cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34740/kaggle/dsv/13727299
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.twnsg8
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.3688 22.04913, -107.2188 22.04913, -107.2188 22.19913, -107.3688 22.19913, -107.3688 22.04913))"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032551-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17605920
title: ХРОНИЧЕСКИЕ ВОСПАЛИТЕЛЬНЫЕ ЗАБОЛЕВАНИЯ ПЛАЦЕНТЫ, АССОЦИИРОВАННЫЕ С РЕЦИДИВИРУЮЩИМИ НЕБЛАГОПРИЯТНЫМИ ИСХОДАМИ БЕРЕМЕННОСТИ
DOI: 10.5281/zenodo.17605921
title: ХРОНИЧЕСКИЕ ВОСПАЛИТЕЛЬНЫЕ ЗАБОЛЕВАНИЯ ПЛАЦЕНТЫ, АССОЦИИРОВАННЫЕ С РЕЦИДИВИРУЮЩИМИ НЕБЛАГОПРИЯТНЫМИ ИСХОДАМИ БЕРЕМЕННОСТИ
DOI: 10.15468/dl.y4cvuf
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.2188 22.04913, -107.0688 22.04913, -107.0688 22.19913, -107.2188 22.19913, -107.2188 22.04913))"
 ]
}

 The dataset includes 17 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032552-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17605939
title: PTPN22 GENETIC VARIANTS AS PREDICTORS OF DISEASE SEVERITY AND JOINT DESTRUCTION IN RHEUMATOID ARTHRITIS: EVIDENCE FROM THE UZBEK POPULATION
DOI: 10.5281/zenodo.17605938
title: PTPN22 GENETIC VARIANTS AS PREDICTORS OF DISEASE SEVERITY AND JOINT DESTRUCTION IN RHEUMATOID ARTHRITIS: EVIDENCE FROM THE UZBEK POPULATION
DOI: 10.15468/dl.a2pwpa
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.0688 22.04913, -106.9188 22.04913, -106.9188 22.19913, -107.0688 22.19913, -107.0688 22.04913))"
 ]
}

 The dataset includes 70 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032554-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2kek73
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Fossil)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tupaia minor"
 ]
}

 The dataset includes 208 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032555-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4g83tm
title: Occurrence Download

description: A dataset containing 148114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Solanum",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1999",
 "Year is less than or equal to 2025",
 "Country is one of (Australia)"
 ]
}

 The dataset includes 148114 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032543-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ycvt7e
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.9188 22.04913, -106.7688 22.04913, -106.7688 22.19913, -106.9188 22.19913, -106.9188 22.04913))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032556-251025141854904/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.30514106
title: Supplementary data file from A total evidence approach justifies taxonomic splitting of the endangered <i>Pecos Gambusia</i> into three species

description: A list of the samples collected including the genus and species identified through hybrid analysis if the sample was from Gambusia affinis, G. geiseri or G. nobilis. Musuem collection abbreviations:
DOI: 10.6084/m9.figshare.30514106.v1
title: Supplementary data file from A total evidence approach justifies taxonomic splitting of the endangered Pecos Gambusia into three species

description: A list of the samples collected including the genus and species identified through hybrid analysis if the sample was from Gambusia affinis, G. geiseri or G. nobilis. Musuem collection abbreviations:
DOI: 10.6084/m9.figshare.30514106.v2
title: Supplementary data file from A total evidence approach justifies taxonomic splitting of the endangered <i>Pecos Gambusia</i> into three species

description: A list of the samples collected including the genus and species identified through hybrid analysis if the sample was from Gambusia affinis, G. geiseri or G. nobilis. Musuem collection abbreviations:
DOI: 10.6084/m9.figshare.30616550
title: <b>Exploring the scale-specific effects of nature and human factors on perennial rice yield using a multi-scale modeling framework</b>

description: Rice is consumed as a staple food by approximately 50% of the global population. As the world’s largest producer of rice, China’s consistent and reliable production levels have a substantial impact on global food security. Yield formation mechanisms exhibit significant spatial heterogeneity due to diverse environments, requiring analysis of multi-factor interactions and scale effects. This study employs an integrated Optimal Parameters-based Geodetector (OPGD) and Multi-scale Geographically Weighted Regression (MGWR) framework to identify key drivers and quantify their spatial scales across China’s perennial rice systems. Results show that hydrothermal conditions, distance to geological hazards (DistDisas), potassium fertilizer application (M2), and soil pH are dominant factors, with all pairs exhibiting nonlinear synergies. MGWR further revealed distinct operational scales: M2 and distance from residential areas acted as large-scale, universally consistent factors. Soil pH, GDP, and slope length and steepness operated at medium scales with regional variation. Soil bulk density, pesticide usage, DistDisas, fertilizer usage, and climate conditions were small-scale factors with high spatial heterogeneity. These findings underscore that yield formation emerges from multi-scale interactions between natural and human factors, affirming the necessity of scale-explicit approaches for accurate yield prediction and targeted agricultural management.
DOI: 10.6084/m9.figshare.30616550.v1
title: <b>Exploring the scale-specific effects of nature and human factors on perennial rice yield using a multi-scale modeling framework</b>

description: Rice is consumed as a staple food by approximately 50% of the global population. As the world’s largest producer of rice, China’s consistent and reliable production levels have a substantial impact on global food security. Yield formation mechanisms exhibit significant spatial heterogeneity due to diverse environments, requiring analysis of multi-factor interactions and scale effects. This study employs an integrated Optimal Parameters-based Geodetector (OPGD) and Multi-scale Geographically Weighted Regression (MGWR) framework to identify key drivers and quantify their spatial scales across China’s perennial rice systems. Results show that hydrothermal conditions, distance to geological hazards (DistDisas), potassium fertilizer application (M2), and soil pH are dominant factors, with all pairs exhibiting nonlinear synergies. MGWR further revealed distinct operational scales: M2 and distance from residential areas acted as large-scale, universally consistent factors. Soil pH, GDP, and slope length and steepness operated at medium scales with regional variation. Soil bulk density, pesticide usage, DistDisas, fertilizer usage, and climate conditions were small-scale factors with high spatial heterogeneity. These findings underscore that yield formation emerges from multi-scale interactions between natural and human factors, affirming the necessity of scale-explicit approaches for accurate yield prediction and targeted agricultural management.
DOI: 10.5281/zenodo.17605965
title: EFFECTIVENESS OF DIGITAL EMPLOYMENT PLATFORMS IN REDUCING YOUTH UNEMPLOYMENT IN UZBEKISTAN
DOI: 10.5281/zenodo.17605966
title: EFFECTIVENESS OF DIGITAL EMPLOYMENT PLATFORMS IN REDUCING YOUTH UNEMPLOYMENT IN UZBEKISTAN
DOI: 10.15468/dl.rp9hej
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.7688 22.04913, -106.6188 22.04913, -106.6188 22.19913, -106.7688 22.19913, -106.7688 22.04913))"
 ]
}

 The dataset includes 33 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032557-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17605946
title: Supplementary Data

description: This file includes Supplementary Data related to "Resistance to Sustainability Transformations and Ways to Overcome It", available from https://dx.doi.org/10.2139/ssrn.5547898
DOI: 10.5281/zenodo.17605947
title: Supplementary Data

description: This file includes Supplementary Data related to "Resistance to Sustainability Transformations and Ways to Overcome It", available from https://dx.doi.org/10.2139/ssrn.5547898
DOI: 10.5281/zenodo.17488054
title: A Stem-Like Tumor Cell Population Defines a Therapeutically Vulnerable Niche in SMARCB1-Deficient Sinonasal Carcinoma

description: SMARCB1-deficient sinonasal carcinoma (SDSC) is a rare, highly aggressive malignancy with dismal prognosis, limited therapeutic options and no established preclinical models. To address this gap, we combined single-nucleus RNA sequencing (snRNAseq), spatial transcriptomics, and ex vivo patient-derived tissue slice culture (TSC) to dissect intratumoral heterogeneity, microenvironmental niches, and treatment vulnerabilities in an index case of SDSC.

snRNAseq revealed three transcriptionally distinct malignant subpopulations. Among these, we identified two specialized subsets: one marked by ALDH1A1, a gene associated with stemness, and another characterized by NTN4 expression. Spatial analysis mapped these populations to discrete tumor niches. Notably, the ALDH1A1+ compartment localized to a basal layer with intermingled TP63 expressing basal cells adjacent to stroma, showed reduced proliferative activity and displayed transcription factor activity consistent with a stem-like state. Ex vivo TSC drug testing revealed striking selective vulnerability: the mTOR inhibitor Sapanisertib induced extensive tumor necrosis and completely ablated both ALDH1A1+ and NTN4+ subpopulations. Gene set enrichment analysis provided mechanistic insight, confirming significant enrichment of PI3K-AKT-mTOR signaling specifically in ALDH1A1+ tumor cells. Additionally, Sapanisertib markedly reduced endothelial cells, consistent with anti-angiogenic effects.

To validate the broader relevance of these findings, we analyzed an independent cohort of 12 SDSC, including recurrent tumors. ALDH1A1 expression was present in all cases across three spatial patterns, with particularly high levels in recurrences compared to primaries, supporting a recurrence-founder role. Furthermore, strong mesothelin expression was observed in both the index patient as well as a subset of the retrospective cohort, suggesting additional therapeutic opportunities with mesothelin-directed antibody-drug conjugates (ADC).

Together, this study provides the most comprehensive molecular and functional characterization of SDSC to date. By uncovering a stem-like, ALDH1A1+ niche vulnerable to mTOR inhibition as well as mesothelin as a potential target of ADCs, our work highlights actionable biology in this otherwise lethal and understudied tumor entity.

This repository holds unprocessed Seurat objects for the snRNAseq and Xenium spatial transcriptomics datasets generated in this study.
DOI: 10.5281/zenodo.17605928
title: A Stem-Like Tumor Cell Population Defines a Therapeutically Vulnerable Niche in SMARCB1-Deficient Sinonasal Carcinoma

description: SMARCB1-deficient sinonasal carcinoma (SDSC) is a rare, highly aggressive malignancy with dismal prognosis, limited therapeutic options and no established preclinical models. To address this gap, we combined single-nucleus RNA sequencing (snRNAseq), spatial transcriptomics, and ex vivo patient-derived tissue slice culture (TSC) to dissect intratumoral heterogeneity, microenvironmental niches, and treatment vulnerabilities in an index case of SDSC.

snRNAseq revealed three transcriptionally distinct malignant subpopulations. Among these, we identified two specialized subsets: one marked by ALDH1A1, a gene associated with stemness, and another characterized by NTN4 expression. Spatial analysis mapped these populations to discrete tumor niches. Notably, the ALDH1A1+ compartment localized to a basal layer with intermingled TP63 expressing basal cells adjacent to stroma, showed reduced proliferative activity and displayed transcription factor activity consistent with a stem-like state. Ex vivo TSC drug testing revealed striking selective vulnerability: the mTOR inhibitor Sapanisertib induced extensive tumor necrosis and completely ablated both ALDH1A1+ and NTN4+ subpopulations. Gene set enrichment analysis provided mechanistic insight, confirming significant enrichment of PI3K-AKT-mTOR signaling specifically in ALDH1A1+ tumor cells. Additionally, Sapanisertib markedly reduced endothelial cells, consistent with anti-angiogenic effects.

To validate the broader relevance of these findings, we analyzed an independent cohort of 12 SDSC, including recurrent tumors. ALDH1A1 expression was present in all cases across three spatial patterns, with particularly high levels in recurrences compared to primaries, supporting a recurrence-founder role. Furthermore, strong mesothelin expression was observed in both the index patient as well as a subset of the retrospective cohort, suggesting additional therapeutic opportunities with mesothelin-directed antibody-drug conjugates (ADC).

Together, this study provides the most comprehensive molecular and functional characterization of SDSC to date. By uncovering a stem-like, ALDH1A1+ niche vulnerable to mTOR inhibition as well as mesothelin as a potential target of ADCs, our work highlights actionable biology in this otherwise lethal and understudied tumor entity.

This repository holds unprocessed Seurat objects for the snRNAseq and Xenium spatial transcriptomics datasets generated in this study.
DOI: 10.15468/dl.sjr594
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.6188 22.04913, -106.4688 22.04913, -106.4688 22.19913, -106.6188 22.19913, -106.6188 22.04913))"
 ]
}

 The dataset includes 61 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032558-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25442/hku.30530507
title: <i>Supporting data for “Synergising Circular Economy (CE) principles with Design for Manufacturing and Assembly (DfMA) to facilitate circularity in modular buildings: A construction value chain approach”</i>

description: The dataset includes data collected for the PhD research titled '<i>Synergising Circular Economy (CE) principles with Design for Manufacturing and Assembly (DfMA) to facilitate circularity in modular buildings: A construction value chain approach</i>'. The research focuses on applying CE principles in IC projects, specifically in modular construction in a WLC approach through the theoretical lens of value. Contextually, the scope of this study is limited to the design stage of a building, envisaging systemic building design. The topological scope of the research includes modular construction projects in ‘industrialising regions’ to explore the environmental impact, specifically in terms of material consumption and the resultant WLC economic impact in the BCI. This research uses a mixed method to realise the stipulated research aim. Data was collected in several steps: Preliminary Interviews, Questionnaire Survey, Delphi Study, Case study, and Validation Interviews. This dataset includes transcripts of the interviews and the records of the data collection platform “Qualtrics” used for the surveys. Anonymity was maintained throughout the data collection process, and codes were used to identify the participants.
DOI: 10.25442/hku.30530507.v1
title: <i>Supporting data for “Synergising Circular Economy (CE) principles with Design for Manufacturing and Assembly (DfMA) to facilitate circularity in modular buildings: A construction value chain approach”</i>

description: The dataset includes data collected for the PhD research titled '<i>Synergising Circular Economy (CE) principles with Design for Manufacturing and Assembly (DfMA) to facilitate circularity in modular buildings: A construction value chain approach</i>'. The research focuses on applying CE principles in IC projects, specifically in modular construction in a WLC approach through the theoretical lens of value. Contextually, the scope of this study is limited to the design stage of a building, envisaging systemic building design. The topological scope of the research includes modular construction projects in ‘industrialising regions’ to explore the environmental impact, specifically in terms of material consumption and the resultant WLC economic impact in the BCI. This research uses a mixed method to realise the stipulated research aim. Data was collected in several steps: Preliminary Interviews, Questionnaire Survey, Delphi Study, Case study, and Validation Interviews. This dataset includes transcripts of the interviews and the records of the data collection platform “Qualtrics” used for the surveys. Anonymity was maintained throughout the data collection process, and codes were used to identify the participants.
DOI: 10.5281/zenodo.17605981
title: DEVELOPMENT OF THE ENTERPRISE OPERATIONAL STRATEGY
DOI: 10.5281/zenodo.17605982
title: DEVELOPMENT OF THE ENTERPRISE OPERATIONAL STRATEGY
DOI: 10.5281/zenodo.17605987
title: SEAMM Package List

description: The package list for the SEAMM environment, also complete conda environment files with and without the version pinned.
DOI: 10.25919/j7m4-c815
title: NBDL-HSJ5FXX2Q85923
DOI: 10.25919/jzws-fg84
title: NBDL-HSJ5FXXBH8542Z
DOI: 10.25919/0kb4-xa89
title: NBDL-HSJ5FXX7H85HEF
DOI: 10.25919/22g2-2q62
title: NBDL-HSJ5FXWAQ8V853
DOI: 10.25919/xfwz-vb75
title: NBDL-HSJ5FXW1N8VX4Q
DOI: 10.25919/n9d1-gn70
title: NBDL-HSJ5FXYFJ863ZA
DOI: 10.25919/y6wm-7y08
title: NBDL-HSJ5FXVDP8XJC0
DOI: 10.25919/6eb0-8d57
title: NBDL-HSJ5FXV4G8X9CW
DOI: 10.15468/dl.grfsbz
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.4688 22.04913, -106.3188 22.04913, -106.3188 22.19913, -106.4688 22.19913, -106.4688 22.04913))"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032560-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zrmbj7
title: Occurrence Download

description: A dataset containing 8106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Centaurea solstitialis"
 ]
}

 The dataset includes 8106 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032559-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/4c8r-p449
title: NBDL-HSJ5FXX4K85NSB
DOI: 10.25919/54z3-5376
title: NBDL-HSJ5FXWCK8VMRB
DOI: 10.25919/8980-w056
title: NBDL-HSJ5FY30M5VAWG
DOI: 10.25919/pb80-ba57
title: NBDL-HSJ5FY1NN5XHYH
DOI: 10.25919/9r9n-nm63
title: NBDL-HSJ5FXV6M8XC9M
DOI: 10.25919/5eb5-b253
title: NBDL-HSJ5FY1SN5X841
DOI: 10.25919/e31w-h804
title: NBDL-HSJ5FXXJQ843R3
DOI: 10.25919/k5kx-cz55
title: NBDL-HSJ5FXVQJ8W4XR
DOI: 10.25919/qy2n-ny19
title: NBDL-HSJ5FXVAM8XA04
DOI: 10.25919/pxgs-tx50
title: NBDL-HSJ5FY1TQ5XCZD
DOI: 10.25919/72jb-sz02
title: NBDL-HSJ5FXVTM8WD64
DOI: 10.25919/akve-h769
title: NBDL-HSJ5FXVSP8WFBG
DOI: 10.25919/1830-j140
title: NBDL-HSJ5FY1PQ5XA9X
DOI: 10.25919/wnjs-2983
title: NBDL-HSJ5FXVCG8XWHW
DOI: 10.25919/c2q3-3796
title: NBDL-HSJ5FXW4K8VRDB
DOI: 10.25919/1jfg-q349
title: NBDL-HSJ5FY0GK5J3BN
DOI: 10.25919/rsvz-sn70
title: NBDL-HSJ5FXW0K8VJJV
DOI: 10.25919/91vq-4489
title: NBDL-HSJ5FY09N5JHE1
DOI: 10.25919/23ed-md45
title: NBDL-HSJ5FXW2Q8VZP3
DOI: 10.25919/31ez-fa85
title: NBDL-HSJ5FXX6Q85PWK
DOI: 10.25919/eaem-sa35
title: NBDL-HSJ5FXVBJ8XBY8
DOI: 10.25919/0vf8-vn60
title: NBDL-HSJ5FXV8G8XQ7C
DOI: 10.25919/61yh-6r80
title: NBDL-HSJ5FXZ3J873ET
DOI: 10.25919/tebz-7t62
title: NBDL-HSJ5FY2VJ5V564
DOI: 10.25919/m46j-b766
title: NBDL-HSJ5FXV9P8XMNG
DOI: 10.25919/f2ry-c674
title: NBDL-HSJ5FXZQJ87WAA
DOI: 10.25919/7ccg-k424
title: NBDL-HSJ5FXX8K8TRXV
DOI: 10.25919/kaqx-0h17
title: NBDL-HSJ5FXV5P8XEV0
DOI: 10.25919/w7fw-7b74
title: NBDL-HSJ5FXX3H85BQZ
DOI: 10.25919/g94b-k619
title: NBDL-HSJ5FXX5N85MB7
DOI: 10.25919/jtvs-tb49
title: NBDL-HSJ5FXWDN8VQA7
DOI: 10.25919/2kmm-g825
title: NBDL-HSJ5FY0YQ5KN8X
DOI: 10.25919/fjzd-4h64
title: NBDL-HSJ5FY3HP5TC4C
DOI: 10.25919/ma17-3c89
title: NBDL-HSJ5FXVEM8XKTM
DOI: 10.25919/swha-xw54
title: NBDL-HSJ5FXW8K8VF1V
DOI: 10.25919/ense-6v72
title: NBDL-HSJ5FY0VH5KXMS
DOI: 10.25919/7nw1-8x63
title: NBDL-HSJ5FXYSP8178J
DOI: 10.25919/fjxe-h440
title: NBDL-HSJ5FXW6Q8T50K
DOI: 10.25919/naxm-0y26
title: NBDL-HSJ5FXVFJ8XH8R
DOI: 10.25919/v342-g502
title: NBDL-HSJ5FXW7H8T7JF
DOI: 10.25919/5gf0-3w84
title: NBDL-HSJ5FXVMG8W02W
DOI: 10.25919/b3zt-d204
title: NBDL-HSJ5FXW3H8VSVZ
DOI: 10.25919/8jga-fc15
title: NBDL-HSJ5FXW5N8VTZ7
DOI: 10.15468/dl.eccjx6
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.3188 22.04913, -106.1688 22.04913, -106.1688 22.19913, -106.3188 22.19913, -106.3188 22.04913))"
 ]
}

 The dataset includes 81 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032561-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2dhyt6
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Fossil)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tupaia dorsalis"
 ]
}

 The dataset includes 13 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032562-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.