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

description: A dataset containing 361 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Omphacomeria acerba",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 361 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013347-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14738209
title: 🇰🇷 🇰🇵 Reddit r/Korea Subreddit Dataset 2026
DOI: 10.15468/dl.bgwfq9
title: Occurrence Download

description: A dataset containing 4851 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((16.460093168521613 48.26426603171156, 16.58990127184201 48.25658201822604, 16.601343468055102 48.34389772964725, 16.471312973907686 48.351597089256984, 16.460093168521613 48.26426603171156))"
 ]
}

 The dataset includes 4851 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013349-260129131611470/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.31260521
title: Speculative survival through capital commodity in a rentier economy: representation of inflation on Iranian social media

description: This study explores the Iranian public’s perception of economic inflation, emphasizing the representation and subsequent attitudes across different commodity categories. Using data from X (formerly Twitter) and Instagram between October 2022 and November 2023, this study applies quantitative content and sentiment analyses on over 6.3 million posts, comparing social-media representation with official inflation data. Computational social science methods, such as data mining, facilitated the data collection. The results reveal a hierarchy of representation: capital commodities (housing, cars, and gold) receiving the most attention, followed by essential and lastly non-essential ones, with little to no consistent correlation between inflation rate and representation. A negative binomial regression confirms that inflation itself is not a significant predictor of public attention, while commodity type, particularly capital commodities, exerts a strong independent effect. Sentiment analysis shows that positive reactions to capital commodity inflation exceed those for essential by a factor of 5.1 and non-essential by 18. Therefore, the emphasis on capital commodities is not merely a response to living-cost crisis or perceptual bias, but reflects collective economic memory and experience under a rentier-crony capitalist system. In this Global South context, speculative behaviors towards capital commodities emerge as a socially-reinforced survival strategy to preserve wealth.
DOI: 10.6084/m9.figshare.31260521.v1
title: Speculative survival through capital commodity in a rentier economy: representation of inflation on Iranian social media

description: This study explores the Iranian public’s perception of economic inflation, emphasizing the representation and subsequent attitudes across different commodity categories. Using data from X (formerly Twitter) and Instagram between October 2022 and November 2023, this study applies quantitative content and sentiment analyses on over 6.3 million posts, comparing social-media representation with official inflation data. Computational social science methods, such as data mining, facilitated the data collection. The results reveal a hierarchy of representation: capital commodities (housing, cars, and gold) receiving the most attention, followed by essential and lastly non-essential ones, with little to no consistent correlation between inflation rate and representation. A negative binomial regression confirms that inflation itself is not a significant predictor of public attention, while commodity type, particularly capital commodities, exerts a strong independent effect. Sentiment analysis shows that positive reactions to capital commodity inflation exceed those for essential by a factor of 5.1 and non-essential by 18. Therefore, the emphasis on capital commodities is not merely a response to living-cost crisis or perceptual bias, but reflects collective economic memory and experience under a rentier-crony capitalist system. In this Global South context, speculative behaviors towards capital commodities emerge as a socially-reinforced survival strategy to preserve wealth.
DOI: 10.15468/dl.94qqhw
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anthonomus grandis",
 "BasisOfRecord is Human Observation",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 28 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013351-260129131611470/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.31260523
title: SensWorkflow: a high-performance framework for remote sensing big data processing on heterogeneous clusters

description: The increasing volume and complexity of remote sensing data have made high performance computing (HPC) essential, with workflows becoming key to enabling efficient and automated processing. However, challenges remain in heterogeneous distributed computing environments. To address these issues, we propose SensWorkflow, a dynamic and visual framework for high-performance remote sensing applications designed to simplify processing workflows and improve computational efficiency. SensWorkflow integrates efficient large-scale data storage and management, a novel blind dating optimization (BDO) task scheduling algorithm newly proposed in this study to improve load balancing and task assignment, model operator management, and visual workflow and task management. It is deployed on a heterogeneous distributed cluster and integrates the Bee grid file system (BeeGFS) for data storage, a not only structured query language (NoSQL) database for metadata management, and the high throughput Condor (HTCondor) framework for distributed task scheduling. To evaluate its performance, the synergetic retrieval of aerosol properties (SRAP) aerosol optical depth (AOD) retrieval algorithm was used as a case study to process 10-day moderate resolution imaging spectroradiometer (MODIS) data in 2022.
DOI: 10.6084/m9.figshare.31260523.v1
title: SensWorkflow: a high-performance framework for remote sensing big data processing on heterogeneous clusters

description: The increasing volume and complexity of remote sensing data have made high performance computing (HPC) essential, with workflows becoming key to enabling efficient and automated processing. However, challenges remain in heterogeneous distributed computing environments. To address these issues, we propose SensWorkflow, a dynamic and visual framework for high-performance remote sensing applications designed to simplify processing workflows and improve computational efficiency. SensWorkflow integrates efficient large-scale data storage and management, a novel blind dating optimization (BDO) task scheduling algorithm newly proposed in this study to improve load balancing and task assignment, model operator management, and visual workflow and task management. It is deployed on a heterogeneous distributed cluster and integrates the Bee grid file system (BeeGFS) for data storage, a not only structured query language (NoSQL) database for metadata management, and the high throughput Condor (HTCondor) framework for distributed task scheduling. To evaluate its performance, the synergetic retrieval of aerosol properties (SRAP) aerosol optical depth (AOD) retrieval algorithm was used as a case study to process 10-day moderate resolution imaging spectroradiometer (MODIS) data in 2022.
DOI: 10.15468/dl.ceagg2
title: Occurrence Download

description: A dataset containing 812 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Osyris lanceolata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 812 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013352-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ygma9
title: Occurrence Download

description: A dataset containing 340 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Chorthippus macrocerus"
 ]
}

 The dataset includes 340 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013354-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18490398
title: SuperDARN data in netCDF format (2013-Jul)

description: 2013-Jul SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6484799
title: SuperDARN data in netCDF format (2013-Jul)

description: 2013-Jul SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.15468/dl.76apu8
title: Occurrence Download

description: A dataset containing 1412 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is United States of America",
 "GadmGid is USA.5.19_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Amphibia",
 "Year 2024-2024"
 ]
}

 The dataset includes 1412 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013356-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brak8j
title: Occurrence Download

description: A dataset containing 863039 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pontederia crassipes, Alternanthera philoxeroides, Phytolacca americana, Pistia stratiotes, Chenopodiastrum hybridum, Sieruela rutidosperma, Cabomba caroliniana, Myriophyllum aquaticum, Parthenium hysterophorus, Matsucoccus matsumurae, Lissachatina fulica, Trachemys scripta, Procambarus clarkii, Lithobates catesbeianus, Phthorimaea absoluta)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 863039 records from 3658 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013305-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqrkae
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.80840000000001 24.483509, 88.73124300000001 24.477931, 88.65600499999999 24.461339, 88.584557 24.434144, 88.51867300000001 24.397023, 88.45998400000001 24.350897, 88.409937 24.296911, 88.36976199999999 24.236404, 88.34043800000001 24.170874, 88.32267400000001 24.101939, 88.31688800000001 24.031301, 88.323204 23.960702, 88.341447 23.891877, 88.371151 23.826518, 88.41157 23.766227, 88.46170100000001 23.712481, 88.52030600000001 23.666595, 88.58594600000001 23.62969, 88.657014 23.602666, 88.731773 23.586184, 88.80840000000001 23.580645, 88.88502699999999 23.586184, 88.95978599999999 23.602666, 89.03085400000001 23.62969, 89.09649400000001 23.666595, 89.15509900000001 23.712481, 89.20523 23.766227, 89.245649 23.826518, 89.275353 23.891877, 89.29359599999999 23.960702, 89.29991200000001 24.031301, 89.29412600000001 24.101939, 89.27636200000001 24.170874, 89.247038 24.236404, 89.206863 24.296911, 89.15681600000001 24.350897, 89.09812700000001 24.397023, 89.03224299999999 24.434144, 88.960795 24.461339, 88.88555700000001 24.477931, 88.80840000000001 24.483509))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080620-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dep5h2
title: Occurrence Download

description: A dataset containing 87 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cerrophidion tzotzilorum"
 ]
}

 The dataset includes 87 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080622-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.53vej3
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alburnus alburnus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1920",
 "Year is less than or equal to 1924"
 ]
}

 The dataset includes 44 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080623-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ud2r1l
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049953-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g5tsx8
title: Occurrence Download

description: A dataset listing the 53 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "StateProvince is BAHIA, BA",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 53 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071573-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zzdqoj
title: Occurrence Download

description: A dataset containing 9446 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Batsites inventory for England (1949-2011)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 9446 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044815-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ys3fgs
title: Occurrence Download

description: A dataset containing 1060970490 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 1060970490 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0172868-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vcglk7
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001840-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nth9oz
title: Occurrence Download

description: A dataset containing 1243456227 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1243456227 records from 20474 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007496-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wge9g8
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xanthodaphne pompholyx (Dall, 1889)"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0103690-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hmk3ur
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-90.1431470999999931 29.9806145999999991, -90.1431470999999931 29.9814695600000007, -90.1431470999999931 29.9824410999999991, -90.1431470999999931 29.9830240199999984, -90.1431470999999931 29.9838401200000000, -90.1431470999999931 29.9847727999999982, -90.1431470999999931 29.9853168600000011, -90.1431470999999931 29.9862883999999994, -90.1423331200000035 29.9862883999999994, -90.1412865700000054 29.9862883999999994, -90.1405501100000066 29.9862883999999994, -90.1400074600000067 29.9862883999999994, -90.1392709999999937 29.9862883999999994, -90.1392709999999937 29.9856277499999990, -90.1392709999999937 29.9848505199999984, -90.1392709999999937 29.9842675900000017, -90.1392709999999937 29.9837623899999990, -90.1392709999999937 29.9829462999999983, -90.1392709999999937 29.9824799599999992, -90.1392709999999937 29.9818193099999988, -90.1392709999999937 29.9813529699999997, -90.1392709999999937 29.9806145999999991, -90.1403563100000014 29.9806145999999991, -90.1410152400000015 29.9806145999999991, -90.1419455099999993 29.9806145999999991, -90.1431470999999931 29.9806145999999991))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091281-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.45z5nx
title: Occurrence Download

description: A dataset containing 2453 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Continent is Europe",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Pittosporum tobira (Murray) Aiton fil."
 ]
}

 The dataset includes 2453 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052694-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ytdtec
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xanthodaphne membranacea (R.B.Watson, 1886)"
 ]
}

 The dataset includes 9 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0103689-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.