cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/yhy-90w-808
title: Adenostyles alliariae subsp. orientalis (Boiss.) Greuter

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/10j-nfc-l3d
title: Diplazium donnell-smithii Christ

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/r1q-47s-zas
title: Achillea crithmifolia Waldst. & Kit.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/v05-p87-veh
title: Hemionitis pinnatifida Baker

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/vn3-m45-6xm
title: Hemionitis pinnatifida Baker

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/2v7-dpx-jcz
title: Verbascum speciosum Schrad.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/aqn-81s-hfn
title: Centaurea grisebachii subsp. occidentalis E. Gamal-Eldin & Wagenitz

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/4p8-h5h-zkq
title: Carduus tmoleus Boiss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/mcf-t8a-s0h
title: Achillea abrotanoides (Vis.) Vis.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/dj0-6am-rgy
title: Allium sardoum Moris

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/j5x-x96-6xk
title: Anthemis cretica (L.) L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/7kz-824-pyt
title: Parablechnum schiedeanum (Schltdl. ex C. Presl) Gasper & Salino

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/bd7-8rw-y3t
title: Centaurea salonitana Vis.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/x03-5j2-4hs
title: Veronica scutellata L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/ddv-v7b-qtq
title: Centaurea solstitialis subsp. solstitialis

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/wgg-rpj-8d8
title: Centaurea ptarmicifolia Halácsy ex Hayek

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/5q2-q8y-kqq
title: Digitalis ferruginea subsp. ferruginea

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/rnz-vph-hsq
title: Scrophularia aestivalis Griseb.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/2wf-25d-pt7
title: Verbascum longifolium Ten.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/znw-g17-bcs
title: Verbascum pulverulentum Vill.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/z03-7wt-fgx
title: Euphrasia L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.15468/dl.uea3a6
title: Occurrence Download

description: A dataset containing 26034 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chamaecrista nictitans"
 ]
}

 The dataset includes 26034 records from 555 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001871-250710112747441/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u9rfhw
title: Occurrence Download

description: A dataset containing 531 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Apodemus rusiges"
 ]
}

 The dataset includes 531 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017563-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g9zp8u
title: Occurrence Download

description: A dataset containing 223 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Diplusodon hirsutus",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 223 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017565-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18639527
title: Leishmania infantum (JPCM5) subcellular fractions, proteomics raw data and identified proteins

description: Project description.- Promastigotes of L. infantum JPCM5 strain were grown at 26 ◦C in Roswell Park Memorial Institute (RPMI) medium supplemented with 15% of heat-inactivated fetal bovine serum (FBS), hemin (10 μg/mL) and an antibiotic mix (streptomycin 10 μg/mL and penicillin 105 U/mL). Cultures (50 mL) were started at 5 × 105 cells/mL and the parasites were harvested in the middle logarithmic growth phase (107 promastigotes/mL). After washing twice with phosphate buffer saline (PBS), the pellets (5 × 108 cells) were processed using the Subcellular Protein Fractionation Kit for Cultured Cells (Cat. Number 78840; Thermofisher Scintific). As a result, four fractions were obtained and processed for proteomic analysis: F1, cytoplasmic fraction; F2, membranous fraction; F3, nuclear soluble fraction; F4, chromatin-bound fraction. The project aimed to analyze the subcellular distribution of L. infantum proteins in the promastigote stage. 

Sample processing protocol.- Each fraction was submitted to in-gel digestion using sequencing-grade trypsin (Promega, Madison, WI, USA) following the procedure described elsewhere (Adán-Jiménez et al., 2024). Peptide samples were analyzed by reverse phase-liquid chromatography (RP-LC)-MS/MS analysis (Dynamic Exclusion Mode) in an Easy-nLC 1200 system coupled to an ion trap LTQ-Orbitrap Velos Pro hybrid mass spectrometer (Thermo Scientific, Waltham, MA, USA).

Data processing protocol.- Peptide identification from raw data was carried out using the PEAKS Studio XPro search engine (Bioinformatics Solutions Inc.,Waterloo, ON, Canada) (Tran et al., 2019). Searches were performed against the most recent L. infantum proteome dataset available at Mendeley Data server (https://data.mendeley.com/datasets/dtmstvb2j5/2). The file protein.html contains the proteins identified from the four fractions.

The proteomic analysis was carried out in the CBM PROTEIN CHEMISTRY FACILITY, which belongs to ProteoRed.

References. 



Adán-Jiménez, J., Sánchez-Salvador, A., Morato, E., Solana, J. C., Aguado, B. and Requena, J. M. (2024). A Proteogenomic Approach to Unravel New Proteins Encoded in the Leishmania donovani (HU3) Genome. Genes 15, 775. doi: 10.3390/GENES15060775.

Tran, N. H., Qiao, R., Xin, L., Chen, X., Liu, C., Zhang, X., Shan, B., Ghodsi, A. and Li, M. (2019). Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry. Nature methods 16, 63–66. doi: 10.1038/S41592-018-0260-3.
DOI: 10.5281/zenodo.18639526
title: Leishmania infantum (JPCM5) subcellular fractions, proteomics raw data and identified proteins

description: Project description.- Promastigotes of L. infantum JPCM5 strain were grown at 26 ◦C in Roswell Park Memorial Institute (RPMI) medium supplemented with 15% of heat-inactivated fetal bovine serum (FBS), hemin (10 μg/mL) and an antibiotic mix (streptomycin 10 μg/mL and penicillin 105 U/mL). Cultures (50 mL) were started at 5 × 105 cells/mL and the parasites were harvested in the middle logarithmic growth phase (107 promastigotes/mL). After washing twice with phosphate buffer saline (PBS), the pellets (5 × 108 cells) were processed using the Subcellular Protein Fractionation Kit for Cultured Cells (Cat. Number 78840; Thermofisher Scintific). As a result, four fractions were obtained and processed for proteomic analysis: F1, cytoplasmic fraction; F2, membranous fraction; F3, nuclear soluble fraction; F4, chromatin-bound fraction. The project aimed to analyze the subcellular distribution of L. infantum proteins in the promastigote stage. 

Sample processing protocol.- Each fraction was submitted to in-gel digestion using sequencing-grade trypsin (Promega, Madison, WI, USA) following the procedure described elsewhere (Adán-Jiménez et al., 2024). Peptide samples were analyzed by reverse phase-liquid chromatography (RP-LC)-MS/MS analysis (Dynamic Exclusion Mode) in an Easy-nLC 1200 system coupled to an ion trap LTQ-Orbitrap Velos Pro hybrid mass spectrometer (Thermo Scientific, Waltham, MA, USA).

Data processing protocol.- Peptide identification from raw data was carried out using the PEAKS Studio XPro search engine (Bioinformatics Solutions Inc.,Waterloo, ON, Canada) (Tran et al., 2019). Searches were performed against the most recent L. infantum proteome dataset available at Mendeley Data server (https://data.mendeley.com/datasets/dtmstvb2j5/2). The file protein.html contains the proteins identified from the four fractions.

The proteomic analysis was carried out in the CBM PROTEIN CHEMISTRY FACILITY, which belongs to ProteoRed.

References. 



Adán-Jiménez, J., Sánchez-Salvador, A., Morato, E., Solana, J. C., Aguado, B. and Requena, J. M. (2024). A Proteogenomic Approach to Unravel New Proteins Encoded in the Leishmania donovani (HU3) Genome. Genes 15, 775. doi: 10.3390/GENES15060775.

Tran, N. H., Qiao, R., Xin, L., Chen, X., Liu, C., Zhang, X., Shan, B., Ghodsi, A. and Li, M. (2019). Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry. Nature methods 16, 63–66. doi: 10.1038/S41592-018-0260-3.
DOI: 10.15468/dl.7g4r3j
title: Occurrence Download

description: A dataset containing 17029 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Codonopsis"
 ]
}

 The dataset includes 17029 records from 261 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017566-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9kmx92
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stevia satureiifolium",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 13 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017574-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fkzpvq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphiocarpus petelotii",
 "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/0017573-260208012135463/datasets/export for details.
DOI: 10.15468/dl.cbh3p4
title: Occurrence Download

description: A dataset containing 111 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "DatasetKey is Royal Botanic Gardens, Kew - Herbarium Specimens",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Combretum hereroense"
 ]
}

 The dataset includes 111 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017568-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jbkwqf
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((59.71287 33.86971,92.85613 33.86971,92.85613 47.12134,59.71287 47.12134,59.71287 33.86971))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Natrix tessellata"
 ]
}

 The dataset includes 133 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017572-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.44jegj
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Diplusodon orbicularis",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 149 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017575-260208012135463/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.29070506
title: Fatigue Classification by ML_2paper

description: To enhance the interpretability and predictive performance of the classification models, this study first conducted paired sample t-tests on all eye-tracking features to identify those with statistically significant differences before and after visual fatigue. A total of eight features were found to be significant (p &lt; 0.05), including four linear parameters (FC_10, FC_25, OL_10, OL_25), two spatial parameters related to gaze dispersion (Radius_50 and Dist_CM), and two nonlinear complexity indicators (SamEn_x and SamEn_y). These selected features encompass multiple dimensions, including fixation density (fixation count), fixation duration (observation length), spatial dispersion of gaze (fixation dispersion), and signal complexity of gaze trajectories (Sample Entropy), providing both behavioral-level and signal-structure-level insights into changes associated with visual fatigue. In the subsequent AI classification phase, three types of models were constructed: one based on linear features (FC_10, FC_25, OL_10, OL_25, Radius_50, Dist_CM), one based on nonlinear features (SamEn_x, SamEn_y), and a hybrid model combining both linear and nonlinear features. These feature sets were input into three supervised machine learning algorithms—Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN)—for comparative analysis. Model performance was comprehensively evaluated using metrics such as AUC, Accuracy, Precision, Recall, and F1-score, in order to assess the contribution and discriminative power of different feature types in identifying visual fatigue.
DOI: 10.6084/m9.figshare.29070506.v5
title: Fatigue Classification by ML_2paper

description: To enhance the interpretability and predictive performance of the classification models, this study first conducted paired sample t-tests on all eye-tracking features to identify those with statistically significant differences before and after visual fatigue. A total of eight features were found to be significant (p &lt; 0.05), including four linear parameters (FC_10, FC_25, OL_10, OL_25), two spatial parameters related to gaze dispersion (Radius_50 and Dist_CM), and two nonlinear complexity indicators (SamEn_x and SamEn_y). These selected features encompass multiple dimensions, including fixation density (fixation count), fixation duration (observation length), spatial dispersion of gaze (fixation dispersion), and signal complexity of gaze trajectories (Sample Entropy), providing both behavioral-level and signal-structure-level insights into changes associated with visual fatigue. In the subsequent AI classification phase, three types of models were constructed: one based on linear features (FC_10, FC_25, OL_10, OL_25, Radius_50, Dist_CM), one based on nonlinear features (SamEn_x, SamEn_y), and a hybrid model combining both linear and nonlinear features. These feature sets were input into three supervised machine learning algorithms—Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN)—for comparative analysis. Model performance was comprehensively evaluated using metrics such as AUC, Accuracy, Precision, Recall, and F1-score, in order to assess the contribution and discriminative power of different feature types in identifying visual fatigue.
DOI: 10.6084/m9.figshare.29070506.v4
title: Fatigue Classification by ML_2paper

description: To enhance the interpretability and predictive performance of the classification models, this study first conducted paired sample t-tests on all eye-tracking features to identify those with statistically significant differences before and after visual fatigue. A total of eight features were found to be significant (p &lt; 0.05), including four linear parameters (FC_10, FC_25, OL_10, OL_25), two spatial parameters related to gaze dispersion (Radius_50 and Dist_CM), and two nonlinear complexity indicators (SamEn_x and SamEn_y). These selected features encompass multiple dimensions, including fixation density (fixation count), fixation duration (observation length), spatial dispersion of gaze (fixation dispersion), and signal complexity of gaze trajectories (Sample Entropy), providing both behavioral-level and signal-structure-level insights into changes associated with visual fatigue. In the subsequent AI classification phase, three types of models were constructed: one based on linear features (FC_10, FC_25, OL_10, OL_25, Radius_50, Dist_CM), one based on nonlinear features (SamEn_x, SamEn_y), and a hybrid model combining both linear and nonlinear features. These feature sets were input into three supervised machine learning algorithms—Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN)—for comparative analysis. Model performance was comprehensively evaluated using metrics such as AUC, Accuracy, Precision, Recall, and F1-score, in order to assess the contribution and discriminative power of different feature types in identifying visual fatigue.
DOI: 10.15468/dl.bmam34
title: Occurrence Download

description: A dataset containing 25253398 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.classificationdetails['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c']['specieskey'] &lt;&gt; '' AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 25253398 records were derived from 71260 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017535-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ycp8fr
title: Occurrence Download

description: A dataset containing 253 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Reldia minutiflora",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 253 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017576-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.umvc2f
title: Occurrence Download

description: A dataset containing 1042 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Senna corymbosa",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 1042 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017577-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5sx4dx
title: Occurrence Download

description: A dataset containing 2354 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Echinolaena inflexa",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 2354 records from 123 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017578-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k8m88w
title: Occurrence Download

description: A dataset containing 608 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arctictis binturong"
 ]
}

 The dataset includes 608 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017579-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4sjzbc
title: Occurrence Download

description: A dataset containing 700 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhabdothamnus solandri",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 700 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017581-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yut873
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arctictis binturong albifrons"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017580-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.