cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/n54j8wbmvn
title: Image Dataset of Street Food Hygiene of Dhaka

description: The dataset comprises 1000 annotated images of street food vendors operating in various neighborhoods of Dhaka, Bangladesh. Images were captured using high-resolution smartphone cameras during daytime hours, ensuring optimal lighting conditions for accurate annotation. Each image is categorized based on five hygiene indicators: glove usage (yes/no), food covering (covered/uncovered), surface cleanliness (clean/dirty), waste presence (present/absent), and vendor appearance (clean/unclean). These labels are included in accompanying JSON and CSV annotation files, providing compatibility with popular machine learning frameworks such as TensorFlow and PyTorch. The dataset is structured into folders labeled by hygiene score and vendor ID to maintain clarity. Image resolution ranges between 1080x720 and 1920x1080 pixels. Most images were captured from a frontal or slightly elevated angle to provide a clear view of both the vendor and the food items. The annotation process involved three reviewers who independently labeled each image and resolved discrepancies through consensus. The dataset was preprocessed to exclude blurry or obstructed images, ensuring a high-quality resource for training and benchmarking. A distribution chart of hygiene indicators across different neighborhoods is included in the metadata, offering additional insights into geographic hygiene patterns within the city.
DOI: 10.17632/n54j8wbmvn.1
title: Image Dataset of Street Food Hygiene of Dhaka

description: The dataset comprises 1000 annotated images of street food vendors operating in various neighborhoods of Dhaka, Bangladesh. Images were captured using high-resolution smartphone cameras during daytime hours, ensuring optimal lighting conditions for accurate annotation. Each image is categorized based on five hygiene indicators: glove usage (yes/no), food covering (covered/uncovered), surface cleanliness (clean/dirty), waste presence (present/absent), and vendor appearance (clean/unclean). These labels are included in accompanying JSON and CSV annotation files, providing compatibility with popular machine learning frameworks such as TensorFlow and PyTorch. The dataset is structured into folders labeled by hygiene score and vendor ID to maintain clarity. Image resolution ranges between 1080x720 and 1920x1080 pixels. Most images were captured from a frontal or slightly elevated angle to provide a clear view of both the vendor and the food items. The annotation process involved three reviewers who independently labeled each image and resolved discrepancies through consensus. The dataset was preprocessed to exclude blurry or obstructed images, ensuring a high-quality resource for training and benchmarking. A distribution chart of hygiene indicators across different neighborhoods is included in the metadata, offering additional insights into geographic hygiene patterns within the city.
DOI: 10.15468/dl.4wfnzt
title: Occurrence Download

description: A dataset containing 2346 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepus saxatilis"
 ]
}

 The dataset includes 2346 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049656-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kc4e7q
title: Occurrence Download

description: A dataset containing 91287 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Potamogeton crispus L."
 ]
}

 The dataset includes 91287 records from 1215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012276-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8qaqen
title: Occurrence Download

description: A dataset containing 502 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Petunia altiplana T.Ando & Hashim."
 ]
}

 The dataset includes 502 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012306-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y8gsuy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platytroctes apus Günther, 1878",
 "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 ((26.9648 10.8496,17.9648 10.8496,17.9648 1.8496,26.9648 1.8496,26.9648 10.8496))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012308-250525065834625/datasets/export for details.
DOI: 10.15468/dl.eruy4d
title: Occurrence Download

description: A dataset containing 286 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 Glandularia bipinnatifida (Schauer) Nutt.",
 "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 286 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012307-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dv88pj
title: Occurrence Download

description: A dataset containing 39863 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Falcaria vulgaris Bernh.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 39863 records from 606 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012309-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r3xb7e
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Dendrocincla merula (Lichtenstein, 1820))",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016321-250525065834625/datasets/export for details.
DOI: 10.15468/dl.rxpwzh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Dendrocincla merula (Lichtenstein, 1820))",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016322-250525065834625/datasets/export for details.
DOI: 10.18739/a2z60c408
title: West Greenland Lakes: Abrupt Transformations Following Compound Extremes Associated With Atmospheric Rivers, 2013-2024

description: Arctic lake ecosystems are sites of high biodiversity that play an important role in carbon cycling, yet the impacts of emerging warmer and wetter conditions on the ecology of these lakes is poorly understood, partly owing to insufficient long-term data. Using a 10-year dataset, we report on an abrupt, coherent, climate-driven transformation of Arctic lakes in Greenland, demonstrating how a season of both record heat and rainfall drove a state change in these systems. This change from “blue” to “brown” lake states altered numerous physical, chemical, and biological lake features.
 This dataset has been analyzed in a manuscript submitted to the Proceedings of the National Academy of Sciences (PNAS) titled: Abrupt transformation of West Greenland lakes following compound climate extremes associated with atmospheric rivers.
DOI: 10.15468/dl.wjfbtu
title: Occurrence Download

description: A dataset containing 3450 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Dendrocincla merula (Lichtenstein, 1820))",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 3450 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016323-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.78edan
title: Occurrence Download

description: A dataset containing 25516 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Acer saccharum Marshall"
 ]
 },
 "HasCoordinate is TRUE",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2024",
 "DecimalLatitude is greater than or equal to 22.339412732727578",
 "DecimalLatitude is less than or equal to 56.478020942153016",
 "DecimalLongitude is greater than or equal to -89.38477198181909",
 "DecimalLongitude is less than or equal to -51.77540380141015",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 25516 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016320-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sur84s
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidostephium asteroides",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 30 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010007-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7tw332
title: Occurrence Download

description: A dataset containing 15545 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Helvella lacunosa"
 ]
}

 The dataset includes 15545 records from 377 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010008-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18363703
title: Physical Intelligence Risk & Emergence Framework (PIRE-F)

description: Artificial intelligence is increasingly embedded in physical systems—robotics, transport, critical infrastructure, and medical devices—where it acts upon matter and energy, producing risks characterized by irreversibility, cascading failure modes, and emergent autonomy. Existing governance approaches, including the NIST AI Risk Management Framework (AI RMF 1.0) and ISO/IEC AI risk guidance, provide organizational scaffolding but under-specify the behavioral enforcement layer required for embodied AI deployments. Meanwhile, the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) imposes binding obligations for high-risk AI systems, including technical documentation, logging, and post-market monitoring, without prescribing a concrete mechanism for demonstrating continuous compliance in real physical environments¹²³.

 

This paper proposes the Physical Intelligence Risk & Emergence Framework (PIRE-F), a novel, model-agnostic governance architecture for AI in physical systems that evaluates risk primarily through observable behavior. PIRE-F formalizes six behavioral-physical governance domains—Material Sovereignty, Behavioral Coherence, Physical Alignment, Boundary Integrity, Emergent Agency, and Consequence Probity—aligned with SCAB principles while articulated for safety engineering and regulatory assessment. The framework introduces quantitative metrics for constraint adherence, coherence divergence, reachability-based boundary risk, agency escalation, and probabilistic trace reconstructability, and defines threshold-driven intervention ladders enabling runtime constraint tightening, authority reassertion, and physical isolation. PIRE-F is shown to instantiate the NIST AI RMF’s Govern–Map–Measure–Manage functions for embodied systems, integrate with ISO/IEC AI risk management processes, and support EU AI Act technical documentation and post-market monitoring through structured behavioral evidence artifacts.
DOI: 10.5281/zenodo.18363704
title: Physical Intelligence Risk & Emergence Framework (PIRE-F)

description: Artificial intelligence is increasingly embedded in physical systems—robotics, transport, critical infrastructure, and medical devices—where it acts upon matter and energy, producing risks characterized by irreversibility, cascading failure modes, and emergent autonomy. Existing governance approaches, including the NIST AI Risk Management Framework (AI RMF 1.0) and ISO/IEC AI risk guidance, provide organizational scaffolding but under-specify the behavioral enforcement layer required for embodied AI deployments. Meanwhile, the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) imposes binding obligations for high-risk AI systems, including technical documentation, logging, and post-market monitoring, without prescribing a concrete mechanism for demonstrating continuous compliance in real physical environments¹²³.

 

This paper proposes the Physical Intelligence Risk & Emergence Framework (PIRE-F), a novel, model-agnostic governance architecture for AI in physical systems that evaluates risk primarily through observable behavior. PIRE-F formalizes six behavioral-physical governance domains—Material Sovereignty, Behavioral Coherence, Physical Alignment, Boundary Integrity, Emergent Agency, and Consequence Probity—aligned with SCAB principles while articulated for safety engineering and regulatory assessment. The framework introduces quantitative metrics for constraint adherence, coherence divergence, reachability-based boundary risk, agency escalation, and probabilistic trace reconstructability, and defines threshold-driven intervention ladders enabling runtime constraint tightening, authority reassertion, and physical isolation. PIRE-F is shown to instantiate the NIST AI RMF’s Govern–Map–Measure–Manage functions for embodied systems, integrate with ISO/IEC AI risk management processes, and support EU AI Act technical documentation and post-market monitoring through structured behavioral evidence artifacts.
DOI: 10.15468/dl.mpzuz7
title: Occurrence Download

description: A dataset containing 63 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptinella scariosa",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 63 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010010-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvmcng
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Craugastor epochthidius"
 ]
}

 The dataset includes 23 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010009-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5kd1r02c
title: MassIVE MSV000100580 - GNPS - INNOMISSION faba bean samples
title: Untargeted LC-MS/MS metabolomics study of faba bean (Vicia faba) seeds grown in three distinct locations across Denmark (with one site practicing organic farming) and represented with ten different cultivars.
DOI: 10.15468/dl.xeeb5k
title: Occurrence Download

description: A dataset containing 700 records in GBIF matching the query:
SELECT
 '356' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= 28.773895969281842
 AND decimalLatitude &lt;= 33.06103686093294
 AND decimalLongitude &gt;= 86.60801420953611
 AND decimalLongitude &lt;= 94.62398123724668
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 700 records were derived from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010002-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x3kfbn
title: Occurrence Download

description: A dataset containing 30713 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hydnum repandum"
 ]
}

 The dataset includes 30713 records from 420 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010011-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dg95j5
title: Occurrence Download

description: A dataset containing 1804 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptorhynchos squamatus",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1804 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010012-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18363726
title: Extreme events as an inadequately explored measure of solar geoengineering performance - Data and Systematic Review
DOI: 10.5281/zenodo.18363727
title: Extreme events as an inadequately explored measure of solar geoengineering performance - Data and Systematic Review
DOI: 10.15468/dl.fccbre
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is KUBI Mammalogy Collection",
 "TaxonKey is Reithrodontomys brevirostris"
 ]
}

 The dataset includes 34 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010013-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.