopes, carbonate-rich soils, and manmade soils, including other types of ash. This data can be reused by those who would like reference data for further testing on wildfire ashes and for those who require reference data on soil engineering properties.
DOI: 10.17603/ds2-6vmy-n836
title: Natural Hazards Research Summit 2022: Data-driven machine learning predictions of multi-hazard hurricane damage to buildings

description: The study presented here uses a data-driven machine learning framework that incorporates loading onto buildings via hurricane wind and surge intensity, load propagation through geospatial features, and load resistance dependent on building components. This framework was applied to a case study of hurricanes Harvey, Irma, Michael, and Laura, which draws from reconnaissance data and observed hazard intensities to hindcast categorical damage states to buildings affected by these hurricanes with 76% accuracy. Variations of the case study further demonstrate favorable performance compared to existing frameworks, identify which features enable accurate predictions, and demonstrate the capacity for increased performance as more reconnaissance data becomes available.
DOI: 10.17603/ds2-e0tv-4q57
title: Loss on ignition testing
title: in Characterization and Geotechnical Properties of Wildfire Ashes

description: This project summarizes the geotechnical engineering properties of eight samples of wildfire ash sampled from three different wildfire sites in central and southern California. This data can be used in conjunction with data collected from others to provide a database of the physical, chemical, hydrological, and engineering properties of wildfire ashes. Extensive engineering testing of wildfire ashes is not readily available in literature, so this work will supplement the supply currently available. This work would be information and educational for those researching wildfire ashes, fire-exposed slopes, carbonate-rich soils, and manmade soils, including other types of ash. This data can be reused by those who would like reference data for further testing on wildfire ashes and for those who require reference data on soil engineering properties.
description: The total combustible material present in wildfire ashes was investigated. The loss on ignition (LOI) testing was performed in two stages to isolate the combustion of unburned organic carbon and the decomposition of carbonates and other volatile mineral phases. Firstly, the combustion of organic carbon phases occurred by heating the samples in a muffle furnace (Lindberg Blue M) to 500°C for 2 hours. Then, the samples were cooled and weighed for total organic carbon (TOC) lost. The samples were placed back into the furnace and heated further to 950°C for 2 hours. Cooled samples were weighed again, and the TOC and LOI were determined.
DOI: 10.17603/ds2-e21h-ry96
title: Research Experiences for Undergraduates (REU), NHERI 2023: Language and Disaster: Linguistic Inaccessibility in Disaster Recovery Planning and Its Impacts on Mexican-Origin Women and Community-Based Organizations.

description: This study analyzes the impact of language inaccessibility in disaster recovery planning on Mexican-origin women and community-based organizations (CBOs) in Houston, Texas after Hurricane Harvey. By performing a Critical Document Analysis of disaster recovery planning and policy documents, as well as a Code-Document and Code-Cooccurrence Analysis of interviews with CBO’s and Mexican-origin women. While the data is not shared in this publication, the analysis of said data may be used to inform and change disaster recovery policy in Houston, Texas. This study reveals the challenges faced and strategies employed at the community level to overcome linguistic barriers. Policy, decision-makers, and main stakeholders are the intended audience.
DOI: 10.17603/ds2-1fcj-p013
title: Microtremor Horizontal-to-Vertical Spectral Ratio (mHVSR) Data Collection at Searles Lake, 2023
title: in Microtremor Horizontal-to-Vertical Spectral Ratio (mHVSR) Site Characterization of California Vertical Arrays

description: The Searles Valley Basin consists of a large endorheic dry lake which contains sediments such as Borax and rock salt, which formed around the late quaternary period. This lakebed exhibited surface manifestation of liquefaction in the form of sand boils in different areas around the lake, following the Ridgecrest Earthquake sequence (RES) on July 4-5, 2019. In an effort to better understand amplification of earthquake ground motions at the site, microtremor Horizontal-to-Vertical-Spectral-Ratios(mHVSR) surveys were performed. The information that these surveys provide can give us insight on site resonances which are anticipated to be significant due to large impedance contrasts. Moreover, we can better understand the geology when multiple surveys are evaluated at different areas around the site. Collaborative research between the University of California, Los Angeles (UCLA) and University of Southern California (USC) has performed mHVSR surveys at 5 sites in the lakebed, close to the sand boils which occurred after the RES. The HVSR curves developed using this dataset may be accessed in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://uclageo.com/VPDB/). This work was supported by the United States Geological Survey under contract G22AP00320.
description: The microtremor Horizontal-to-Vertical spectral ratio (mHVSR) method provides frequency-dependent ratios of Fourier amplitude spectra (FAS) for the horizontal to vertical components of a 3-component recording of ambient ground motions (typically velocities) from microtremors. This method can identify the frequencies associated with site resonances at sites with large impedance contrasts, and hence has potential to provide useful parameters for predicting seismic site response. The mHVSR method is applied by recording ground vibrations either from a temporarily-deployed seismometer, typically recording for a relatively short period of time (~1-2 hrs.), or from a permanently-installed broadband seismometer. It is also useful for studying the spatial, temporal, and azimuthal variation of ground vibrations at sites.

The overall goals of our HVSR research are to develop a publicly accessible database of HVSR data for use in research, to develop effective protocols for analysis and interpretation of HVSR data, and to develop methods for predicting site response conditioned on HVSR data. The database has been established and is available in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://uclageo.com/VPDB/); the work presented in this doi is contributing to that database.
DOI: 10.17603/ds2-fpkz-tz94
title: Web Application for Visualization of LEAP-2022 Centrifuge Data and their Comparisons with User-Generated Numerical Simulations

description: This project provides a web application created using a Python-based code to visualize the results of centrifuge tests conducted as part of LEAP-GWU-2022 (See the link to the data in Related Data and Software). The web application prompts the user to select a participating university and one of the centrifuge tests conducted at that university. Then, the application displays time histories of accelerations, dynamic excess pore water pressure and/or earth pressure on the wall, lateral displacement of the sheet-pile wall at ground surface and settlements at predefined locations. In addition, the web application displays figures of deformed shape of the sheet pile wall and the available CPT data for each centrifuge test. Users can also add their numerical simulations of the same test and display comparisons of experimental versus numerically simulated accelerations, pore water pressures, lateral displacement of the sheet pile wall at ground surface and backfill settlements at predefined locations. The web application also provides the option of creating a PDF file that includes all the generated figures.
DOI: 10.17603/ds2-wpfr-4v13
title: Acceleration time series at depth for 21 seismic stations in California: Application of the double convolution methodology

description: Numerical simulations (nonlinear dynamic analyses) are increasingly used to assess structures for design purposes and for the forensic evaluation of past earthquake-induced failures. These simulations require input ground motions to be applied at the top of a stiff layer underlying a soil deposit of interest. The lack of ground motion recordings for these analyses, particularly in poorly instrumented regions, leads to the use of inappropriate ground motions in numerical simulations. To address this problem, the authors presented the double convolution methodology, a practical approach used to modify ground motion recordings to be consistent with conditions at some depth and thus be used as input ground motions. This dataset consists of results from the double convolution methodology for 21 top-of-soil seismic stations from the Center for Strong Motion Data (CESMD). Recorded and modified ground motions are presented, as well as associated data, metadata, and shear-wave velocity (Vs) profiles used in the double convolution methodology. This project is useful for anyone looking to use motions at these locations and propagate them upwards for their desirable application depth.
DOI: 10.17603/ds2-y5jp-ff88
title: Public Health Workforce COVID-19 Burnout

description: The COVID-19 pandemic resulted in a range of negative mental health impacts among the public health workforce. This study assesses reported experiences of burnout among public health practitioners from across the US.
DOI: 10.17603/ds2-hb4d-j458
title: Soil-Plate Interface Tests
title: in Development of an Innovative Ultra High Performance Concrete Foundation System with Bio-inspired Surfaces to Support Renewable Offshore Wind Turbines

description: The planned offshore wind energy (OWE) production in the U.S. has been growing rapidly with targets of 30 GW by 2030 and 110 GW by 2050 and strong support from coastal states. Achieving these targets requires cost-effective and innovative components including foundations, which could cost 14% to 34% of the overall project cost. Offshore wind turbines (OWTs) are commonly supported on large-diameter steel foundations (piles, anchors or suction caissons). Currently the U.S. does not have the capability to fabricate large diameter steel foundations supporting OWTs and instead relies on foundations fabricated abroad. Therefore, a U.S. manufactured foundation system to support renewable OWE infrastructure is required to meet the growing demand. The goal of this project was to develop a domestically fabricated, bio-inspired surface optimized Ultra High-Performance Concrete (UHPC) foundation system to support the growing renewable OWE infrastructure. This project represented the first phase which was focused on material properties, structural capacity of designed UHPC cross-sections, and the effects of surface elements on the soil-pile interaction when subjected to axial loading. The soil-pile interaction was investigated using plates with different designs of surface elements, small-scale piles and larger-scale pile tests subjected to axial loading.
description: Soil-Plate Interface Tests focus on determining the effects of different variables on the soil-foundation interface shear resistance.  These variables include the effect of surface design (asperity height, spacing, and spacing to height ratio).
DOI: 10.17603/ds2-sget-8e59
title: Research Experiences for Undergraduates (REU), NSF NHERI 2024: Assessment of Soil Liquefaction Potential in Portland, Oregon, with Cone Penetrometer Testing (CPT)

description: The focus of this poster, presentation, and paper is the assessment of liquefaction potential at a site in Portland, Oregon with cone penetrometer testing (CPT). The validity of CPT for evaluating liquefaction potential is examined and the results can be used to investigate the effectiveness of Microbially Induced Desaturation (MID), a method of liquefaction mitigation conducted at the site. This project is distinctive due to the application of CPT with the Large Scale Mobile Shakers in pursuit of establishing a base liquefaction potential to compare with an area treated with the liquefaction mitigation technique. This location is near the Portland airport, so the information regarding whether or not the area will liquefy would be crucial in the event of a high magnitude earthquake, which this area is vulnerable to. This research is of use to those interested in geotechnical engineering and seismic events, specifically the phenomenon of earthquake- triggered liquefaction.
DOI: 10.5517/ccdc.csd.cc2l0tct
title: CCDC 2384066: Experimental Crystal Structure Determination

description: Related Article: Luying Song, Yuhong Sun, Renbo An, Liming Wang, Ying Jin|2025|RSC Advances|15|17031|doi:10.1039/D5RA01633A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.mrj8qb
title: Occurrence Download

description: A dataset containing 135 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 COUNT(*) occurrences
FROM
 occurrence
WHERE
 (occurrence.taxonkey = 5210979 OR occurrence.acceptedtaxonkey = 5210979 OR occurrence.kingdomkey = 5210979 OR occurrence.phylumkey = 5210979 OR occurrence.classkey = 5210979 OR occurrence.orderkey = 5210979 OR occurrence.familykey = 5210979 OR occurrence.genuskey = 5210979 OR occurrence.specieskey = 5210979)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 135 records were derived from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015620-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21979/n9/6sh5j5
title: Understanding bending-induced loss and bending-induced higher-order modes suppression in negative curvature hollow core fiber

description: This dataset contains the data obtained from COMSOL Multiphysics Software used for the paper “Understanding bending-induced loss and bending-induced higher-order modes suppression in negative curvature hollow core fiber”
DOI: 10.15468/dl.u8d49n
title: Occurrence Download

description: A dataset containing 12730 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Banc de dades de biodiversitat de Catalunya-MolusCat"
 ]
}

 The dataset includes 12730 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001303-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4s7xqw
title: Occurrence Download

description: A dataset containing 5189 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Bhutan, Nepal, Pakistan, Afghanistan, Myanmar, Bangladesh)",
 "TaxonKey is Jamides"
 ]
}

 The dataset includes 5189 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049149-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dpat8c
title: Occurrence Download

description: A dataset containing 21136 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Scomber japonicus Houttuyn, 1782"
 ]
}

 The dataset includes 21136 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012979-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dymmy6
title: Occurrence Download

description: A dataset containing 21114177 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 21114177 records from 931 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001041-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18211006
title: CARTIO Protocol: Virtual Machine Images for x64 and ARM64 Architectures

description: This record contains the virtual machine disk images (OVA/VMDK) used to perform the reliability and binary synchronization experiments for the CARTIO protocol. It includes pre-configured environments for both node A (Provider) and node B (Consumer/Judge) across Intel/AMD (x64) and Apple Silicon (ARM64) architectures. These VMs are essential for full reproducibility of the thesis results.