cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5ew693
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Alonella, Anisocentropus, Anopheles, Aphelocheirus schoutedeni, Aphelocheirus, Atherix, Athripsodes prionii, Atrichopogon, , Aulophorus, Bezzia, Biomphalaria pfeifferi, Biomphalaria, Branchiura sowerbyi, Branchiura, Canthydrus notula, Canthydrus, Caridina nilotica, Caridina typus, Catoxyethira, Ceratogomphus, Ceriodaphnia, Chaetogaster, Chaoborus, Chlorocypha, Chrysops, Chydorus, Clinotanypus, Corynoneura, Culicoides, Cyclops, Cypridopsis, Cyprilla, , Dineutus, Dryops, Ecnomus thomasseti, Elattoneura, Enallagma, Ephoron, Eubrianax, Forcipomyia, Goerodes, Gomphocythere, Helminthopsis, Hemerodromia, Hydaticus dorsiger, Hydaticus, Hydra, Hydrellia, Hydropsyche, Hyphydrus, Ilyocryptus, Isocypris, Laccophilus flaveolus, Laccophilus lineatus, Laccophilus modestus, Laccophilus pellucidus, Leptelmis, Leptocerus, Lestes, Limnodrilus, Limnophora, Lobelmis, Machadorythus, Macrobrachium equidens, Macrobrachium, Macromia, Micronecta dimidiata, Naucoris obscuratus, Naucoris, Notonurus, Nychia, Oecetis, Orthotrichia, Pachyelmis, Palpomyia, Paracyclops, Paragomphus, Parasetodes, Phaon, Pionocypris, Pleuroxus, Polyplectropus, Potamodytes, Potamogethes, Pristina, Procladius, Prosopistoma, Pseudagrion gigas, Pseudagrion hageni, Pseudagrion kersteni, Pseudagrion salisburyense, Pseudancyronyx, Maruina, Pericoma, Ranatra, Rhantaticus congestus, Rhantaticus, Rheotanytarsus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((15.6372 -28.0032,16.2782 -28.5786,20.509 -28.5786,20.509 -24.0715,15.4933 -24.0715,15.4945 -24.1257,16.0509 -25.6631,15.6372 -28.0032))"
 ]
}

 The dataset includes 30 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020148-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17603/ds2-spft-xp02
title: Mitigating the Effects of Excessive Heat in Hillsborough County's Vulnerable Neighborhoods

description: Hillsborough County, Florida faces the climate stressor of excessive heat each year. Exposure to excessive heat can lead to heat-related illness or death, especially in vulnerable populations. This study uses a mixed methods approach to understand the factors that contribute to social vulnerability levels of different census tracts in Hillsborough County and to identify strategies to mitigate the harmful effects of excessive heat in vulnerable communities. An analysis of different vulnerability and resilience indices was conducted to determine the locations in Hillsborough County with high concentrations of socially vulnerable populations. Additionally, several interviews with stakeholders in emergency management, nonprofits, and religious organizations were completed to understand the status of Hillsborough County’s resilience-building strategies and projects. Furthermore, reports from the City of Tampa—Resilient Tampa (May 2021) and Tampa's Heat Resilience Playbook (July 2024)—were reviewed, and recommendations from these reports were compared with stakeholder interview responses. The geographic distribution of several socially vulnerable populations was mapped, and areas of need were identified. Some of these areas lie outside of Tampa’s municipal boundary, and recommendations were made for strategies that can be implemented in these vulnerable communities by the county-level government to build resilience to excessive heat.

The Weather Climate and Society REU program invited 10 students from across the US to conduct research projects related to disaster-vulnerable communities in Florida and other extreme weather-affected areas. These projects were interdisciplinary, integrating social science and physical science aspects of severe weather, climate, and related disasters through field work, interviews, and/or spatial analysis of secondary data in GIS. The PI of this REU is Dr. Jennifer Collins.
DOI: 10.15468/dl.gqujy3
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hantzschia amphioxyss, Hapalosiphon, Heteroleibleinia, , Hippodonta, Homoeothrix, Kirchneriella, Klebsormidium, Kobayasiella, Kobayasiella subtilissima, Lagerheimia, Lemnicola, , Luticola goeppertiana, Dorofeyukea, Lyngbya, Melosira, Melosira varians, Merismopedia, Micractinium, Micrasterias, Microcystis, Monoraphidium, Mougeotia, Navicula angusta, Navicula antonii, Navicula capitatoradiata, Navicula cincta, Navicula cryptocephala, Navicula cryptotenelloides, Navicula erifuga, Navicula germainii, Navicula gregaria, Navicula heimansioides, Navicula libonensis, Navicula longicephala, Navicula minima, Navicula, Navicula notha, Navicula radiosa, Navicula ranomafanensis, Navicula recens, Navicula reichardtiana, Navicula rhynchocephala, Navicula riediana, Navicula rostellata, Navicula schroeteri, Navicula symmetrica, Navicula tripunctata, Navicula trivialis, Navicula veneta, Navicula zanoni, Navicymbula, Nitzschia, , Nitzschia agnewii, , Nitzschia archibaldii, Nitzschia aurariae, Nitzschia capitellata, , Nitzschia closterium, Nitzschia desertorum, Nitzschia dissipata, Nitzschia etoshensis, Nitzschia filiformis, , , Nitzschia intermedia, Nitzschia irremissa, Nitzschia liebetruthii, , Nitzschia littorea, , , Nitzschia nana, Nitzschia pura, , Nitzschia recta, Nitzschia sublinearis, Nitzschia communis, Nostoc, Nostoc commune, Oedogonium, Oedogonium minus, Oocystis, Orthoseira, Oscillatoria, Oscillatoria princeps, Oscillatoria sancta, Oscillatoria tenuis, Oxyneis, Palmella, Pediastrum, Pediastrum duplex, Phacus, Phormidium, Pinnularia acrosphaeria, Pinnularia, )",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((27.1332 -20.158,25.5395 -23.2724,25.5395 -24.0715,30.5701 -24.0715,30.5701 -20.3186,29.6496 -19.6123,28.947 -19.4003,28.1821 -19.4609,27.6072 -19.7214,27.1332 -20.158))"
 ]
}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020149-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2k44zu
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lachesis acrochorda"
 ]
}

 The dataset includes 120 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020150-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17603/ds2-zs73-tg92
title: Information Sources and Government Trust Regarding Evacuation Decisions for Hurricanes Helene and Milton

description: Effective communication is critical to successfully protect the public and maintain trust in local institutions. Official sources have commonly failed to capitalize on the rise of social media, leading to unofficial sources filling in the gaps on sites such as X to provide weather-related information to the public. It is important to explore where people get their information and how it shapes their sentiments because of its revealing nature for implications on public trust and safety. This study explores the relationship between information sources and trust in government evacuation decisions during Hurricanes Helene and Milton. To do this, a statewide survey (n=2185) was conducted to understand populaces’ responses to weather risk and information. Quantitative data was then analyzed in SPSS, while open-ended responses were coded using NVivo to identify themes and sentiments. Findings from a chi-square test indicate an association between official sources and trust in government. In addition, general negative themes around evacuation orders and dissent surrounding local officials were discovered in the open-ended responses. The findings indicate that there need to be improvements in official messaging transparency and real-time messaging so that the public will continue to rely on official sources, especially on newer social media platforms.

The Weather Climate and Society REU program invited 10 students from across the US to conduct research projects related to disaster-vulnerable communities in Florida and other extreme weather-affected areas. These projects were interdisciplinary, integrating social science and physical science aspects of severe weather, climate, and related disasters through field work, interviews, and/or spatial analysis of secondary data in GIS. The PI of this REU is Dr. Jennifer Collins.
DOI: 10.15468/dl.bjavjh
title: Occurrence Download

description: A dataset containing 1035 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dendroctonus frontalis"
 ]
}

 The dataset includes 1035 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020151-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mb22xw
title: Occurrence Download

description: A dataset containing 18850 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-74.33907 1.59257,-72.83526 1.59257,-72.83526 3.02202,-74.33907 3.02202,-74.33907 1.59257))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 18850 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020152-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qabe9s
title: Occurrence Download

description: A dataset containing 43012 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-96.79577904820381 28.333514797230354, -96.79856627835869 28.33378758040244, -96.8013600914187 28.333573911861272, -96.80405306242598 28.332882009159434, -96.80654165033873 28.3317384816741, -96.80873018492612 28.33018730498572, -96.81053454868041 28.32828812628192, -96.81188541143551 28.32611396661529, -96.81273089307983 28.3237484091603, -96.81303855228268 28.321282382372672, -96.8127966255716 28.31881066240172, -96.81201447030563 28.316428229661454, -96.810722195906 28.3142266197626, -96.8089694989116 28.312290408888042, -96.80682374782184 28.310693968213638, -96.80436739213778 28.309498611394453, -96.80169479547685 28.308750243895556, -96.79890861421812 28.308477603652992, -96.79611586008562 28.30869115994854, -96.79342379682505 28.309382712318026, -96.7909358272821 28.310525704719254, -96.78874752754628 28.31207624303336, -96.78694297937142 28.31397477725956, -96.78559154099993 28.316148384461012, -96.78474518017579 28.31851356557115, -96.78443647207686 28.32097944942928, -96.78467733986051 28.323451281645823, -96.78545858737978 28.325834064718403, -96.78675024340961 28.32803620970138, -96.78850270555238 28.32997305895017, -96.79064864106263 28.331570144102216, -96.79310557236305 28.332766053386546, -96.79577904820381 28.333514797230354))",
 "Year is one of (2019, 2020, 2021, 2022, 2023, 2024, 2025)",
 "KingdomKey is one of (Animalia, Fungi, Plantae)"
 ]
}

 The dataset includes 43012 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020153-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27186087
title: IPD-Brain: An Indian histopathology dataset for glioma subtype classification

description: <pre>The IPD-Brain Dataset is a comprehensive collection comprising 547 high-resolution H&E stained slides from 367 patients, aimed at advancing the study of glioma subtypes and immunohistochemical (IHC) biomarkers. This dataset, one of the largest of its kind in Asia, is especially notable for its focus on the diverse demographics of the Indian population. Each slide is scanned at a magnification of 40x and includes detailed clinical annotations in a xlsx file such as patient age, sex, radiological findings, diagnosis, CNS WHO grade, and IHC biomarker status, which covers IDH1 R132H, ATRX, p53, and the proliferation index Ki67. Open for use and governed by ethical guidelines, the IPD-Brain Dataset is designed to facilitate a wide range of applications, from training machine learning models to exploring regional and ethnic variations in disease.A higher resolutions version of this dataset (upto 40x magnification) can be downloaded from data foundation, please follow the following link: https://india-data.org/dataset-details/170acc68-1288-499e-9a91-b951e569e70d</pre><br>
DOI: 10.6084/m9.figshare.27186087.v1
title: IPD Brain

description: <pre>The IPD-Brain Dataset is a comprehensive collection comprising 547 high-resolution H&E stained slides from 367 patients, aimed at advancing the study of glioma subtypes and immunohistochemical (IHC) biomarkers. This dataset, one of the largest of its kind in Asia, is especially notable for its focus on the diverse demographics of the Indian population. Each slide is scanned at a magnification of 40x and includes detailed clinical annotations in a xlsx file such as patient age, sex, radiological findings, diagnosis, CNS WHO grade, and IHC biomarker status, which covers IDH1 R132H, ATRX, p53, and the proliferation index Ki67. Open for use and governed by ethical guidelines, the IPD-Brain Dataset is designed to facilitate a wide range of applications, from training machine learning models to exploring regional and ethnic variations in disease.A higher resolutions version of this dataset (upto 40x magnification) can be downloaded from data foundation, please follow the following link: https://datafoundation.iiit.ac.in/dataset-versions/cb5917e1-6e56-4984-b6d1-f91d52ccd36c.</pre>
DOI: 10.6084/m9.figshare.27186087.v2
title: IPD-Brain: An Indian histopathology dataset for glioma subtype classification

description: <pre>The IPD-Brain Dataset is a comprehensive collection comprising 547 high-resolution H&E stained slides from 367 patients, aimed at advancing the study of glioma subtypes and immunohistochemical (IHC) biomarkers. This dataset, one of the largest of its kind in Asia, is especially notable for its focus on the diverse demographics of the Indian population. Each slide is scanned at a magnification of 40x and includes detailed clinical annotations in a xlsx file such as patient age, sex, radiological findings, diagnosis, CNS WHO grade, and IHC biomarker status, which covers IDH1 R132H, ATRX, p53, and the proliferation index Ki67. Open for use and governed by ethical guidelines, the IPD-Brain Dataset is designed to facilitate a wide range of applications, from training machine learning models to exploring regional and ethnic variations in disease.A higher resolutions version of this dataset (upto 40x magnification) can be downloaded from data foundation, please follow the following link: https://india-data.org/dataset-details/170acc68-1288-499e-9a91-b951e569e70d</pre><br>
DOI: 10.17603/ds2-fx61-nx53
title: Interpretation of the Hurricane Ian cone forecast impact on evacuation decision making of individuals aged 55 and older

description: Hurricane Ian (2022) affected Pinellas County Florida which had a population estimate of 409,230 (42.5%) older adults aged 55+ in 2022. Forecast cones released before landfall may be interpreted in different ways by various populations. Further investigation is needed to evaluate the relationship between cone interpretation and evacuation decisions in 55+ adults to improve risk communication. An anonymous survey was administered to populations impacted by Hurricane Ian to further examine forecast cone interpretation and evacuation behaviors. Researchers used R Studio for sub setting the 55+ population along with cleaning, categorization, and organization in preparation for statistical analyses using a logistic regression model in IBM SPSS Version 29. The data from questions The size of the cone represents the size of the storm (OR = 1.13, 95% CI [1.006 - 1.270]) and Areas outside the cone are not at risk to hurricane impacts (OR = 1.223, CI 95% [1.003-1.492]) proved to be statistically significant, meaning that individuals who evacuated are more likely to fully agree that the cone represents the size of the storm and hurricane impacts are not present outside the cone. As a result, older adults in Pinellas County who evacuated for Hurricane Ian had slightly higher odds of interpreting the forecast cone incorrectly.

The Weather Climate and Society REU program invited 10 students from across the US to conduct research projects related to disaster-vulnerable communities in Florida and other extreme weather-affected areas. These projects were interdisciplinary, integrating social science and physical science aspects of severe weather, climate, and related disasters through field work, interviews, and/or spatial analysis of secondary data in GIS. The PI of this REU is Dr. Jennifer Collins.
DOI: 10.5281/zenodo.17041470
title: SEAMM Package List

description: The package list for the SEAMM environment, also complete conda environment files with and without the version pinned.
DOI: 10.15468/dl.wpww68
title: Occurrence Download

description: A dataset containing 7235 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biodiversidad asociada a la mina de explotación y producción de Ferroníquel Cerro Matoso S.A."
 ]
}

 The dataset includes 7235 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020154-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rkz7p3
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Specimen, Material sample, Material citation, Living Specimen, Fossil, Occurrence evidence)",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pristimantis myops"
 ]
}

 The dataset includes 68 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020155-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48366/r1468542
title: A Comparative Study of Malware Detection with AI Investigations

description: This work is an outlook of existing works that surveyed and reviewed detection of malware using AI.
DOI: 10.25574/26454
title: Chandra X-ray Observatory ObsId 26454

description: Deep Chandra Observations of Spectacular NGC 3081
DOI: 10.15468/dl.9rm5ck
title: Occurrence Download

description: A dataset containing 162057 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cynodon dactylon"
 ]
}

 The dataset includes 162057 records from 1990 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020064-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wlgsey
title: Occurrence Download

description: A dataset containing 124 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Spinus yarrellii (Audubon, 1839)"
 ]
}

 The dataset includes 124 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002989-171113114016250/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kau2hp
title: Occurrence Download

description: A dataset containing 78645 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lethrinidae"
 ]
}

 The dataset includes 78645 records from 184 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055826-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3zjkkj
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lobelia pringlei S.Watson"
 ]
}

 The dataset includes 64 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056813-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jfuret
title: Occurrence Download

description: A dataset containing 3870 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendroica fusca (Statius Müller, 1776)",
 {
 "or" : [
 "Country is Venezuela (Bolivarian Republic of)",
 "Country is Bolivia (Plurinational State of)",
 "Country is Peru",
 "Country is Colombia",
 "Country is Ecuador"
 ]
 }
 ]
}

 The dataset includes 3870 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002990-150221044754056/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kycqfa
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "InstitutionCode is fb-umsnh",
 "TaxonKey is Herichthys tepehua De la Maza-Benignos, Ornelas-García, Lozano-Vilano, García-Ramírez & Doadrio, 2014"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062731-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bottbe
title: Occurrence Download

description: A dataset containing 246 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Algyroides marchi Valverde, 1958"
 ]
}

 The dataset includes 246 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002990-150316153013904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zptxpy
title: Occurrence Download

description: A dataset containing 240842 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is MEX.25.12_2",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 240842 records from 387 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056640-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.