cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.m37pvmdg1
title: <strong>Wind resource assessment and energy modelling of smaller outer islands in Fiji</strong>

description: This study assesses and models the wind resources and energy potential of
 five smaller outer islands in Fiji that are not connected to the central
 electricity grid. Long-term wind data spanning approximately 9 – 11 years
 were analyzed using the Wind Atlas Analysis and Application Program
 (WAsP). High-resolution wind resource maps were generated and evaluated
 for each island site.   Results indicated that Yasawa and Koro
 Islands have a higher wind potential, with mean wind speeds of 7.01 m/s
 and 6.47 m/s and corresponding wind power densities (WPD) of 335 W/m² and
 339 W/m², respectively, indicating suitability for utility-scale wind
 power applications. The islands of Gau, Ovalau, and Taveuni exhibit
 moderate wind speeds ranging from 4.26 m/s to 4.82 m/s, indicating
 potential for standalone or hybrid renewable energy systems. The modelled
 wind farms have installed capacities of 0.8 MW to 10 MW, yielding annual
 energy productions (AEP) of 4.23 GWh/year to 22.97 GWh/year. These AEPs
 are sufficient to meet the energy demand of the islands. The analysis
 highlights the spatial mismatch between island-wide grid-average wind
 resources and localized turbine micro-siting conditions, emphasizing the
 importance of site-specific assessment in complex island terrain. These
 findings support wind energy integration into Fiji’s renewable energy
 transition in outer islands without grid-connected electricity, align with
 Fiji’s UNFCCC Nationally Determined Contribution (NDC) targets, and
 support Sustainable Development Goals SDG 7 (Affordable and Clean Energy)
 and SDG 13 (Climate Action).
description: # <strong>Wind resource assessment and energy modelling of smaller
 outer islands in Fiji</strong> Dataset DOI:
 [10.5061/dryad.m37pvmdg1](10.5061/dryad.m37pvmdg1) ## Description of the
 data and file structure The files contain the Wind Atlas Application and
 Analysis Program (WAsP) model files for wind resource assessment and
 energy modelling for Gau, Koro, Levuka, Taveuni and Yasawa Islands in
 Fiji.  ## Files and Variables File 1: Energy_modeling_(Gau_Island).wwh
 File 2: Energy_Modeling_(Koro)__(4_Turbines).wwh File 3:
 Energy_Modeling_(Levuka)_11GWh(20_Turbines).wwh File 4:
 Energy_Modelling_(Taveuni)_AEP_22GWh(36_Turbines).wwh File 5:
 Energy_Modeling_(Yasawa)_AEP_4.3GWh(4_Turbines).wwh **Description:** This
 WAsP Files contain all the modelling data for the research paper. ##
 Code/software Wind Atlas Application and Analysis Program (WAsP) Version
 12.9 is needed to view the files. Even if you just install WAsP12.9 you
 should be able to view all the modelling workspace, parameters, variables
 and results. For WAsP to perform calculations for the modelling, a valid
 license from Denmark Technical University is required.
DOI: 10.15468/dl.s8s4gd
title: Occurrence Download

description: A dataset containing 1175106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ghana",
 {
 "or" : [
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "Geometry POLYGON((-2.21869 6.59328,-2.15898 6.59328,-2.11617 6.66121,-2.03607 6.76094,-2.10311 6.80627,-2.12411 6.85715,-2.13247 6.82735,-2.16466 6.81917,-2.19676 6.72486,-2.21263 6.68902,-2.21869 6.68902,-2.21869 6.59328))"
 ]
 },
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1175106 records from 598 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015615-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ea9k4n
title: Occurrence Download

description: A dataset containing 23559 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Espeletia"
 ]
}

 The dataset includes 23559 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015678-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18633284
title: BO'LAJAK MUSIQA O'QITUVCHILARINING PEDAGOGIK MAHORATINI RIVOJLANTIRISH METODIKASI

description: Mazkur maqolada bo‘lajak musiqa o‘qituvchilarining pedagogik mahoratini rivojlantirishning nazariy asoslari va amaliy metodik jihatlari tahlil qilinadi. Zamonaviy ta’lim tizimida musiqa ta’limining sifatini oshirish o‘qituvchining kasbiy kompetensiyasi, ijodiy yondashuvi hamda pedagogik texnologiyalarni samarali qo‘llay olish qobiliyati bilan bevosita bog‘liq ekani asoslab beriladi. Tadqiqot doirasida pedagogik mahorat tushunchasining tarkibiy komponentlari - metodik tayyorgarlik, kommunikativ kompetensiya, ijodkorlik, refleksiv yondashuv va innovatsion faoliyat elementlari tizimli ravishda yoritiladi. Shuningdek, musiqa o‘qituvchilarini tayyorlash jarayonida interfaol metodlar, amaliy mashg‘ulotlar, sahnaviy faoliyat, integrativ yondashuv hamda axborot-kommunikatsiya texnologiyalaridan foydalanishning metodik imkoniyatlari ko‘rib chiqiladi. Tadqiqot natijalari bo‘lajak pedagoglarning kasbiy shakllanish jarayonini takomillashtirishga xizmat qiluvchi samarali metodik modelni ishlab chiqish zarurligini ko‘rsatadi. Maqola musiqa ta’limi sohasida pedagogik tayyorgarlikni modernizatsiya qilishga qaratilgan ilmiy-amaliy tavsiyalar bilan boyitilgan.
DOI: 10.5281/zenodo.18633285
title: BO'LAJAK MUSIQA O'QITUVCHILARINING PEDAGOGIK MAHORATINI RIVOJLANTIRISH METODIKASI

description: Mazkur maqolada bo‘lajak musiqa o‘qituvchilarining pedagogik mahoratini rivojlantirishning nazariy asoslari va amaliy metodik jihatlari tahlil qilinadi. Zamonaviy ta’lim tizimida musiqa ta’limining sifatini oshirish o‘qituvchining kasbiy kompetensiyasi, ijodiy yondashuvi hamda pedagogik texnologiyalarni samarali qo‘llay olish qobiliyati bilan bevosita bog‘liq ekani asoslab beriladi. Tadqiqot doirasida pedagogik mahorat tushunchasining tarkibiy komponentlari - metodik tayyorgarlik, kommunikativ kompetensiya, ijodkorlik, refleksiv yondashuv va innovatsion faoliyat elementlari tizimli ravishda yoritiladi. Shuningdek, musiqa o‘qituvchilarini tayyorlash jarayonida interfaol metodlar, amaliy mashg‘ulotlar, sahnaviy faoliyat, integrativ yondashuv hamda axborot-kommunikatsiya texnologiyalaridan foydalanishning metodik imkoniyatlari ko‘rib chiqiladi. Tadqiqot natijalari bo‘lajak pedagoglarning kasbiy shakllanish jarayonini takomillashtirishga xizmat qiluvchi samarali metodik modelni ishlab chiqish zarurligini ko‘rsatadi. Maqola musiqa ta’limi sohasida pedagogik tayyorgarlikni modernizatsiya qilishga qaratilgan ilmiy-amaliy tavsiyalar bilan boyitilgan.
DOI: 10.15468/dl.ykcfyr
title: Occurrence Download

description: A dataset containing 314 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Espeletia occidentalis"
 ]
}

 The dataset includes 314 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015680-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wep4ek
title: Occurrence Download

description: A dataset containing 256 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Melanopsidium nigrum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 256 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015681-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/jnbxze
title: network_application_fig1.jpg

description: produced by running compute_example_fig1.R
DOI: 10.57745/ol9d8l
title: res_all_8_datasets.rds

description: produced by running compute_example_fig1.R
DOI: 10.57745/rcdn2g
title: heatmap_50_figS2.jpg

description: produced by running compute_performance_supplementary.R
DOI: 10.57745/ubcb48
title: graphs.zip

description: contains 8 graphs, each one for a dataset
DOI: 10.57745/xrbkwa
title: heatmap_100-1000_figS1.jpg

description: produced by running compute_performance_supplementary.R
DOI: 10.57745/cjwmrn
title: exec_time_figS3.jpg

description: produced by running execution_time/compute_execution_time_supplementary.R
DOI: 10.57745/jqgolp
title: performances.zip

description: contains: (1) folders res_nX/ corresponding to NeighborFinder results for each simulated sample size X tested, a file corresponds to one dataset ; (2) scores/ with nX/ folders gathering scores calculated when comparing the ground truth with the previous results ; (3) truth/ containing for each dataset an edge table of true neighbors based on the graph produced in graphs/
DOI: 10.57745/dnngxi
title: time_high_prev_species_NF.rds

description: produced by running execution_time/compute_execution_time_supplementary.R
DOI: 10.57745/1ah9dh
title: compute_example_fig1.R

description: source code used to produce an illustration example of the NeighborFinder method, the corresponding network and edge table can be found in the example/ folder
DOI: 10.57745/jwsqu1
title: compute_execution_time_supplementary.R

description: source code that was used to produce the figure S3 in execution_time/
DOI: 10.57745/ggvr0w
title: compute_performance_supplementary.R

description: source code that was used to produce the figures S1 and S2 in performance_figures/, 
included in the Supplementary Material of the Application Note
DOI: 10.57745/wx5isf
title: compute_example_fig1.R

description: source code used to produce an illustration example of the NeighborFinder method, the corresponding network and edge table can be found in the example/ folder
DOI: 10.57745/yxjflj
title: compute_execution_time_supplementary.R

description: source code that was used to produce the figure S3 in execution_time/
DOI: 10.57745/nwmizc
title: compute_performance_supplementary.R

description: source code that was used to produce the figures S1 and S2 in performance_figures/, 
included in the Supplementary Material of the Application Note
DOI: 10.57745/b7fxm1
title: graphs.zip

description: contains 8 graphs, each one for a dataset
DOI: 10.57745/gtamh3
title: res_all_8_datasets.rds

description: produced by running compute_example_fig1.R
DOI: 10.57745/hjlww4
title: Supplementary Material - NeighborFinder paper

description: NeighborFinder is an R package that implements a local network inference method designed for microbiome data. It enables the targeted discovery of direct neighbors around a species of interest. This repository contains the files and code needed to reproduce the figures presented in the article: "NeighborFinder: an R package inferring local microbial network around a species of interest" (Sola, M. et al., 2025). It also contains the intermediate files needed to evaluate NeighborFinder's performance, as well as the corresponding R script for calculating them from semi-synthetic datasets.
DOI: 10.57745/ukyj0x
title: performances.zip

description: contains: (1) folders res_nX/ corresponding to NeighborFinder results for each simulated sample size X tested, a file corresponds to one dataset ; (2) scores/ with nX/ folders gathering scores calculated when comparing the ground truth with the previous results ; (3) truth/ containing for each dataset an edge table of true neighbors based on the graph produced in graphs/
DOI: 10.25345/c5h708d7n
title: MassIVE MSV000100837 - Astrocyte exosomes as vehicles for the transmission of neuroinflammation post-infection and post-traumatic brain injury
title: Many patients develop chronic neurological symptoms following SARS-CoV-2 infection (neurological long COVID) that may reflect a state of heightened and persistent neuroinflammation. Chronic neuroinflammation is also observed in patients with post-concussion syndrome after (repeated incidences of) mild traumatic brain injury (mTBI). However, the combined impact of COVID-19 (infection) and mTBI (trauma) on neuroinflammation and brain health has not been previously investigated. Here, we show that patients with a combined history of COVID-19 and mTBI (COVID-19+mTBI+) have worsened neurological/psychological symptoms and increased biomarkers of neurodegeneration. Astrocyte-derived exosomes (ADEs) isolated from COVID-19-mTBI- patients (controls) do not affect primary astrocytes, but ADEs from COVID-19+mTBI+ patients induce striking astrocyte activation and marked alterations in cellular neurodegeneration signaling pathways. COVID-19+mTBI+ ADEs also cause reactive astrogliosis following intracerebral microinjection in naive mice. These findings suggest a novel paradigm whereby signals responsible for the chronic neuroinflammatory state in COVID-19+mTBI+ patients are stored as cargo in glial exosomes.
DOI: 10.15139/s3/wgkujd
title: Data Management and Sharing Plan for: Reaching persons with HIV who are out of care through Expedited access to Long-Acting Injectable antiretroviral therapy -

description: The Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data.
description: Data Management and Sharing Plan
DOI: 10.5281/zenodo.18505414
title: 1. CARINA.WP2.T2.5.Physical-chemical characterization. v1

description: This dataset refers also to CARINA Subtask 2.5.1 (Research, development, and formulation of biostimulants).
DOI: 10.5281/zenodo.18505413
title: 1. CARINA.WP2.T2.5.Physical-chemical characterization. v1

description: This dataset refers also to CARINA Subtask 2.5.1 (Research, development, and formulation of biostimulants).
DOI: 10.5281/zenodo.18606753
title: 4. CARINA.WP2.T2.5.2. Biostimulant tests. V1

description: Bio-tests will be performed at field conditions (greenhouse trials)

 

DOI: 10.5281/zenodo.18606754

License: Creative Commons Attribution Non Commercial No Derivatives 4.0 International
DOI: 10.5281/zenodo.18606754
title: 4. CARINA.WP2.T2.5.2. Biostimulant tests. V1

description: Bio-tests will be performed at field conditions (greenhouse trials)

 

DOI: 10.5281/zenodo.18606754

License: Creative Commons Attribution Non Commercial No Derivatives 4.0 International
DOI: 10.15468/dl.96m8tu
title: Occurrence Download

description: A dataset containing 460 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Blepharocarya involucrigera",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 460 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015684-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18633308
title: ВНЕДРЕНИЕ FINTECH-РЕШЕНИЙ В БАНКОВСКОЙ СИСТЕМЕ И ИХ ЭФФЕКТИВНОСТЬ

description: В статье исследуются процессы внедрения FinTech-решений в банковской системе и анализируется их экономическая и организационная эффективность. Рассматриваются ключевые направления цифровой трансформации банков, включая мобильный банкинг, искусственный интеллект, блокчейн-технологии, автоматизацию бизнес-процессов и системы Big Data. Проведен анализ влияния финансовых технологий на снижение операционных издержек, повышение качества обслуживания клиентов и оптимизацию управления рисками. Особое внимание уделено вопросам кибербезопасности и нормативно-правового регулирования. На основе сравнительного и системного анализа выявлены основные преимущества и риски интеграции FinTech в банковскую инфраструктуру. Результаты исследования демонстрируют, что эффективное внедрение цифровых технологий способствует повышению конкурентоспособности банков, расширению финансовой инклюзии и устойчивости финансового сектора в условиях цифровой экономики.
DOI: 10.5281/zenodo.18633307
title: ВНЕДРЕНИЕ FINTECH-РЕШЕНИЙ В БАНКОВСКОЙ СИСТЕМЕ И ИХ ЭФФЕКТИВНОСТЬ

description: В статье исследуются процессы внедрения FinTech-решений в банковской системе и анализируется их экономическая и организационная эффективность. Рассматриваются ключевые направления цифровой трансформации банков, включая мобильный банкинг, искусственный интеллект, блокчейн-технологии, автоматизацию бизнес-процессов и системы Big Data. Проведен анализ влияния финансовых технологий на снижение операционных издержек, повышение качества обслуживания клиентов и оптимизацию управления рисками. Особое внимание уделено вопросам кибербезопасности и нормативно-правового регулирования. На основе сравнительного и системного анализа выявлены основные преимущества и риски интеграции FinTech в банковскую инфраструктуру. Результаты исследования демонстрируют, что эффективное внедрение цифровых технологий способствует повышению конкурентоспособности банков, расширению финансовой инклюзии и устойчивости финансового сектора в условиях цифровой экономики.
DOI: 10.15468/dl.b64w6u
title: Occurrence Download

description: A dataset containing 9087 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Heliconiaceae"
 ]
}

 The dataset includes 9087 records from 242 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015683-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18632974
title: Brandenburg-S12-CropVal: A Sentinel-1/2 Multi-Modal Cropland Segmentation Dataset for Cross-Regional Transferability Assessment (Brandenburg, Germany, 2024)

description: Brandenburg-S12-CropVal is a large-scale, multi-modal remote sensing dataset covering the entire federal state of Brandenburg, Germany (~29,500 km²), designed for evaluating the cross-regional and cross-sensor generalization capability of cropland segmentation models. Developed as part of the CrossModMamba study, it complements the training dataset HSR-MFCS (https://doi.org/10.5281/zenodo.17054418) from Sichuan, China. The dataset comprises Sentinel-2 Level-2A surface reflectance imagery (RGB bands B4, B3, B2) and Sentinel-1 GRD SAR imagery (VV and VH polarizations, IW mode, descending orbit) acquired during the 2024 growing season, all processed on Google Earth Engine. Cloud contamination was mitigated using the S2_CLOUD_PROBABILITY dataset and QA60 quality band, retaining only clear-sky observations. Reference labels were derived from official parcel-level crop type vector polygons for 2024 provided by the Brandenburg State Office for Surveying and Geoinformation (LGB), standardized according to the EuroCrops HCAT3 hierarchical taxonomy and consolidated into binary classes: cropland (all cultivated agricultural parcels) and non-cropland (forests, water bodies, built-up areas, and bare land). All layers are co-registered at 10 m spatial resolution and projected to EPSG:32633 (WGS 84 / UTM zone 33N). This dataset enables a stringent assessment of model transferability across five simultaneous domain shifts: (1) geographic region (East Asia → Central Europe), (2) sensor platform (Gaofen-1/3 → Sentinel-1/2), (3) spatial resolution (4 m → 10 m), (4) landscape structure (fragmented hilly terraces → large-scale consolidated plains), and (5) crop phenology and management practices. In the CrossModMamba study, the model trained exclusively on Sichuan HSR-MFCS data was applied to this dataset, demonstrating robust cross-domain generalization.
DOI: 10.5281/zenodo.18632973
title: Brandenburg-S12-CropVal: A Sentinel-1/2 Multi-Modal Cropland Segmentation Dataset for Cross-Regional Transferability Assessment (Brandenburg, Germany, 2024)

description: Brandenburg-S12-CropVal is a large-scale, multi-modal remote sensing dataset covering the entire federal state of Brandenburg, Germany (~29,500 km²), designed for evaluating the cross-regional and cross-sensor generalization capability of cropland segmentation models. Developed as part of the CrossModMamba study, it complements the training dataset HSR-MFCS (https://doi.org/10.5281/zenodo.17054418) from Sichuan, China. The dataset comprises Sentinel-2 Level-2A surface reflectance imagery (RGB bands B4, B3, B2) and Sentinel-1 GRD SAR imagery (VV and VH polarizations, IW mode, descending orbit) acquired during the 2024 growing season, all processed on Google Earth Engine. Cloud contamination was mitigated using the S2_CLOUD_PROBABILITY dataset and QA60 quality band, retaining only clear-sky observations. Reference labels were derived from official parcel-level crop type vector polygons for 2024 provided by the Brandenburg State Office for Surveying and Geoinformation (LGB), standardized according to the EuroCrops HCAT3 hierarchical taxonomy and consolidated into binary classes: cropland (all cultivated agricultural parcels) and non-cropland (forests, water bodies, built-up areas, and bare land). All layers are co-registered at 10 m spatial resolution and projected to EPSG:32633 (WGS 84 / UTM zone 33N). This dataset enables a stringent assessment of model transferability across five simultaneous domain shifts: (1) geographic region (East Asia → Central Europe), (2) sensor platform (Gaofen-1/3 → Sentinel-1/2), (3) spatial resolution (4 m → 10 m), (4) landscape structure (fragmented hilly terraces → large-scale consolidated plains), and (5) crop phenology and management practices. In the CrossModMamba study, the model trained exclusively on Sichuan HSR-MFCS data was applied to this dataset, demonstrating robust cross-domain generalization.
DOI: 10.5281/zenodo.18632787
title: Supporting Information for: Dynamic Stabilization of HMG-CoA Reductase through Optimized Flavonoid Scaffolds: A Mechanistic Investigation of Kaempferol and Apigenin Analogues

description: Supporting Information for: 



Dynamic Stabilization of HMG-CoA Reductase through Optimized Flavonoid Scaffolds: A Mechanistic Investigation of Kaempferol and Apigenin Analogues



 

By Yoshua B. Mtulo, James E. Mgaya, Anthony A. Tepeli, Andrew S. Paluch and Lucas Paul*

 

*lucas.paul@udsm.ac.tz

 

Submitted to ChemistrySelect, 13 February 2026

 

ADMET

This folder includes five files, each containing the SMILES string used for ADMET analysis.

 

Within the folders " kaempferol" and "apigenin" we provide tabulated spreadsheets of the respective Ligand SMILES and CHEMBL ID.
DOI: 10.5281/zenodo.18632788
title: Supporting Information for: Dynamic Stabilization of HMG-CoA Reductase through Optimized Flavonoid Scaffolds: A Mechanistic Investigation of Kaempferol and Apigenin Analogues

description: Supporting Information for: 



Dynamic Stabilization of HMG-CoA Reductase through Optimized Flavonoid Scaffolds: A Mechanistic Investigation of Kaempferol and Apigenin Analogues



 

By Yoshua B. Mtulo, James E. Mgaya, Anthony A. Tepeli, Andrew S. Paluch and Lucas Paul*

 

*lucas.paul@udsm.ac.tz

 

Submitted to ChemistrySelect, 13 February 2026

 

ADMET

This folder includes five files, each containing the SMILES string used for ADMET analysis.

 

Within the folders " kaempferol" and "apigenin" we provide tabulated spreadsheets of the respective Ligand SMILES and CHEMBL ID.
DOI: 10.15468/dl.u9kcxn
title: Occurrence Download

description: A dataset containing 27445 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Otis tarda",
 "Year 2020-2026"
 ]
}

 The dataset includes 27445 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015685-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.