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

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Setipinna phasa)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 19 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020186-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7d7nj
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 (Philantomba maxwellii)",
 "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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020187-250802193616735/datasets/export for details.
DOI: 10.5281/zenodo.16615394
title: Text data (with sound file) of Irabu Ryukyuan (Japonic, Miyako)_5

description: Fully annotated narrative text with sound files: ヌーシ御嶽のタマミガ(Tamamiga the guardian of Nuushi Utaki)

Meta data:

data recorded 20250301

data recorded and annotated by Michinori Shimoji

data from ST (born in 1951, female, Nagahama, Irabu)

data status: open for academic uses only
DOI: 10.5281/zenodo.16753649
title: Text data (with sound file) of Irabu Ryukyuan (Japonic, Miyako)_5

description: Fully annotated narrative text with sound files: ヌーシ御嶽のタマミガ(Tamamiga the guardian of Nuushi Utaki)

Meta data:

data recorded 20250301

data recorded and annotated by Michinori Shimoji

data from ST (born in 1951, female, Nagahama, Irabu)

data status: open for academic uses only
DOI: 10.15468/dl.7kznt3
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 (Philantomba maxwellii)",
 "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/0020188-250802193616735/datasets/export for details.
DOI: 10.14466/cefasdatahub.151
title: Sea Angling Diary Catch, Participation and Economic Estimates 2016-2021

description: Modelled estimates of the participation, catch and economic impact of recreational sea angling taken from the Sea Angling Diary project in the UK from 2016 onwards which collects user responses via an app.

The Sea Angling Diary programme has been running since 2016 with the aim of estimating the number of sea anglers, how often they fish, what they catch, and the social and economic benefits that they generate. This is done through combining the outputs from two surveys: a survey of 12,000 individuals that generates estimates of the numbers of anglers and their characteristics; and sea anglers that volunteer as ‘citizen scientists’ to report their catches through the Sea Angling Diary with separate surveys for volunteers to report their spend on Sea Angling in 2016, 2017 and 2021. These estimates are combined accounting for differences in characteristics of sea anglers to generate the numbers and tonnages of fish kept and released by sea anglers in the UK as well as the economic impact of sea angling.

To estimate the participation and effort by UK sea anglers, questions were added to a survey of 12,000 residents (Watersports Participation Survey - WPS). Due to COVID restrictions, it was not possible to do face-to-face surveys as in 2016-19. Instead, data from the WPS from 2016-19 were modelled and used to derive estimates for 2016-2020 for the UK. This approach utilised all existing data to generate estimates for the total number of UK anglers and days fished with more consistent and robust results than previous annual estimates. Sea anglers signed up to the Sea Angling Diary provide data on their fishing sessions and report catches of fish. These data were used to model the number of fish kept and released by individual sea anglers each year and the weights of individual fish. Numbers of sea anglers were combined with diary panel estimates of catch per angler, to estimate total UK catches, after correcting for differences between the diary sample and the UK population. 

Economic estimates were generated from separate surveys of the diarist panel in 2016, 2017 and 2021 as part of the sea angling diary project. Expenditure on trips and major items (capital) was collected from the sample of sea anglers and raised to the total population of UK sea anglers using information generated from the estimates of the participation and effort by UK sea anglers. The total economic impact, Gross Value Added (GVA), and employment supported by sea angling in the UK in 2016, 2017 and 2021 were estimated using an Input-Output method. In this, taxes were removed, and expenditure partitioned between industrial sectors accounting for imports.
DOI: 10.15468/dl.jjrazb
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Paraguay",
 "TaxonKey is Psomophis obtusus"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020191-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16748753
title: LPDM footprint dataset - Brazil

description: Sample dataset of LPDM footprints for GOSAT measurements over and near Brazil, generated with the Met Office's NAME III v7.2. The footprints were generated for for GOSAT measurements for 2014, 2015, 2016 and 2018 in the [35.8∘ S -7.3∘ N, 76.0∘ W - 32.8∘ W] domain. Dispersion was modelled in a domain that covers the whole South American continent (domain [61.0∘ S -22.3∘ N, 91.3∘ W - 24.8∘ W]).

Created for Tunnicliffe et al. (2020) and published as part of preprint "Enabling Fast Greenhouse Gas Emissions Inference from Satellites with GATES: a Graph-Neural-Network Atmospheric Transport Emulation System" (Fillola et al, 2025, egusphere-2025-2392, the code is hosted in github at https://github.com/elenafillo/GATES_LPDM_emulator). See Ganesan et al. (2017) for details on how they were generated.

The datasets are provided as monthly netCDF arrays, which can be opened and explored in python using the xarray library. Each file contains backwards dispersion plumes (under variable "fp"), with the coordinates of the satellite measurement stored in the "release_lat" and "release_lon" variables.

 

Fillola et al. (2025). Enabling Fast Greenhouse Gas Emissions Inference from Satellites with GATES: a Graph-Neural-Network Atmospheric Transport Emulation System. Preprint egusphere-2025-2392. https://doi.org/10.5194/egusphere-2025-2392 

Tunnicliffe et al. (2020). Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from Satellite Data. Atmospheric Chemistry and Physics, 20(21), 13041–13067. https://doi.org/10.5194/acp-20-13041-2020

Ganesan et al. (2017): Atmospheric observations show accurate reporting and little growth in India's methane emissions, Nature Communications, 8, 836, https://doi.org/10.1038/s41467-017-00994-7
DOI: 10.5281/zenodo.16748754
title: LPDM footprint dataset - Brazil

description: Sample dataset of LPDM footprints for GOSAT measurements over and near Brazil, generated with the Met Office's NAME III v7.2. The footprints were generated for for GOSAT measurements for 2014, 2015, 2016 and 2018 in the [35.8∘ S -7.3∘ N, 76.0∘ W - 32.8∘ W] domain. Dispersion was modelled in a domain that covers the whole South American continent (domain [61.0∘ S -22.3∘ N, 91.3∘ W - 24.8∘ W]).

Created for Tunnicliffe et al. (2020) and published as part of preprint "Enabling Fast Greenhouse Gas Emissions Inference from Satellites with GATES: a Graph-Neural-Network Atmospheric Transport Emulation System" (Fillola et al, 2025, egusphere-2025-2392, the code is hosted in github at https://github.com/elenafillo/GATES_LPDM_emulator). See Ganesan et al. (2017) for details on how they were generated.

The datasets are provided as monthly netCDF arrays, which can be opened and explored in python using the xarray library. Each file contains backwards dispersion plumes (under variable "fp"), with the coordinates of the satellite measurement stored in the "release_lat" and "release_lon" variables.

 

Fillola et al. (2025). Enabling Fast Greenhouse Gas Emissions Inference from Satellites with GATES: a Graph-Neural-Network Atmospheric Transport Emulation System. Preprint egusphere-2025-2392. https://doi.org/10.5194/egusphere-2025-2392 

Tunnicliffe et al. (2020). Quantifying sources of Brazil's CH4 emissions between 2010 and 2018 from Satellite Data. Atmospheric Chemistry and Physics, 20(21), 13041–13067. https://doi.org/10.5194/acp-20-13041-2020

Ganesan et al. (2017): Atmospheric observations show accurate reporting and little growth in India's methane emissions, Nature Communications, 8, 836, https://doi.org/10.1038/s41467-017-00994-7
DOI: 10.15468/dl.zsfzd5
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 (Philantomba maxwellii)",
 "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/0020189-250802193616735/datasets/export for details.
DOI: 10.15468/dl.zd8gbm
title: Occurrence Download

description: A dataset containing 3696490 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2016",
 "Year is less than or equal to 2021",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Country is United Kingdom of Great Britain and Northern Ireland",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 3696490 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020154-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bqfwfu
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platysternon megacephalum",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 29 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020192-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.trykc2
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia candida",
 "Country is Malaysia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020195-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25625/wqoxtx
title: Data Management Plan

description: This is the Data Management Plan that will be followed by researchers working within UNPAG. Different versions of the DMP will be posted here.
DOI: 10.25625/wqoxtx/ecybxv
title: UNPAG_DMP_v1.pdf

description: This is the first version of the DMP for UNPAG. Future versions will be posted here.
DOI: 10.15468/dl.xt7pta
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia candida",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020193-250802193616735/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.29609312
title: Replication Data for: Mindfulness and creative self-efficacy in human–AI decision-making: Implications for adaptive AI design

description: This dataset supports the study "Mindfulness and creative self-efficacy shape human–AI decision-making: Implications for adaptive AI design." It includes participant responses across variables and time points in wide and long formats. (2025-07-21)
DOI: 10.6084/m9.figshare.29609312.v2
title: Replication Data for: Mindfulness and creative self-efficacy in human–AI decision-making: Implications for adaptive AI design

description: This dataset supports the study "Mindfulness and creative self-efficacy shape human–AI decision-making: Implications for adaptive AI design." It includes participant responses across variables and time points in wide and long formats. (2025-07-21)
DOI: 10.6084/m9.figshare.29609312.v1
title: Replication Data for: Mindfulness and creative self-efficacy shape human–AI decision-making: Implications for adaptive AI design

description: This dataset supports the study "Mindfulness and creative self-efficacy shape human–AI decision-making: Implications for adaptive AI design." It includes participant responses across variables and time points in wide and long formats. (2025-07-21)
DOI: 10.15468/dl.qma6jv
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Peersia frithii"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020197-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9evjg5
title: Occurrence Download

description: A dataset containing 431 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 (Philantomba maxwellii)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 431 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020198-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14466/cefasdatahub.152
title: 2015-2016 Acoustic Telemetry data for European eels (Anguilla anguilla) in Hanningfield reservoir, Essex, UK

description: Data from the tagging and tracking of European eels (Anguilla anguilla) in Hanningfield reservoir in 2015 and 2016. Acoustic tagging was undertaken on 36 eels between September and December 2015, then again on 68 eels between June and August 2016. In each year, the fine-scale movements of eels in the reservoir were tracked for a 6-month period. Various biometric recordings were taken whilst the eels were anaesthetised, such as total length and weight, pectoral fin size and length, vertical and horizonal eye measures, and lipid percentage.
The data were collected over the course of several tagging surveys between 2015 and 2016. Acoustic telemetry data on the eel positions was collected using an array of 31 receivers (Vemco VR2W V5–180 kHz), which were deployed in the reservoir between 29 July 2015 and 14 December 2016. Lipid level was measured with the calibrated Distell fatmeter (model-FM 692) and used as an indicator of eel fitness. 

Peer-reviewed papers published from this data:
Bašić, T., Aislabie, L., Ives, M., Fronkova, L., Piper, A. and Walker, A., 2019. Spatial and temporal behavioural patterns of the European eel Anguilla anguilla in a lacustrine environment. Aquatic Sciences, 81, pp.1-15. Available at: https://link.springer.com/article/10.1007/s00027-019-0671-y
Williamson, M.J., Jacoby, D.M., Bašić, T., Walker, A. and Piper, A.T., 2024. Social network analysis as a tool to inform anguillid eel conservation and management. ICES Journal of Marine Science, p.fsae001. Available at: https://academic.oup.com/icesjms/advance-article/doi/10.1093/icesjms/fsae001/7587675?
DOI: 10.15468/dl.r8uymz
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Centrolene geckoideum"
 ]
}

 The dataset includes 49 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020199-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3e42ky
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Moenkhausia eigenmanni)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 45 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020201-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q759jj
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tephrosia candida",
 "Country is Mozambique",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020203-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yb8xgx
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 (Philantomba maxwellii)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020202-250802193616735/datasets/export for details.
DOI: 10.15468/dl.kx486q
title: Occurrence Download

description: A dataset containing 5034 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Uracentron azureum, Uracentron flaviceps, Uranoscodon superciliosus, Diploglossus fasciatus, Diploglossus lessonae, Ophiodes fragilis, Ophiodes enso, Ophiodes striatus, Alopoglossus amazonius, Alopoglossus angulatus, Alopoglossus atriventris, Alopoglossus avilapiresae, Alopoglossus buckleyi, Alopoglossus brevifrontalis, Alopoglossus collii, Alopoglossus gansorum, Alopoglossus indigenorum, Alopoglossus meloi, Alopoglossus tapajosensis, Alopoglossus theodorusi, Calyptommatus confusionibus, Calyptommatus frontalis, Calyptommatus leiolepis, Calyptommatus nicterus, Calyptommatus sinebrachiatus, Gymnophthalmus leucomystax, Gymnophthalmus underwoodi, Gymnophthalmus vanzoi)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5034 records from 136 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020204-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.