cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31046065.v1
title: Risk Management assessment of social sustainability in supply chains: a Bayesian Network model proposal

description: Recently, the social dimension of sustainability has become a focal point for academia and practitioners. Despite this growing attention, several unresolved challenges still exist within supply chain management (SCM), limiting the attainment of satisfactory levels of sustainability. This study fills this gap by proposing a Bayesian Network (BN) model, an Artificial Intelligence (AI) technique, for assessing the risk probability related to the social dimension of sustainability in supplier contracting. This novel approach utilises BN model incorporating the Human Development Index (HDI) and Global Slavery Index (GSI) to ascertain the likelihood of non-compliance risks in social aspects across apparel supply chains. Findings and testing of the BN model in apparel industry revealed that this model represents a proactive tool for decision-makers and practitioners by facilitating the monitoring and control of social burdens across SC tiers. Empirical analysis successfully identified the risk probability levels of non-compliance integrating company-specific data and external sources. The BN model offers a comprehensive understanding of the supply chain to mitigate a company’s risk and leverage its transparency regarding the social dimension of sustainability. The BN model offers an essential resource for practitioners, decision-makers, and academia to address more effectively the social dimension of sustainability in the SCM.
DOI: 10.7910/dvn/blm4jx
title: Replication Data for: “Identification of Semiparametric Panel Multinomial Choice Models with Infinite-Dimensional Fixed Effects”

description: Review of Economics and Statistics: Forthcoming
DOI: 10.15468/dl.tubgub
title: Occurrence Download

description: A dataset containing 120346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Erigeron sumatrensis"
 ]
}

 The dataset includes 120346 records from 1105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002504-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ktk8xy
title: Occurrence Download

description: A dataset containing 92356 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Hypericum perforatum L.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 92356 records from 420 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009724-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ja8fk
title: Occurrence Download

description: A dataset listing the 132038 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "Year 1981-2025"
 ]
}

 The dataset's 132038 records were derived from 3834 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013610-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpkpnj
title: Occurrence Download

description: A dataset containing 3125 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fagus crenata Blume",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2010",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3125 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003870-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17603/ds2-0mg2-3669
title: U.S. County-Level Power Reliability

description: This dataset presents information related to the power reliability of distribution utilities and power marketers of electricity collected from the U.S. Energy Information Administration (EIA) - 861 Annual Electric Power Industry Report. The survey covers more than 3,600 utility firms in over 3,200 U.S. counties between 2013 and 2020. For each utility, detailed information on three metrics of power interruption is provided: (1) System Average Interruption Duration Index (SAIDI) measures the minutes of non-momentary electric power interruptions per year the average customer experienced, (2) System Average Interruption Frequency Index (SAIFI) measures the number of non-momentary electric power interruptions per year the average customer experienced, and (3) Customer Average Interruption Duration Index (CAIDI) measures the average number of minutes it takes to restore non-momentary electric power interruptions. All three reliability measures are reported in two forms, depending on whether to include Major Event Days (MED) or not. We clean and aggregate utility responses contained in the report by taking the weighted sum of utility-level measures using their market shares as weights to provide measures of power reliability at the U.S. county-level. Specifically, the dataset includes information on the county-level measures of SAIDI, SAIFI, and CAIDI from 2013 to 2020. Additionally, we separate SAIDI into Minor SAIDI (SAIDI without MED) and Major SAIDI (SAIDI less Minor SAIDI) to better understand the differences between power interruptions due to major events and interruptions that are more consistent with normal operations. Missing data suggests that no utility provider within that county/year self-reported their power reliability information.
DOI: 10.17603/ds2h68m
title: CU1, CU2 - University of Cambridge Experiments, in PRJ-1843: LEAP-UCD-2017
title: in LEAP-UCD-2017 Experiments (Liquefaction Experiments and Analysis Projects)

description: Twenty-four centrifuge model tests of liquefaction and lateral spreading, performed as part of a round robin test program, are shared and compared in this archive. Please see the general report section of the published project for an overview comparison and background of all of the experiments. One document in the report (with “ReadMe” in the file name) describes the organization of the data archive. The comparisons presented in the general report section will serve as an index to help the users find individual experiments of interest.  This data from 24 model tests is published as nine separate experiments in this archive (one experiment per centrifuge facility). Each "experiment" includes two or three model tests and each model test includes between one and three destructive shaking events.
All of the tests modeled a 4 m thick deposit of Ottawa F-65 sand with a 5-degree surface slope in a rigid box. The tests covered a range of ground motion intensities and a range of relative densities to define the median response and the sensitivity of the response to relative density and shaking intensity. The nine centrifuge facilities involved in this test program included Cambridge University (UK), Ehime University (Japan), IFSTTAR (France), NCU (Taiwan), KAIST (Korea), Kyoto University (Japan), RPI (USA), UC Davis (USA), and Zhejiang University (China).
description: Lateral spreading of a submerged slope for LEAP-UCD-2017
DOI: 10.17603/ds2m11v
title: UCD1, UCD2 and UCD3 - UC Davis Experiments, in PRJ-1843: LEAP-UCD-2017
title: in LEAP-UCD-2017 Experiments (Liquefaction Experiments and Analysis Projects)

description: Twenty-four centrifuge model tests of liquefaction and lateral spreading, performed as part of a round robin test program, are shared and compared in this archive. Please see the general report section of the published project for an overview comparison and background of all of the experiments. One document in the report (with “ReadMe” in the file name) describes the organization of the data archive. The comparisons presented in the general report section will serve as an index to help the users find individual experiments of interest.  This data from 24 model tests is published as nine separate experiments in this archive (one experiment per centrifuge facility). Each "experiment" includes two or three model tests and each model test includes between one and three destructive shaking events.
All of the tests modeled a 4 m thick deposit of Ottawa F-65 sand with a 5-degree surface slope in a rigid box. The tests covered a range of ground motion intensities and a range of relative densities to define the median response and the sensitivity of the response to relative density and shaking intensity. The nine centrifuge facilities involved in this test program included Cambridge University (UK), Ehime University (Japan), IFSTTAR (France), NCU (Taiwan), KAIST (Korea), Kyoto University (Japan), RPI (USA), UC Davis (USA), and Zhejiang University (China).
description: Lateral spreading of a submerged slope for LEAP-UCD-2017
DOI: 10.17603/ds2-jgf8-ak64
title: A Curated Database of Physical and Virtual Calibration Chamber Experiments of Cone Penetration Tests in Layered Soil Specimens

description: This project provides a curated dataset of 259 cone penetration test (CPT) profiles, including both measured and “true” CPT data in layered and homogeneous soils. The data is compiled from 179 virtual calibration chamber (VCC) simulations by Rateria and Maurer (2025) and 80 experiments from prior literature (41 physical and 39 virtual). These profiles support a deeper understanding of layered soil-system characterization and enable the development and enhancement of CPT inversion methods.

The VCC experiments were conducted using Discrete Element Method (DEM) simulations in a 1-meter cylindrical chamber with ~1.5 million particles. Each dataset includes cone-tip resistance and, when available, sleeve friction profiles. 

Reusability:
This dataset can be reused to train CPT inversion models, conduct parametric studies, and support geotechnical education. 

Uniqueness:
It is the largest known open-access collection of paired measured and true CPT profiles, combining physical and virtual experiments, providing a valuable resource for CPT inversion research.

Audience:
Geotechnical engineers, researchers, educators, and data scientists working on soil characterization, modeling, or CPT interpretation.
DOI: 10.17603/ds2-htk5-9w67
title: 2021 Social Science Extreme Events Research (SSEER) Network
title: in Social Science Extreme Events Research (SSEER) Network Data, Survey Instrument, and Annual Census

description: This dataset includes information regarding 1,396 unique social science researchers who signed up for the Social Science Extreme Events Research (SSEER) network between July 8, 2018 and December 31, 2021. Researchers’ information is collected via an online survey that consists of 19 questions and takes approximately 7 minutes to complete. The envisioned audience for this data and other information includes those who are interested in learning more about the composition of the social science hazards and disaster research workforce, the events that they study, and their skills and expertise.
description: This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit:  https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
DOI: 10.17603/ds2-qbsx-ma75
title: May 28, 2019 EF4 Linwood Tornado: Six-Month Post-Tornado Recovery Report
title: in StEER - 28 MAY 2019 LINWOOD, KS EF4 TORNADO: FIELD ASSESSMENT STRUCTURAL TEAM 1 (FAST-1)

description: On May 28, 2019, a destructive EF4 tornado struck north-eastern Kansas, resulting in severe damage in Leavenworth County and surrounding areas. The tornado travelled 31.8 miles in 55 minutes and had a maximum width of one mile. There were 18 injuries but no fatalities. The Structural Extreme Events Reconnaissance (StEER) funded a quick response field study, referred to here as Wave 1, to document post-tornado damage to building structures along the tornado path. The Wave 1 survey documented initial building damage, aerial imagery of the tornado path and provides an essential baseline for subsequent impact and recovery studies. A second and third wave of data collection were funded by PI Sutley’s fellowship funding from the National Academies of Science, Engineering, and Medicine Gulf Research Program, and were executed six months and twelve months after the tornado, respectively. The Wave 2 and 3 teams consisted of structural engineering professors and students, behavioral economics professor and students, and public administration and urban planning students from the University of Kansas. Goals for Wave 2 and Wave 3 were to: (1) document risk perception, sheltering behavior, impact, and recovery experience of households during and since the May 2019 tornado, and (2) document the repair progress for homes along the tornado path six and twelve months after a major tornado in rural Kansas. This project achieves collected data from Waves 1, 2, and 3. This collection also archives survey instruments and Institutional Review Board protocol approved by the University of Kansas IRB office for Waves 2 and 3.
description: An EF4 tornado occurred in northeastern Kansas on May 28, 2019 causing considerable damage in Leavenworth County. Damage mostly consisted of single-family residential structures, and was assessed by a team of researchers led by the University of Kansas (KU) three days after the tornado. This report presents a follow-up study undertaken six months after the tornado to document building-level data on repair progress and household-level data on building code perceptions, risk perceptions, recovery progress, and socio-demographics.
DOI: 10.17603/ds2-fv2y-5z03
title: Data Report
title: in GEER Reconnaissance of 2018 Palu-Donggala Earthquake and Flowslides

description: This collection includes a preprint of the paper "Field Reconnaissance Data from GEER Investigation of the 2018 MW 7.5 Palu-Donggala Earthquake" submitted for publication in Data in Brief. This article describes details of the data collection and processing used for this dataset.
description: The Mw7.5 Palu-Donggala earthquake occurred on 28 September 2018 and caused significant damage in Palu City and the surrounding Central Sulawesi region of Indonesia. The earthquake initiated a series of catastrophic landslides (classified as flowslides), collapsed buildings, and generated tsunami waves that impacted the coast of Palu Bay. The earthquake claimed over 4,000 lives, making it the deadliest natural disaster of 2018. We performed a post-earthquake field reconnaissance and collected perishable data at the sites of five significant flowslides (named for the communities where they occurred: Balaroa, Petobo, Lolu Village, Jono Oge, and Sibalaya), as well as at other damage locations in the mesoseismal region. Our field team consisted of five U.S.-based members, who were sponsored by the U.S. National Science Foundation-supported Geotechnical Extreme Events Reconnaissance (GEER) organization, in collaboration with geologists, geotechnical engineers, and other researchers from Indonesia's Center for Earthquake Studies (PusGen) and the Indonesian Society of Geotechnical Engineers (HATTI) [collectively referred to as the Palu Earthquake "GEER" team]. The GEER team arrived at Palu City on 13 November 2018 and conducted five days of extensive fieldwork using instrumentation from the RAPID Facility, including mobile data collection software, digital imaging systems, high-resolution global position system (GPS) antennas, and unmanned aerial vehicles (UAVs, or "drones"). The resulting dataset includes over 2,000 geotagged photographs, UAV images, GPS coordinates, and other field measurements and observations, as well as associated post-processed geospatial data products (point clouds, digital surface models, orthomosaic images). Additionally, we used remote sensing data (i.e., pre- and post-event satellite imagery) to generate displacement vectors for over 1,200 structures affected by the flowslides.
DOI: 10.15468/dl.7xgm3g
title: Occurrence Download

description: A dataset containing 57020401 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Observation.org, Nature data from around the World",
 "License is CC-BY-NC 4.0",
 "TaxonKey is Aves",
 "Year 2005-2025"
 ]
}

 The dataset includes 57020401 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015621-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17603/ds2-sqf4-9k45
title: Green social work educational resources in Canada

description: Green social work (GSW) is a relatively new framework within social work. The primary objective of this approach is to integrate an environmental focus. GSW aims to address economic oppression, engage in disaster resilience, and sustainable practices. The project GSW Education in Canada aims to comprehensively examine the Canadian schools of social work programs (Bachelor, Master, and Ph.D.), related courses, areas of faculty specialization, and placement opportunities. This project examines the level of GSW teaching and knowledge mobilization in the Canadian social work educational system. Consequently, through website keywords (e.g., climate change, disaster, environment, green social work, and sustainability) searching, data from the academic institutions’ official websites for 45 universities and colleges were collected. These data include (1) course descriptions, (2) faculty members areas of research and/or practice, (3) when possible, social work field placement opportunities. The first iteration of this data included information about faculty members, including name and research or practice specialization. However, faculty members’ data is not able to be published due to privacy and ethical concerns. This data set emphasizes the Canadian post-secondary institutions’ emphasis or lack of focus on GSW. This information might encourage schools of social work and faculty members to promote GSW research, teaching, and practice through integrating disaster response, climate change, and sustainability practices. International and Canadian social work researchers could use this data to identify future research collaborations across Canadian geographical areas where GSW curricula can be further developed. Prospective social work students can use this data to find GSW-related programs and courses and network with faculty members with related research interests. For the public, this data can provide information about social work courses and curricula across Canada and highlight the scholars with relevant expertise amongst the institutions.
DOI: 10.17603/ds2-d25m-gg48
title: SKS02: Centrifuge Test of Liquefaction-Induced Downdrag in Uniform Liquefiable Deposit
title: in Centrifuge Testing of Liquefaction-Induced Downdrag on Axially Loaded Piles

description: The SKS02 centrifuge model test examined liquefaction-induced downdrag in a predominantly uniform liquefiable soil deposit. The soil profile consisted of a 1 m of coarse sand, underlain by 4 m of clay, 9 m of liquefiable loose soil, and a deeper dense soil (prototype scale). The test included two 635 mm diameter (D) piles, with their tip embedded to the depth of 0D and 5D in the dense sand layer. The model was shaken with a suite of scaled Santa Cruz earthquake motions with peak horizontal accelerations ranging from 0.025 g to 0.4 g. The model was heavily instrumented to track the development of pore-pressures, axial loads, and soil and pile settlements during and post shaking. With multiple shakings, the drag load on the piles increased and saturated at the load curve estimated from the mobilization of full negative skin friction (assuming it equal to the interface shear strength). A higher drag load was observed along the deep-embedded 5D pile as compared to the shallow-embedded 0D pile. While soil settlements were large, the piles underwent considerably smaller settlements. Most of the pile settlement (>90%) occurred during shaking and very minimal settlement (<5mm) occurred during reconsolidation.
description: Downdrag loads on pile foundations can be an important design consideration when earthquake-induced liquefaction is expected to cause ground settlements. Despite significant research progress on the effects of liquefaction on structures, and the seismic response of piles, there is still a knowledge gap in the assessment of liquefaction-induced downdrag loads on piles. The interrelationships between mechanisms affecting negative skin friction are not accounted for in current practice. Hence, our inability to confidently account for liquefaction-induced downdrag may lead to over-conservative or unsafely designed piles. This project aims to develop centrifuge-based design guidelines for the assessment of liquefaction-induced downdrag loads on piles. Specifically, this dataset includes data from two large-scale centrifuge model tests (SKS02 and SKS03) designed to systematically illuminate the mechanisms affecting negative skin friction for a variety of situations wherein liquefaction takes place around piles. Results from these tests can be used to validate numerical models in predicting the response of piles in liquefiable soils and further the development of the constitutive and interface models. Additionally, data from these tests can be used to study the lateral confinement condition at the interface for jacked piles during shaking, when soil is fully liquefied, as well as post shaking.