cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31028245
title: <b>Draft genome sequence of </b><b><i>Priestia Megaterium</i></b><b> MHES4, a biofertilizer candidate isolated from tomato rhizosphere in Bangladesh</b>

description: This study presents the draft genome sequence of <i>Priestia megaterium</i> strain MHES4, a bacterium isolated from rhizosphere of tomato grown in drought-prone ecosystem of Rajshahi, Bangladesh. The strain was investigated for its potential application as a climate-smart biofertilizer. The final assembly comprises 60 contigs with a total length of 5,267,048 bp and 37.9% G+C content. Annotations revealed 5,445 coding sequences (CDS), 28 tRNAs, and 5 rRNAs.
DOI: 10.6084/m9.figshare.31028245.v1
title: <b>Draft genome sequence of </b><b><i>Priestia Megaterium</i></b><b> MHES4, a biofertilizer candidate isolated from tomato rhizosphere in Bangladesh</b>

description: This study presents the draft genome sequence of <i>Priestia megaterium</i> strain MHES4, a bacterium isolated from rhizosphere of tomato grown in drought-prone ecosystem of Rajshahi, Bangladesh. The strain was investigated for its potential application as a climate-smart biofertilizer. The final assembly comprises 60 contigs with a total length of 5,267,048 bp and 37.9% G+C content. Annotations revealed 5,445 coding sequences (CDS), 28 tRNAs, and 5 rRNAs.
DOI: 10.15468/dl.b9utx5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((90.02402499999999 25.418935, 89.946282 25.413358, 89.870475 25.396765, 89.79848800000001 25.36957, 89.73210899999999 25.332448, 89.672982 25.286323, 89.62256600000001 25.232339, 89.582098 25.171834, 89.552565 25.106308, 89.534679 25.037379, 89.528863 24.96675, 89.53523800000001 24.89616, 89.55362700000001 24.827346, 89.58355899999999 24.761999, 89.624284 24.70172, 89.674789 24.647986, 89.73382700000001 24.602111, 89.79995 24.565215, 89.871537 24.538199, 89.94684100000001 24.521721, 90.02402499999999 24.516183, 90.101209 24.521721, 90.176513 24.538199, 90.24809999999999 24.565215, 90.314222 24.602111, 90.373261 24.647986, 90.423766 24.70172, 90.46449 24.761999, 90.494423 24.827346, 90.512812 24.89616, 90.519187 24.96675, 90.51336999999999 25.037379, 90.495485 25.106308, 90.465952 25.171834, 90.425484 25.232339, 90.375067 25.286323, 90.31594 25.332448, 90.249561 25.36957, 90.177575 25.396765, 90.101767 25.413358, 90.02402499999999 25.418935))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081597-251120083545085/datasets/export for details.
DOI: 10.15468/dl.hpgjfk
title: Occurrence Download

description: A dataset containing 2039 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Iva xanthiifolia"
 ]
}

 The dataset includes 2039 records from 112 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081598-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.19407.14244
title: Kidney Damage- Master Summary.pdf
DOI: 10.15468/dl.jjkxbx
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "PublishingOrg is c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f",
 "StateProvince is Hessen",
 "TaxonKey is Martes martes",
 "Year 2010-2026"
 ]
}

 The dataset includes 14 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081599-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18133425
title: Animal Density Analysis in Brazil: Population-Livestock Relationships and Projections 2014-2034

description: Version 2.0This version includes methodological refinements, expanded statistical analyses, improved data organization, and editorial revisions. Minor corrections were applied to figures, tables, and metadata to enhance clarity, reproducibility, and alignment with the associated manuscript submitted to a peer-reviewed journal. No changes were made to the original data sources.
DOI: 10.5281/zenodo.18157977
title: Animal Density Analysis in Brazil: Population-Livestock Relationships and Projections 2014-2034

description: Version 2.0This version includes methodological refinements, expanded statistical analyses, improved data organization, and editorial revisions. Minor corrections were applied to figures, tables, and metadata to enhance clarity, reproducibility, and alignment with the associated manuscript submitted to a peer-reviewed journal. No changes were made to the original data sources.
DOI: 10.15468/dl.wtunu8
title: Occurrence Download

description: A dataset containing 17844 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((0.68025 46.34985,0.675 46.33703,0.67185 46.33145,0.67129 46.32207,0.67509 46.31211,0.68351 46.30709,0.7012 46.3113,0.70488 46.30987,0.70394 46.30332,0.71017 46.29877,0.73616 46.30062,0.73591 46.30664,0.74097 46.30674,0.74414 46.30011,0.74627 46.2953,0.75348 46.29612,0.76278 46.29295,0.77597 46.30676,0.78921 46.30167,0.79176 46.29837,0.79821 46.29381,0.80378 46.29342,0.80542 46.29462,0.8124 46.29509,0.81857 46.29153,0.82145 46.29208,0.82428 46.29364,0.83173 46.29445,0.83515 46.29335,0.83775 46.29474,0.8386 46.2976,0.84095 46.29931,0.82878 46.31397,0.82824 46.31546,0.83303 46.31656,0.84055 46.31553,0.84784 46.32035,0.85445 46.33051,0.85073 46.33914,0.83277 46.3475,0.82999 46.34443,0.80945 46.35073,0.80832 46.35473,0.80647 46.3587,0.7942 46.35746,0.7917 46.35959,0.78966 46.36223,0.78501 46.36364,0.78083 46.36557,0.7773 46.36901,0.77287 46.3711,0.76954 46.37572,0.76241 46.37876,0.75437 46.3801,0.75477 46.38229,0.75077 46.38539,0.74111 46.3852,0.73223 46.38368,0.72575 46.38272,0.71633 46.38253,0.70883 46.38254,0.70154 46.38357,0.6972 46.37746,0.69364 46.37019,0.69102 46.36362,0.68644 46.35767,0.68025 46.34985)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 17844 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081601-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rskgq7
title: Occurrence Download

description: A dataset containing 64874 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lama glama"
 ]
}

 The dataset includes 64874 records from 131 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081555-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djbzyj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.902565 25.430337, 89.824815 25.424759, 89.74900100000001 25.408167, 89.677007 25.380971, 89.61062200000001 25.34385, 89.55149 25.297724, 89.501069 25.24374, 89.46059700000001 25.183236, 89.431061 25.117709, 89.413174 25.048781, 89.407357 24.978151, 89.41373299999999 24.907562, 89.432124 24.838748, 89.462059 24.773401, 89.502788 24.713122, 89.553297 24.659388, 89.612341 24.613513, 89.67847 24.576617, 89.750063 24.549601, 89.825374 24.533124, 89.902565 24.527586, 89.97975599999999 24.533124, 90.05506699999999 24.549601, 90.12666 24.576617, 90.192789 24.613513, 90.251833 24.659388, 90.302342 24.713122, 90.34307099999999 24.773401, 90.373006 24.838748, 90.391397 24.907562, 90.397773 24.978151, 90.39195599999999 25.048781, 90.37406799999999 25.117709, 90.344533 25.183236, 90.304061 25.24374, 90.25364 25.297724, 90.194508 25.34385, 90.128123 25.380971, 90.056129 25.408167, 89.980315 25.424759, 89.902565 25.430337))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081602-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.16777726
title: Constructing a Spatiotemporal Knowledge Graph for Urban Traffic from Trajectory Big Data

description: Description

This dataset comprises data directly derived from, or further processed based on, the proposed urban traffic ST-KG in connection with the research presented in the paper. It is used to demonstrate the applicability of the proposed ST-KG across four key tasks: spatiotemporal analysis of congestion dynamics, traffic speed prediction, intelligent question answering on congestion, and tracing the causes of congestion. The data are organized according to these research tasks as follows:

1. Urban Traffic ST-KG Construction & Congestion Level Assessment.zip

Contains the urban traffic ST-KG entities and relations (converted to CSV format) used for producing Figures 1 and 2 in the paper. 

2. Spatiotemporal Analysis of Urban Traffic Congestion Dynamics.zip

Contains the processed results extracted from the urban traffic ST-KG and computed for exploring the spatiotemporal evolution of congestion. The dataset includes three folders—weekday, weekend, and holiday—each containing five subfolders (group 1–5) that store the average traffic speed of each grid cell within the corresponding group.

3. Traffic Speed Prediction at the Regional Scale.zip

Contains the data used for traffic speed prediction, including the counts of seven types of Points of Interest (POIs) within each predicted grid cell, data from two precipitation stations, and the adjacency matrix of the predicted grid cells. The prediction target is the average traffic speed of the predicted grid cells, calculated at five-minute intervals. The file feature_matrix_X.csv stores the interpolated average traffic speed matrix.

4. Intelligent Question Answering on Traffic Congestion.zip

Records the specific entities and relations extracted by the LLM-Agent from the urban traffic ST-KG in response to user queries.

5. Tracing the Causes of Non-Recurrent Traffic Congestion.zip

Contains statistical analyses based on the results from Intelligent Question Answering on Traffic Congestion, further deriving traffic flow data. The files include:



date_group_counts.xlsx – daily traffic flow

date_time_range_count.xlsx – traffic flow at five-minute intervals

honeycomb_time_date_count.xlsx – traffic flow of each grid cell at five-minute intervals

honeycomb_time_date_congestion_count.xlsx – traffic flow of each grid cell at five-minute intervals, categorized by congestion level


Naming Notes



In the paper, the "grid" is hexagonal in shape; therefore, it is referred to as "honeycomb" in the dataset.

The "state" in the paper is derived from mapped trajectory points and is directly referred to as "trajectory_point" in the dataset.
DOI: 10.15468/dl.g7a7qj
title: Occurrence Download

description: A dataset listing the 0 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Bird pollinator populations in Agroecosystems of Rwanda: a baseline perspective for pollinator conservation"
 ]
}

 The dataset's 0 records were derived from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081578-251120083545085/datasets/export for details.
DOI: 10.15468/dl.8d9fsw
title: Occurrence Download

description: A dataset listing the 32662 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is The fossil collection (F) of the Muséum national d'Histoire naturelle (MNHN - Paris)"
 ]
}

 The dataset's 32662 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081580-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.58063/yj07-nz09
title: Database of Hus’s works
DOI: 10.15468/dl.h4tcw8
title: Occurrence Download

description: A dataset containing 39777602 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Marmaronetta angustirostris, Melanitta perspicillata, Mergus merganser, Neochen jubata, Netta erythrophthalma, Netta peposaca, Netta rufina, Nettapus auritus, Nettapus coromandelianus, Oxyura australis, Oxyura ferruginea, Oxyura jamaicensis, Oxyura leucocephala, Oxyura maccoa, Oxyura vittata, Plectropterus gambensis, Polysticta stelleri, Pteronetta hartlaubii, Radjah radjah, Sarkidiornis melanotos, Sibirionetta formosa, Spatula clypeata, Spatula cyanoptera, Spatula discors, Spatula hottentota, Spatula platalea, Spatula puna, Spatula rhynchotis, Spatula versicolor, Tadorna cana, Tadorna ferruginea, Tadorna tadorna, Tadorna tadornoides, Tadorna variegata, Thalassornis leuconotus, Aerodramus bartschi, Aerodramus vanikorensis, Chaetocercus jourdanii, Florisuga mellivora, Apteryx australis, Apteryx haastii, Apteryx owenii, Anthracoceros malayanus, Buceros bicornis, Bucorvus abyssinicus, Bucorvus leadbeateri, Bycanistes brevis, Lophoceros nasutus, Phoeniculus purpureus, Rhyticeros undulatus, Tockus deckeni, Podargus strigoides, Casuarius bennetti, Casuarius casuarius, Dromaius novaehollandiae, Actophilornis africanus, Aethia cristatella, Burhinus superciliaris, Charadrius dubius, Chionis albus, Chroicocephalus cirrocephalus, Chroicocephalus hartlaubii, Chroicocephalus novaehollandiae, Cursorius cursor, Glareola ocularis, Himantopus himantopus, Himantopus mexicanus, Jacana jacana, Larus dominicanus, Larus occidentalis, Limosa limosa, Pluvialis apricaria, Pluvialis squatarola)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 39777602 records from 4312 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081556-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1198620.10fu
title: SH1198620.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198621.10fu
title: SH1198621.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198623.10fu
title: SH1198623.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198624.10fu
title: SH1198624.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198626.10fu
title: SH1198626.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198627.10fu
title: SH1198627.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198631.10fu
title: SH1198631.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1198632.10fu
title: SH1198632.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.