cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17711785
title: MMHOI Dataset: Modeling Complex 3D Multi-Human Multi-Object Interactions

description: Introduction

The MMHOI dataset addresses the challenge of modeling real-world scenes with multiple humans and objects interacting in causal, goal-oriented, or cooperative ways. Existing 3D human-object interaction (HOI) benchmarks capture only a subset of these complex interactions. MMHOI closes this gap by providing a large-scale dataset with comprehensive 3D shape and pose annotations for every person and object, covering 78 action categories and 14 interaction-specific body parts across 12 everyday scenarios. MMHOI is designed to foster research in multi-human multi-object interactions and serves as a benchmark for next-generation HOI algorithms. All necessary data for training, validation, and testing are publicly released.

At a Glance

Unzipped Size: 173 GB

The unzipped folder contains a README.md that describes the contents of each subfolder.

Contents:



20240418_personM_personC_from4C_all_30skip_start-end: 13G

20240417_personM_personC_to3C_finish: 1.7G

20240418_personB_personC_noC1andC2_all_30_skip_start-end: 3.1G

20240412_personA_personC: 19G

20240508_personJ_personK_30_skip_start-end: 16G

20240423_personB_personC_and_C2_all__start-end: 3.3G

20240417_personM_personB_finish: 4.6G

20240508_personE_personD_all_30skip_start-end: 17G

Single20240531_personA_all_30skip_start-end: 4.2G

20240412_personA_personB: 24G

20240426_personL_personC_all_30skip_start-end: 17G

20240424_personB_personD_all_start-end: 13G

20240510_personH_personI: 16G

20240426_personB_personG_all_30skip_start-end: 7.0G

20240423_personM_personC_30_skip_all_start-end: 17G


Other Resources

The code associated with the approach will be released separately on GitHub.

Citation

If you use the MMHOI dataset in your research, please cite our contribution:



@inproceedings{cherian2021insegan,
    title={MMHOI: Modeling Complex 3D Multi-Human Multi-Object Interactions},
    author={K. Kogashi, A. Cherian, and M-Y. J. Kuo},
    booktitle={Proceedings of the Winter Conference on Applications of Computer Vision},
    year={2026}
}


License

The MMHOI dataset is released under CC-BY-SA-4.0 license.

All data:

Created by Mitsubishi Electric Research Laboratories (MERL), 2025-2026

SPDX-License-Identifier: CC-BY-SA-4.0
DOI: 10.15468/dl.a9wdk7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-119.6105 35.64822, -119.6101 35.64822, -119.6096 35.64824, -119.6091 35.64828, -119.6087 35.64834, -119.6082 35.64842, -119.6078 35.64852, -119.6073 35.64864, -119.6069 35.64878, -119.6065 35.64893, -119.6061 35.6491, -119.6057 35.64929, -119.6053 35.6495, -119.6049 35.64972, -119.6045 35.64996, -119.6042 35.65021, -119.6039 35.65048, -119.6035 35.65076, -119.6032 35.65105, -119.603 35.65136, -119.6027 35.65168, -119.6025 35.652, -119.6023 35.65234, -119.6021 35.65269, -119.6019 35.65304, -119.6018 35.6534, -119.6016 35.65376, -119.6015 35.65413, -119.6015 35.65451, -119.6014 35.65488, -119.6014 35.65526, -119.6014 35.65564, -119.6015 35.66039, -119.6015 35.66077, -119.6015 35.66116, -119.6016 35.66154, -119.6017 35.66192, -119.6018 35.66229, -119.602 35.66266, -119.6021 35.66302, -119.6023 35.66337, -119.6025 35.66371, -119.6028 35.66405, -119.603 35.66437, -119.6033 35.66469, -119.6036 35.66499, -119.6039 35.66527, -119.6043 35.66555, -119.6046 35.66581, -119.605 35.66605, -119.6054 35.66628, -119.6058 35.66649, -119.6062 35.66668, -119.6066 35.66685, -119.607 35.66701, -119.6075 35.66715, -119.6079 35.66727, -119.6084 35.66736, -119.6088 35.66744, -119.6093 35.6675, -119.6098 35.66754, -119.6103 35.66756, -119.6148 35.66764, -119.6152 35.66764, -119.6157 35.66762, -119.6162 35.66758, -119.6167 35.66751, -119.6171 35.66743, -119.6176 35.66733, -119.618 35.66721, -119.6185 35.66707, -119.6189 35.66691, -119.6193 35.66673, -119.6197 35.66654, -119.6201 35.66633, -119.6205 35.6661, -119.6209 35.66585, -119.6212 35.66559, -119.6215 35.66532, -119.6219 35.66503, -119.6222 35.66473, -119.6224 35.66442, -119.6227 35.66409, -119.6229 35.66376, -119.6231 35.66341, -119.6233 35.66306, -119.6235 35.6627, -119.6236 35.66233, -119.6237 35.66196, -119.6238 35.66158, -119.6239 35.6612, -119.6239 35.66082, -119.624 35.66044, -119.624 35.65588, -119.624 35.6555, -119.624 35.65512, -119.6239 35.65474, -119.6239 35.65437, -119.6237 35.654, -119.6236 35.65363, -119.6235 35.65327, -119.6233 35.65292, -119.6231 35.65257, -119.6229 35.65224, -119.6226 35.65191, -119.6224 35.65159, -119.6221 35.65129, -119.6218 35.65099, -119.6215 35.65071, -119.6212 35.65045, -119.6208 35.65019, -119.6204 35.64996, -119.6201 35.64974, -119.6197 35.64953, -119.6193 35.64935, -119.6188 35.64918, -119.6184 35.64902, -119.618 35.64889, -119.6175 35.64878, -119.6171 35.64868, -119.6166 35.6486, -119.6162 35.64855, -119.6157 35.64851, -119.611 35.64823, -119.6105 35.64822))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021253-251120083545085/datasets/export for details.
DOI: 10.15468/dl.b2xbvb
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dahlia campanulata"
 ]
}

 The dataset includes 37 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021254-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18112/openneuro.ds007006.v1.0.0
title: VR-Compassion Cultivation Training
DOI: 10.15468/dl.4yp929
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-115.7165 34.19703, -115.7161 34.19708, -115.7156 34.19714, -115.7151 34.19723, -115.7147 34.19734, -115.7142 34.19746, -115.7138 34.19761, -115.7134 34.19777, -115.7129 34.19795, -115.7125 34.19815, -115.7121 34.19837, -115.7118 34.19861, -115.7114 34.19886, -115.7111 34.19912, -115.7107 34.1994, -115.7104 34.1997, -115.7101 34.2, -115.7099 34.20032, -115.7096 34.20066, -115.7094 34.201, -115.7092 34.20135, -115.709 34.20171, -115.7088 34.20208, -115.7087 34.20245, -115.7086 34.20283, -115.7085 34.20321, -115.7084 34.2036, -115.7084 34.20399, -115.7084 34.20438, -115.7084 34.20477, -115.7085 34.20733, -115.7085 34.20772, -115.7086 34.2081, -115.7087 34.20848, -115.7088 34.20886, -115.7089 34.20923, -115.7091 34.20959, -115.7092 34.20995, -115.7094 34.2103, -115.7097 34.21064, -115.7099 34.21097, -115.7102 34.21129, -115.7104 34.2116, -115.7107 34.2119, -115.7111 34.21218, -115.7114 34.21245, -115.7117 34.2127, -115.7121 34.21294, -115.7125 34.21317, -115.7129 34.21337, -115.7133 34.21356, -115.7137 34.21373, -115.7141 34.21389, -115.7146 34.21402, -115.715 34.21414, -115.7155 34.21423, -115.7159 34.21431, -115.7164 34.21437, -115.7168 34.21441, -115.7173 34.21442, -115.7178 34.21442, -115.7182 34.2144, -115.7209 34.21422, -115.7213 34.21417, -115.7218 34.21411, -115.7223 34.21402, -115.7227 34.21392, -115.7232 34.21379, -115.7236 34.21365, -115.7241 34.21348, -115.7245 34.2133, -115.7249 34.2131, -115.7253 34.21288, -115.7257 34.21264, -115.7261 34.21239, -115.7264 34.21212, -115.7267 34.21184, -115.727 34.21154, -115.7273 34.21123, -115.7276 34.21091, -115.7279 34.21057, -115.7281 34.21023, -115.7283 34.20987, -115.7285 34.20951, -115.7287 34.20913, -115.7288 34.20876, -115.7289 34.20837, -115.729 34.20799, -115.7291 34.20759, -115.7291 34.2072, -115.7291 34.20681, -115.7291 34.20433, -115.7291 34.20395, -115.7291 34.20356, -115.729 34.20318, -115.7289 34.2028, -115.7288 34.20243, -115.7287 34.20206, -115.7285 34.20169, -115.7283 34.20134, -115.7281 34.20099, -115.7279 34.20065, -115.7277 34.20032, -115.7274 34.2, -115.7271 34.1997, -115.7268 34.1994, -115.7265 34.19912, -115.7262 34.19885, -115.7258 34.1986, -115.7255 34.19836, -115.7251 34.19814, -115.7247 34.19794, -115.7243 34.19775, -115.7238 34.19758, -115.7234 34.19743, -115.723 34.1973, -115.7225 34.19719, -115.7221 34.19709, -115.7216 34.19702, -115.7212 34.19696, -115.7207 34.19693, -115.7202 34.19691, -115.7198 34.19692, -115.717 34.19701, -115.7165 34.19703))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021255-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.17488826
title: Performance Evaluation and Cross-Validation of Low-Cost Particulate Matter Sensors for Environmental Research

description: This dataset serves as supplementary material for the publication:  Performance Evaluation and Cross-Validation of Low-Cost Particulate Matter Sensors for Environmental Research

The data, derivatievs and statistics were collected from the METER.AC network (https://meter.ac/), an open-access, real-time environmental monitoring system with a well-distributed array of sensors across Bulgaria.

 

Acknowledgement: This study is financed by the European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, project № BG-RRP-2.004-0001-C01
DOI: 10.5281/zenodo.17488827
title: Performance Evaluation and Cross-Validation of Low-Cost Particulate Matter Sensors for Environmental Research

description: This dataset serves as supplementary material for the publication:  Performance Evaluation and Cross-Validation of Low-Cost Particulate Matter Sensors for Environmental Research

The data, derivatievs and statistics were collected from the METER.AC network (https://meter.ac/), an open-access, real-time environmental monitoring system with a well-distributed array of sensors across Bulgaria.

 

Acknowledgement: This study is financed by the European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, project № BG-RRP-2.004-0001-C01
DOI: 10.5281/zenodo.16807221
title: Cloud Physics Lidar Level 1 & 2 Data Products from the GLOVE Field Campaign

description: The Cloud Physics LiDAR (CPL) dataset consists of backscatter coefficient, lidar depolarization ratio, layer top/base height, layer type, particulate extinction coefficient, ice water content, and layer/cumulative optical depth data collected from the CPL onboard the NASA ER-2 high-altitude research aircraft in support of the Goddard Space Flight Center's Lidar Observation and Validation Experiment (GLOVE) field campaign. The main goals of GLOVE were to validate atmospheric data products from the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) and the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite missions. GLOVE was based out of NASA Armstrong Flight Research Center at Edwards Air Force Base in California. The dataset files are available in HDF-5 format from February 03 to 20, 2025. A user's guide, with file formats, is included in this repository as a pdf file.
DOI: 10.5281/zenodo.16807220
title: Cloud Physics Lidar Level 1 & 2 Data Products from the GLOVE Field Campaign

description: The Cloud Physics LiDAR (CPL) dataset consists of backscatter coefficient, lidar depolarization ratio, layer top/base height, layer type, particulate extinction coefficient, ice water content, and layer/cumulative optical depth data collected from the CPL onboard the NASA ER-2 high-altitude research aircraft in support of the Goddard Space Flight Center's Lidar Observation and Validation Experiment (GLOVE) field campaign. The main goals of GLOVE were to validate atmospheric data products from the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) and the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite missions. GLOVE was based out of NASA Armstrong Flight Research Center at Edwards Air Force Base in California. The dataset files are available in HDF-5 format from February 03 to 20, 2025. A user's guide, with file formats, is included in this repository as a pdf file.
DOI: 10.15468/dl.x9mxmr
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "TaxonKey is Utricularia praeterita"
 ]
}

 The dataset includes 18 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021256-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v8zw2y
title: Occurrence Download

description: A dataset containing 417733 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((17.857971 59.327702, 17.989807 59.327702, 17.989807 59.39349, 17.857971 59.39349, 17.857971 59.327702))"
 ]
}

 The dataset includes 417733 records from 83 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021221-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.neb4ns
title: Occurrence Download

description: A dataset containing 197 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Olax triplinervia"
 ]
}

 The dataset includes 197 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021258-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4jkh23
title: Occurrence Download

description: A dataset containing 4449 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Benin",
 "OccurrenceStatus is Present",
 "TaxonKey is Adansonia digitata"
 ]
}

 The dataset includes 4449 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021259-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26301/nkv2-bn91
title: Bimaristan Nur al-Din

description: The digital documentation of Bimaristan Nur al-Din was part of Project Anqa, a collaboration between CyArk, the International Council on Monuments and Sites (ICOMOS), and Carleton University with funding support from the UK based charity, Arcadia Foundation. Responding to the catastrophic loss of heritage in the Middle East, the project seeks to further protect monuments through training local heritage professionals in digital preservation techniques. In partnership with the UNESCO Office for the Preservation of Syrian Cultural Heritage, CyArk trained Syrian heritage professionals in Lebanon to carry out the digital documentation of six sites in Damascus, including Bimaristan Nur al-Din.
description: Over eight centuries old, the Bimaristan Nur al-Din, is the earliest surviving site for the development of Islamic medicine. Throughout the building's lifetime, the site has functioned as a medical school as well as a place of healing in the heart of the old city of Damascus. Built in 1154, the building is characterized by its red brick muqarnas, elaborate entrance block, and finely carved wooden doors. The hospital was in use until the 20th century when it was converted into a Museum of Arabic Medicine and Science. The preservation of the building is a reminder of the major contributions of Islamic medicine to the world today.
description: LiDAR - Terrestrial, Photogrammetry - Terrestrial
DOI: 10.5281/zenodo.17675675
title: Bottom Temperature and Dissolved Oxygen Saturation in Sechura Bay

description: This dataset contains oceanographic records of bottom temperature (°C) and dissolved oxygen saturation (%) from Argopecten purpuratus (Peruvian scallop) bottom-culture, in the Constante production zone, Sechura Bay (Peru). Data cover the period from 07 November 2013 to 26 March 2019, recorded at hourly intervals. Measurements were obtained using MiniDOT datalogger (PME Inc., Vista, CA) installed 0.2 m above the seafloor on a metal frame by semi-autonomous diving. The data recorded in the table correspond to temperature (Temp_fond), dissolved oxygen saturation (DO_sat), and the time in UTC−05:00 (Hora_Lima). The fixed station was located in Constante (5°40’33.3” S, 80°54’1.6” W).

A portion of these environmental records has been previously used in peer-reviewed publications, including:





Cueto-Vega, R., Flye-Sainte-Marie, J., Aguirre-Velarde, A., Jean, F., Gil-Kodaka, P., and Thouzeau, G. (2022). Size-based survival of cultured Argopecten purpuratus (L, 1819) under severe hypoxia. Journal of the World Aquaculture Society, 53(1), 151–173. https://doi.org/10.1111/jwas.12777




Kluger, L., Kochalski, S., Aguirre-Velarde, A., Vivar, I., and Wolff, M. (2019). Coping with abrupt environmental change: The impact of the coastal El Niño 2017 on artisanal fisheries and mariculture in North Peru. ICES Journal of Marine Science, 76. https://doi.org/10.1093/icesjms/fsy171



The complete compiled dataset was provided by A. Aguirre-Velarde and R. Cueto-Vega and has been harmonized for use in the manuscript “Biological Response Matrix for risk management of bottom-cultured Peruvian scallops under oxygen deficiency, temperature, and exposure-time stressors” (in review). The unified database supports the analysis of environmental variability during years with and without mass-mortality events of A. purpuratus, and the development of a Biological Response Matrix .
DOI: 10.5281/zenodo.17675676
title: Bottom Temperature and Dissolved Oxygen Saturation in Sechura Bay

description: This dataset contains oceanographic records of bottom temperature (°C) and dissolved oxygen saturation (%) from Argopecten purpuratus (Peruvian scallop) bottom-culture, in the Constante production zone, Sechura Bay (Peru). Data cover the period from 07 November 2013 to 26 March 2019, recorded at hourly intervals. Measurements were obtained using MiniDOT datalogger (PME Inc., Vista, CA) installed 0.2 m above the seafloor on a metal frame by semi-autonomous diving. The data recorded in the table correspond to temperature (Temp_fond), dissolved oxygen saturation (DO_sat), and the time in UTC−05:00 (Hora_Lima). The fixed station was located in Constante (5°40’33.3” S, 80°54’1.6” W).

A portion of these environmental records has been previously used in peer-reviewed publications, including:





Cueto-Vega, R., Flye-Sainte-Marie, J., Aguirre-Velarde, A., Jean, F., Gil-Kodaka, P., and Thouzeau, G. (2022). Size-based survival of cultured Argopecten purpuratus (L, 1819) under severe hypoxia. Journal of the World Aquaculture Society, 53(1), 151–173. https://doi.org/10.1111/jwas.12777




Kluger, L., Kochalski, S., Aguirre-Velarde, A., Vivar, I., and Wolff, M. (2019). Coping with abrupt environmental change: The impact of the coastal El Niño 2017 on artisanal fisheries and mariculture in North Peru. ICES Journal of Marine Science, 76. https://doi.org/10.1093/icesjms/fsy171



The complete compiled dataset was provided by A. Aguirre-Velarde and R. Cueto-Vega and has been harmonized for use in the manuscript “Biological Response Matrix for risk management of bottom-cultured Peruvian scallops under oxygen deficiency, temperature, and exposure-time stressors” (in review). The unified database supports the analysis of environmental variability during years with and without mass-mortality events of A. purpuratus, and the development of a Biological Response Matrix .
DOI: 10.15468/dl.9kehmx
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-115.6602 34.7711, -115.6597 34.7712, -115.6593 34.77131, -115.6588 34.77145, -115.6584 34.77161, -115.658 34.77178, -115.6576 34.77198, -115.6572 34.77219, -115.6568 34.77242, -115.6564 34.77266, -115.6561 34.77292, -115.6557 34.7732, -115.6554 34.77349, -115.6551 34.77379, -115.6548 34.7741, -115.6546 34.77443, -115.6543 34.77477, -115.6541 34.77511, -115.6539 34.77547, -115.6538 34.77584, -115.6536 34.77621, -115.6535 34.77658, -115.6534 34.77696, -115.6533 34.77735, -115.6533 34.77774, -115.6533 34.77813, -115.6532 34.78102, -115.6532 34.78142, -115.6532 34.78182, -115.6533 34.78222, -115.6533 34.78261, -115.6535 34.783, -115.6536 34.78338, -115.6537 34.78376, -115.6539 34.78412, -115.6541 34.78449, -115.6544 34.78484, -115.6546 34.78518, -115.6549 34.78551, -115.6552 34.78582, -115.6555 34.78612, -115.6558 34.78641, -115.6573 34.78764, -115.6577 34.7879, -115.658 34.78815, -115.6584 34.78838, -115.6588 34.7886, -115.6592 34.7888, -115.6596 34.78898, -115.66 34.78914, -115.6604 34.78929, -115.6609 34.78942, -115.6613 34.78953, -115.6617 34.78962, -115.6622 34.78969, -115.6627 34.78974, -115.6631 34.78977, -115.6636 34.78979, -115.664 34.78978, -115.6645 34.78975, -115.665 34.78971, -115.6697 34.78914, -115.6702 34.78907, -115.6706 34.78898, -115.6711 34.78888, -115.6715 34.78875, -115.672 34.78861, -115.6724 34.78845, -115.6728 34.78826, -115.6732 34.78807, -115.6736 34.78785, -115.674 34.78762, -115.6744 34.78737, -115.6747 34.78711, -115.675 34.78683, -115.6753 34.78654, -115.6756 34.78623, -115.6759 34.78592, -115.6762 34.78559, -115.6764 34.78525, -115.6766 34.7849, -115.6768 34.78455, -115.6769 34.78418, -115.6771 34.78381, -115.6772 34.78344, -115.6773 34.78306, -115.6773 34.78268, -115.6774 34.78229, -115.6777 34.77778, -115.6777 34.7774, -115.6777 34.77702, -115.6777 34.77664, -115.6776 34.77626, -115.6776 34.77588, -115.6775 34.77551, -115.6773 34.77514, -115.6772 34.77478, -115.677 34.77443, -115.6768 34.77408, -115.6766 34.77374, -115.6764 34.77341, -115.6761 34.7731, -115.6758 34.77279, -115.6755 34.7725, -115.6752 34.77221, -115.6749 34.77195, -115.6746 34.77169, -115.6742 34.77145, -115.6738 34.77123, -115.6734 34.77102, -115.673 34.77083, -115.6726 34.77066, -115.6722 34.77051, -115.6718 34.77037, -115.6713 34.77025, -115.6709 34.77015, -115.6704 34.77007, -115.67 34.77001, -115.6695 34.76997, -115.669 34.76995, -115.6686 34.76995, -115.6681 34.76997, -115.6676 34.77, -115.6672 34.77006, -115.6607 34.77102, -115.6602 34.7711))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021257-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7aqaw3
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Olax wightiana"
 ]
}

 The dataset includes 51 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021260-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4m3mfr
title: Occurrence Download

description: A dataset listing the 29 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA.29.8_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Carnivora"
 ]
}

 The dataset's 29 records were derived from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021252-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.