cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22008/fk2/89hwey/zanv8a
title: ib17_a.TIF
DOI: 10.5281/zenodo.18400260
title: Climatology of serial cyclone clusters and solitary cyclones in the Arctic for 1979 to 2024

description: This dataset provides a climatology of serial cyclone cluster and solitary cyclone events for the Arctic region including information on cyclone (cluster) occurrences and properties (event duration, cyclone intensity, cyclone cluster size). The dataset is derived from 6-hourly sea level pressure fields from the ERA5 reanalysis (Hersbach et al., 2020) by applying the Multi-Object Analysis of Atmospheric Phenomena (MOAAP) tracking tool (Prein et al., 2023) version V1.1.1 (https://github.com/AndreasPrein/MOAAP) and additional post-processing routines to separate the detected cyclone events into serial clusters and solitary cyclones. The separation is based on a maximum allowed time gap of 48 hours between consecutive cyclone passages. The dataset is available on the Equal-Area Scalable Earth (EASE) grid version 2.0 (Brodzik et al., 2012) with 25km² horizontal resolution and covers the years 1979 to 2024 with a daily temporal resolution. Hereby, days with a cyclone occurrence for at least one, 6-hourly timestep are considered as cyclone days. An example jupyter notebook showcasing the programmatic use of the data will be made avilable at https://ac3-tr.github.io/ac3-book/example-notebooks/ .
DOI: 10.5281/zenodo.18400261
title: Climatology of serial cyclone clusters and solitary cyclones in the Arctic for 1979 to 2024

description: This dataset provides a climatology of serial cyclone cluster and solitary cyclone events for the Arctic region including information on cyclone (cluster) occurrences and properties (event duration, cyclone intensity, cyclone cluster size). The dataset is derived from 6-hourly sea level pressure fields from the ERA5 reanalysis (Hersbach et al., 2020) by applying the Multi-Object Analysis of Atmospheric Phenomena (MOAAP) tracking tool (Prein et al., 2023) version V1.1.1 (https://github.com/AndreasPrein/MOAAP) and additional post-processing routines to separate the detected cyclone events into serial clusters and solitary cyclones. The separation is based on a maximum allowed time gap of 48 hours between consecutive cyclone passages. The dataset is available on the Equal-Area Scalable Earth (EASE) grid version 2.0 (Brodzik et al., 2012) with 25km² horizontal resolution and covers the years 1979 to 2024 with a daily temporal resolution. Hereby, days with a cyclone occurrence for at least one, 6-hourly timestep are considered as cyclone days. An example jupyter notebook showcasing the programmatic use of the data will be made avilable at https://ac3-tr.github.io/ac3-book/example-notebooks/ .
DOI: 10.22008/fk2/89hwey/4zhi4f
title: ib17_b.ARW
DOI: 10.22008/fk2/89hwey/5bhf7j
title: ib17_b.TIF
DOI: 10.22008/fk2/89hwey/ky2hbd
title: ib17_c.ARW
DOI: 10.22008/fk2/89hwey/sxofsr
title: ib17_c.TIF
DOI: 10.15468/dl.r5st6m
title: Occurrence Download

description: A dataset listing the 1758 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "Geometry POLYGON((-74.9891 1.17613,-74.10321 0.18199,-73.52962 0.63129,-74.41232 1.6062,-74.4888 1.54886,-74.9891 1.17613))"
 ]
}

 The dataset's 1758 records were derived from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003748-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/89hwey/e973ae
title: ib18_a.TIF
DOI: 10.22008/fk2/89hwey/tdxnid
title: ib18_a.ARW
DOI: 10.22008/fk2/89hwey/ahrddn
title: ib18_b.TIF
DOI: 10.22008/fk2/89hwey/wjprvg
title: ib18_b.ARW
DOI: 10.5061/dryad.dv41ns252
title: DNA sequence data generated using non-invasive feather and eggshell samples from the Grenada Dove for two gene regions: Cyt b and ND2

description: As an island endemic with a decreasing population, the Critically
 Endangered Grenada Dove Leptotila wellsi is threatened by accelerated loss
 of genetic diversity resulting from ongoing habitat fragmentation. Small,
 threatened populations are difficult to sample directly but advances in
 molecular methods mean that non-invasive samples can be used. We performed
 the first assessment of genetic diversity of populations of Grenada Dove
 by a) assessing mtDNA genetic diversity in the only two areas of occupancy
 on Grenada, b) defining the number of haplotypes present at each site and
 c) evaluating evidence of isolation between sites. We used non-invasively
 collected samples from two locations: Mt Hartman (n=18) and Perseverance
 (n=12). DNA extraction and PCR were used to amplify 1,751 bps of mtDNA
 from two mitochondrial markers: NADH dehydrogenase 2 (ND2) and Cytochrome
 b (Cyt b). Haplotype diversity (h) of 0.4, a nucleotide diversity (π) of
 0.00023 and two unique haplotypes were identified within the ND2
 sequences; a single haplotype was identified within the Cyt b
 sequences. Of the two haplotypes identified; the most common haplotype
 (haplotype A = 73.9%) was observed at both sites and the other (haplotype
 B = 26.1%) was unique to Perseverance. Our results show low mitochondrial
 genetic diversity and clear evidence for genetically isolated populations.
 The Grenada Dove needs urgent conservation action, including habitat
 protection and potential augmentation of gene flow by translocation in
 order to increase genetic resilience and diversity with the ultimate aim
 of securing the long-term survival of this Critically Endangered
 species. 
description: DNA extraction was carried out with the QIAGEN DNeasy® Blood and
 Tissue kit (QIAGEN Inc., Crawley) using the optimised protocol outlined in
 Peters et al. (2019). PCR was used to amplify mitochondrial markers:
 <em>ND2</em> and <em>Cyt b</em> using primers and
 cycling parameters outlined in Peters et al. (2022). Samples were prepared
 and submitted to Eurofins Genomics following the Mix2Seq kit (Eurofins
 Genomics, Luxembourg) instructions for sequencing using Sanger sequencing
 methods. Sequence assembly was performed using Sequencher 5.4.6 (Gene
 Codes Corporation 2017).
description: # DNA sequence data generated using non-invasive feather and eggshell
 samples from the Grenada Dove for two gene regions: Cyt b and ND2
 [https://doi.org/10.5061/dryad.dv41ns252](https://doi.org/10.5061/dryad.dv41ns252) This data set contains DNA sequence data generated for the Grenada Dove in FASTA file format. ## Description of the data and file structure Data are provided for each sample and each gene region in separate FASTA files and are named as follows: SAMPLE\_NAME\_ GENE\_REGION.FASTA <br> <br>
DOI: 10.22008/fk2/89hwey/1r2jqi
title: ib18_c.ARW
DOI: 10.22008/fk2/89hwey/kqbwdo
title: ib18_c.TIF
DOI: 10.22008/fk2/89hwey/ek8lfc
title: ib19_a.ARW
DOI: 10.22008/fk2/89hwey/qrwkhe
title: ib19_a.TIF
DOI: 10.22008/fk2/89hwey/upcmwe
title: ib19_b.ARW
DOI: 10.22008/fk2/89hwey/heughy
title: ib19_c.ARW
DOI: 10.22008/fk2/89hwey/kanskz
title: ib19_b.TIF
DOI: 10.22008/fk2/89hwey/eu4pjo
title: ib19_c.TIF
DOI: 10.22008/fk2/89hwey/fgjqeh
title: ib20_a.ARW
DOI: 10.22008/fk2/89hwey/biscig
title: ib20_b.ARW
DOI: 10.22008/fk2/89hwey/fzaavy
title: ib20_a.TIF
DOI: 10.22008/fk2/89hwey/lzp3mk
title: ib21_a.ARW
DOI: 10.22008/fk2/89hwey/x8pv9v
title: ib20_b.TIF
DOI: 10.22008/fk2/89hwey/f4yize
title: ib21_a.TIF
DOI: 10.22008/fk2/89hwey/ok5lof
title: ib21_b.ARW
DOI: 10.22008/fk2/89hwey/sepc0m
title: ib21_b.TIF
DOI: 10.22008/fk2/89hwey/vy6hxo
title: ib21_c.ARW
DOI: 10.22008/fk2/89hwey/wwky62
title: ib21_c.TIF
DOI: 10.22008/fk2/89hwey/97ca4m
title: ib22_a.ARW
DOI: 10.22008/fk2/89hwey/f9mqzr
title: ib22_a.TIF
DOI: 10.22008/fk2/89hwey/haisrt
title: ib22_b.ARW
DOI: 10.22008/fk2/89hwey/i1agos
title: ib22_b.TIF
DOI: 10.22008/fk2/89hwey/az6jby
title: ib22_c.TIF
DOI: 10.22008/fk2/89hwey/wu3wyh
title: ib22_c.ARW
DOI: 10.22008/fk2/89hwey/6uglem
title: ib6_a.ARW
DOI: 10.22008/fk2/89hwey/n7qrz1
title: ib6_a.TIF
DOI: 10.22008/fk2/89hwey/rhlajy
title: ib6_b.ARW
DOI: 10.22008/fk2/89hwey/17dfc8
title: ib6_c.ARW
DOI: 10.22008/fk2/89hwey/kexrgm
title: ib6_b.TIF
DOI: 10.22008/fk2/89hwey/6694nf
title: ib6_c.TIF
DOI: 10.22008/fk2/89hwey/qmkwkf
title: ib7_a.ARW
DOI: 10.22008/fk2/89hwey/izbbw8
title: ib7_b.ARW
DOI: 10.22008/fk2/89hwey/lpma7r
title: ib7_a.TIF
DOI: 10.22008/fk2/89hwey/efibpq
title: ib7_b.TIF
DOI: 10.22008/fk2/89hwey/s6k4mu
title: ib7_c.TIF
DOI: 10.22008/fk2/89hwey/zrombe
title: ib7_c.ARW
DOI: 10.22008/fk2/89hwey/ae3vdi
title: ib8_a.TIF
DOI: 10.22008/fk2/89hwey/rmmziv
title: ib8_a.ARW
DOI: 10.22008/fk2/89hwey/1kssuv
title: ib8_b.TIF
DOI: 10.22008/fk2/89hwey/qnfcqr
title: ib8_b.ARW
DOI: 10.22008/fk2/89hwey/qwgihv
title: ib8_c.ARW
DOI: 10.22008/fk2/89hwey/1n2q2k
title: ib9_a.ARW
DOI: 10.22008/fk2/89hwey/qycmdl
title: ib8_c.TIF
DOI: 10.22008/fk2/89hwey/qtazes
title: ib9_b.ARW
DOI: 10.22008/fk2/89hwey/xq4veg
title: ib9_a.TIF
DOI: 10.22008/fk2/89hwey/1ofc7a
title: ib9_b.TIF
DOI: 10.22008/fk2/89hwey/qoqubg
title: ib9_c.ARW
DOI: 10.22008/fk2/89hwey/xsnby0
title: ib9_c.TIF
DOI: 10.22008/fk2/89hwey/mtufqw
title: IndholdIsaaffik.docx
DOI: 10.22008/fk2/89hwey/wqsqvs
title: In progress_is_pos2019.docx
DOI: 10.22008/fk2/89hwey/ea3k92
title: Isaaffik.docx
DOI: 10.22008/fk2/89hwey/ktnn6m
title: ISPositioner2019.xlsx
DOI: 10.15468/dl.z5qgbr
title: Occurrence Download

description: A dataset containing 12749 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudophycis bachus",
 "HasCoordinate is true",
 "DecimalLatitude is greater than -90",
 "DecimalLatitude is less than 90",
 "DecimalLongitude is greater than -180",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950",
 "Year is less than or equal to 2014"
 ]
}

 The dataset includes 12749 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003779-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/89hwey/5wxue7
title: Readme photos.docx
DOI: 10.22008/fk2/89hwey/rrkyzq
title: ISSEDISAAFFIK.xlsx
DOI: 10.22008/fk2/89hwey/ho8nf2
title: Sampling Protocol for Sediment Concentration in Greenland Icebergs.docx
DOI: 10.22008/fk2/89hwey/prqorn
title: References.docx
DOI: 10.22008/fk2/89hwey/plamvu
title: Sedconc2019fin.xlsx
DOI: 10.22008/fk2/89hwey/7lu3bq
title: sejltur.jpg
DOI: 10.22008/fk2/89hwey/uxtp58
title: Sediment2018dk.xlsx
DOI: 10.22008/fk2/89hwey/k8xriz
title: spectralResponseILCE7M2.png
DOI: 10.22008/fk2/89hwey/wxojna
title: settings.xml
DOI: 10.5061/dryad.6m905qg69
title: Data from: field evaluation: the effect of two transgenic Bt maize events on predatory arthropods in the Huang-Huai-Hai summer maize-growing region of China

description: To illustrate the impact of genetically modified (GM) Bt maize on the
 natural enemy communities in the Huang-Huai-Hai summer maize-growing
 region in China, the abundance of seven common predator groups (Geocoris
 pallidipennis, Harmonia axyridis, lacewings, Orius sauteri, Propylea
 japonica, spiders, Staphylinidae) was quantitatively evaluated by planting
 Bt-Cry1Ab DBN9936 and Bt-Cry1Ab/Cry2Aj Ruifeng 125 events during the
 growing season from 2016 to 2019. A total of 11,172- 13,739 predators were
 observed in each varieties during four years, and the abundance of each
 groups on Bt maize varied between sample dates and among those enemy
 taxons. The shannon-Wiener diversity index from seven groups showed very
 similar temporal dynamics and there were not significant differences in Bt
 and non-Bt maize, showing that Bt maize did not disrupt the stability of
 predator enemy aggregation in the field. Spiders, H. axyridis, P.
 japonica, Lacewing, O. sauteri with positive taxon weights after using
 principal response curve (PRC) method, indicated that Bt maize had a
 positive effect on the abundances of individual taxa. All this indicating
 that the two Bt maize hybrids did not adversely affect predator community
 in the Huang-Huai-Hai summer maize-growing region of China.
description: Whole-plant visual inspections were carried out every 7 days from
 the 20th day after planting to harvest in each Bt and non-Bt maize plot
 during 2016-2019. We used a five-point sampling method along the two
 corner-to-corner diagonals in each plot, and twenty plants were selected
 from each point (totaling 100 plants sampled per plot, per time and each
 replication). The numbers of visible natural enemies on leaves, ears,
 husks, stalks, sheaths, and tassels were noted, and the total numbers per
 plot (100 plants) were counted.
description: There are seven columns. The first column was the sample date, and the
 second was maize variation, and third was noted as Bt or non-Bt, the four
 "repeat" means the replication ID, Species were the natural
 enemy taxa, Numbersper100 means the number of 100 plants by whole-plant
 visual inspection method, Year was the year conducted the trail. The code
 was the total detail code used in the article.
DOI: 10.22008/fk2/89hwey/5u9obh
title: spectralResponseILCE7M2.txt
DOI: 10.22008/fk2/89hwey/oenlga
title: Icesampling2022concentration.xlsx

description: Sediment concentrations 2022
DOI: 10.22008/fk2/89hwey/nhoh0y
title: Photos_of_samples_2022.pdf

description: Photos_of_samples_2022
DOI: 10.22008/fk2/89hwey/uqhb3e
title: Sketch_of_sampling.pdf

description: Sketch_of_sampling
DOI: 10.22008/fk2/89hwey/0te99w
title: Read_me_Sketch_of_sampling.docx

description: Read_me_Sketch_of_sampling
DOI: 10.22008/fk2/89hwey/9nte9w
title: DiskoPositions2022.xlsx

description: Sample Positions 2021
DOI: 10.22008/fk2/89hwey/4y3gr2
title: Icesampling2021concentration.xlsx

description: Sediment concentrations 2021
DOI: 10.22008/fk2/89hwey/ovikeb
title: Read_Me_2022_positions.docx

description: See "Sediment concentration 2022" for positions
DOI: 10.22008/fk2/89hwey/z7tvve
title: GreenlandIcesamplesBH_Year_of_sampling.pdf

description: :unav
DOI: 10.22008/fk2/89hwey/9iamuh
title: DiskoPositions2021.xlsx

description: :unav
DOI: 10.22008/fk2/89hwey/cjmj7t
title: ISPositioner2019_rev.xlsx

description: :unav
DOI: 10.5281/zenodo.14735130
title: Federated SVHN (i.i.d.) and CIFAR-10 (i.i.d. and non-i.i.d.)

description: Custom federated versions of SVHN and CIFAR-10 datasets used for the experiments in: Federated Learning With Individualized Privacy Through Client SamplingPlease cite this paper as reference.

Further descriptions found in the paper(s).
DOI: 10.5281/zenodo.14735129
title: Federated SVHN (i.i.d.) and CIFAR-10 (i.i.d. and non-i.i.d.)

description: Custom federated versions of SVHN and CIFAR-10 datasets used for the experiments in: Federated Learning With Individualized Privacy Through Client SamplingPlease cite this paper as reference.

Further descriptions found in the paper(s).
DOI: 10.5061/dryad.sqv9s4n9c
title: Equatorial waves for: A prediction attempt using equatorial waves for tropical sea surface temperature anomaly by Atlantic zonal mode

description: The dataset is the wave-induced geopotential output from linear ocean
 models and potential energy flux by a group-velocity-based wave energy
 flux scheme in the period (1992–2016), which is involved in building a
 lightweight model, as well as showing a simple instance of utilizing the
 wave energy transfer for the prediction of Atlantic Niño/Niñas.
description: Simulations by linear ocean models are performed independently
 for the first three baroclinic modes using corresponding gravity wave
 speed and projected wind forcing. The geopotential anomaly is then
 calculated through summing the geopotential anomaly in each mode with the
 correponding eigenvector at the sea surface as weights. The potential
 energy flux is also a combination of all the three baroclinic modes,
 whereas group velocity in each mode is obtained by dividing the
 corresponding wave energy from the wave energy flux which is calculated
 through the AGC-L0 scheme.
description: # Title of Dataset Equatorial waves for "A prediction attempt using
 equatorial waves for tropical sea surface temperature anomaly by Atlantic
 zonal mode" ## Description of the data and file structure The
 geopotential anomaly is averaged over the ATL3 region (3S-3N,20W-0). The
 potential energy flux includes six files each containing the record
 passing one meridional section (3S-3N) located at the equator. The data is
 binary dataset writing in GRADS format. Users can find description files
 with the extention of "ctl"
DOI: 10.5061/dryad.wstqjq2t6
title: EOU UK central heating on/off date micro-survey result 2017 to 2022

description: When do UK Twitter users (2017 to 2022) turn their central heating fully
 off, by month? This informal periodic survey on social media suggests that
 a substantial fraction of respondents (up to 10%) leave their central
 heating on year-round, which may lead to unnecessary energy consumption
 and carbon emissions.
description: UK Twitter followers' heating status was polled periodically
 from April 2017 to July 2022. The poll question changed
 slightly over time. Per-poll results are captured in
 the data.
description: # EOU UK Central Heating On/Off Date Micro-survey 2017 to 2022 Result
 [Data at DataDryad](https://doi.org/10.5061/dryad.wstqjq2t6)
 [Analysis](https://www.earth.org.uk/note-on-survey-UK-central-heating-on-off-dates.html) A series of informal polls were run between 2017 and 2022 inclusive, asking followers to report if their central heating system was on or off (or otherwise). These micro-survey results are individually reported, and collated to capture, for example, what fraction of central heating systems are left on all year. Results are roughly in-line with UK government surveys/reports suggesting that a significant fraction (single digit percent) of UK central heating systems are permanently left on, controlled only by the thermostat. One drive for the survey was to probe this fraction, since then heating can end up running unnecessarily on borderline days, or even cool days well away from the main heating season. ## Description of the data and file structure Poll data CSV, one survey record per row, with fields: poll start date, duration (d), Twitter link, total count, on count, off count, what-is-off count, other count. The structure is: * A header line. * One line per data record, each record being one poll result. * The records are in ascending date order. * The (poll start) date is in YYYY-MM-DD ISO 8601 format. * Each line/record contains comma-separated values for: * poll start date * poll duration (days) * Twitter poll link URL * vote count total * vote count "on" * vote count "off" * vote count "what's off?" * vote count "other" * The last ("other") value is nominally redundant. * An empty field represents a missing datum or zero count or not applicable. * The duration of initial polls was not recorded. * The "other" question was not asked on later polls. The CSV file stands alone, but links out to the Twitter polls. The data is described and analysed in https://www.earth.org.uk/note-on-survey-UK-central-heating-on-off-dates.html ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * https://www.earth.org.uk/data/UKCHOnOff/UKCHOnOff-poll-data.csv Data was derived from the following sources: * Twitter polls created by the author.
DOI: 10.15468/dl.wb3kw9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Indigofera australis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003780-260126135527185/datasets/export for details.
DOI: 10.5281/zenodo.14734046
title: Synthetic Health Sensor Data From Wearables With Stress Labels

description: Data stems from a adapted pipline of the models found in the paper:  Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress DetectionPlease cite this paper as reference.

Both are synthetic time-series datasets created from training GANs on the WESAD dataset.Each set features data for 10,000 subjects instead of just 15 found in the original.An important difference to the original is the reduction of labels to only: stress and non-stress.One is generated using a CGAN and the other a DGAN.

Used for testing re-identification attacks in: Slice it up: Unmasking User Identities in Smartwatch Health Data
DOI: 10.60905/eyeen9
title: Manifestaci��n de estudiantes ayer tarde en Medell��n

description: &lt;p&gt;Manifestaci��n con desfile pac��fico desde la UdeA hasta la plaza Nutibara con el motivo de visibilizar temas de la pol��tica nacional como lucha electoral, empobrecimiento y doctrina militar. Al llegar a la plaza los estudiantes hallaron resistencia para ingresar por parte de las fuerzas del orden, lo que form�� una pedrea y da��os a veh��culos de la polic��a. Protestaban adem��s por la presencia de los llamados ���Cuerpos de Paz��� en la universidad y los disturbios en Lorica (C��rdoba) y la UTP (Pereira).&lt;/p&gt;
description: CONTEXTO DE LA NOTICIA: Disputas pol��ticas entre China y Rusia, Debate entre Bavaria y Lleras por impuestos, Proyecto Musgrave en Colombia (Defensas y oposiciones), viajes de Pablo VI por Europa, impuesto a la gasolina, movimiento Golconda y curas rebeldes.
DOI: 10.5281/zenodo.14734045
title: Synthetic Health Sensor Data From Wearables With Stress Labels

description: Data stems from a adapted pipline of the models found in the paper:  Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress DetectionPlease cite this paper as reference.

Both are synthetic time-series datasets created from training GANs on the WESAD dataset.Each set features data for 10,000 subjects instead of just 15 found in the original.An important difference to the original is the reduction of labels to only: stress and non-stress.One is generated using a CGAN and the other a DGAN.

Used for testing re-identification attacks in: Slice it up: Unmasking User Identities in Smartwatch Health Data
DOI: 10.15468/dl.qvdq6t
title: Occurrence Download

description: A dataset containing 7269 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-96.24032 15.73044,-96.22811 15.74064,-96.2266 15.74904,-96.25689 15.76848,-96.2722 15.76309,-96.27232 15.76946,-96.2923 15.78944,-96.29897 15.79167,-96.30449 15.80306,-96.31038 15.81075,-96.32872 15.81073,-96.3387 15.80862,-96.35873 15.79807,-96.36594 15.78912,-96.37734 15.78582,-96.38829 15.78576,-96.40393 15.78816,-96.40808 15.78424,-96.41688 15.78158,-96.4329 15.78004,-96.44648 15.77287,-96.4526 15.76687,-96.45554 15.75891,-96.46497 15.75629,-96.46804 15.75,-96.47453 15.74812,-96.49166 15.7538,-96.50597 15.74752,-96.50574 15.72252,-96.49812 15.72055,-96.49219 15.71604,-96.47393 15.7098,-96.46379 15.70884,-96.45709 15.71086,-96.4511 15.70304,-96.44153 15.69697,-96.44044 15.69217,-96.43226 15.69568,-96.41883 15.69573,-96.39344 15.6896,-96.37903 15.68972,-96.35998 15.68396,-96.35219 15.6902,-96.33909 15.68581,-96.33322 15.68986,-96.31188 15.68681,-96.30991 15.69677,-96.30391 15.70927,-96.28972 15.71726,-96.28045 15.72779,-96.27223 15.72771,-96.26041 15.72076,-96.24857 15.72235,-96.24523 15.7312,-96.24032 15.73044))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 7269 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003781-260126135527185/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/14654440
title: Peer-to-Peer Boliviano (BOB) Exchange Data