cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jhyjva
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Helluomorphoides papago (Casey, 1913)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 45 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008600-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57830/2311571
title: Southeast Alaska I&M Network Water Quality Data Package (FQ_Q) for monitoring years 2010-2024 at Sitka National Historical Park

description: This data set is a comma-separated values (CSV) file containing continuous hourly water quality observations of the Indian River in Sitka National Historical Park for monitoring years 2010-2024. The core parameters collected are water temperature, dissolved oxygen, pH, and conductivity, obtained from multiparameter sondes during the ice-free season. Turbidity was added to the monitoring effort starting in 2023. Using the Aquarius Time-Series application, data have been quality controlled, graded against formal criteria specified in the protocol (SOP 7, Data Evaluation and Grading in Aquarius), drift corrected where appropriate, and certified for publication. The data set (CSV) and associated metadata are zipped into a site-specific archive (ZIP file), identified as the FQ_Q deliverable in the water quality protocol.
DOI: 10.57830/2311570
title: Southeast Alaska I&M Network Water Quality Data Package (FQ_Q) for monitoring years 2010-2024 at Glacier Bay National Park and Preserve

description: This data set is a comma-separated values (CSV) file containing continuous hourly water quality observations of the Salmon River in Glacier Bay National Park and Preserve for monitoring years 2010-2024. The core parameters collected are water temperature, dissolved oxygen, pH, and conductivity, obtained from multiparameter sondes during the ice-free season. Using the Aquarius Time-Series application, data have been quality controlled, graded against formal criteria specified in the protocol (SOP 7, Data Evaluation and Grading in Aquarius), drift corrected where appropriate, and certified for publication. The data set (CSV) and associated metadata are zipped into a site-specific archive (ZIP file), identified as the FQ_Q deliverable in the water quality protocol.
DOI: 10.57830/2311567
title: Southeast Alaska I&M Network Water Quality Data Package (FQ_Q) for monitoring years 2011-2024 at Klondike Gold Rush National Historical Park

description: This data set is a comma-separated values (CSV) file containing continuous hourly water quality observations of the Taiya River in Klondike Gold Rush National Historical Park for monitoring years 2011-2024. The core parameters collected are water temperature, dissolved oxygen, pH, turbidity, and conductivity, obtained from multiparameter sondes during the ice-free season. Using the Aquarius Time-Series application, data have been quality controlled, graded against formal criteria specified in the protocol (SOP 7, Data Evaluation and Grading in Aquarius), drift corrected where appropriate, and certified for publication. The data set (CSV) and associated metadata are zipped into a site-specific archive (ZIP file), identified as the FQ_Q deliverable in the water quality protocol.
DOI: 10.15468/dl.tjwh25
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Oreanthes Benth."
 ]
}

 The dataset includes 103 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008601-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18269455
title: Croton urucurana Baill. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.18269454
title: Croton urucurana Baill. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.18269315
title: SuperDARN data in netCDF format (1994-Dec)

description: 1994-Dec SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6832923
title: SuperDARN data in netCDF format (1994-Dec)

description: 1994-Dec SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.15468/dl.fsgxp9
title: Occurrence Download

description: A dataset containing 1058 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Specimen)",
 "OccurrenceStatus is Present",
 "TaxonKey is Urva edwardsii"
 ]
}

 The dataset includes 1058 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014331-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rhvmv5
title: Occurrence Download

description: A dataset containing 39120 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Academy of Natural Sciences of Philadelphia Herpetology Collection"
 ]
}

 The dataset includes 39120 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014330-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15770/eum_sec_clm_1009
title: Radio Occultation Processing Package version 12 - Multimission
DOI: 10.5281/zenodo.18269456
title: Croton uruguayensis Baill. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.18269457
title: Croton uruguayensis Baill. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.15468/dl.pyvsxe
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Specimen)",
 "OccurrenceStatus is Present",
 "TaxonKey is Urva fusca"
 ]
}

 The dataset includes 82 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014332-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c2equ9
title: Occurrence Download

description: A dataset containing 4258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((21.31132 38.8507,183.04352 38.8507,183.04352 77.28748,21.31132 77.28748,21.31132 38.8507))",
 "HasCoordinate is true",
 "TaxonKey is Melanohalea"
 ]
}

 The dataset includes 4258 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014333-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34882/dezim.nadira-rr-cati.download.1.0.0
title: Rassistische Realitäten
DOI: 10.15468/dl.mkzg39
title: Occurrence Download

description: A dataset containing 1178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trifolium montanum)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 1178 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014335-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hj3d23
title: Occurrence Download

description: A dataset containing 200 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Specimen)",
 "OccurrenceStatus is Present",
 "TaxonKey is Urva javanica"
 ]
}

 The dataset includes 200 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014334-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34882/dezim.nadira-rr-cati.onsite.1.0.0
title: Rassistische Realitäten
DOI: 10.5281/zenodo.18262825
title: HRA Knowledge Graph v2.4

description: The Human Reference Atlas (HRA) for the healthy, adult body is being developed by a team of international, interdisciplinary experts across 20+ consortia. It provides standard terminologies and data structures for describing specimens, biological structures, and spatial positions of experimental datasets and ontology-linked reference anatomical structures (AS), cell types (CT), and biomarkers (B). We introduce the HRA Knowledge Graph (KG) as central data resource for the HRA, supporting cross-scale, biological queries to Resource Description Framework graphs using SPARQL. In April 2025, the HRA KG covers 71 organs with 5,800 AS, 2,268 CTs, 2,531 Bs; it has 10,064,033 nodes, 171,250,177 edges, and a size of 125.84 GB. The HRA KG comprises 13 types of Digital Objects (DOs) using the Common Coordinate Framework Ontology to standardize core concepts and relationships across DOs. We (1) provide data and code for HRA KG construction; (2) detail HRA KG deployment by Linked Open Data principles; and (3) illustrate HRA KG usage via application programming interfaces, user interfaces, data products. A companion website is at cns-iu.github.io/hra-kg-supporting-information.
DOI: 10.34882/dezim.nadira-rr-cati.remote.1.0.0
title: Rassistische Realitäten
DOI: 10.5281/zenodo.18019914
title: REMIND-MFA input data
DOI: 10.5281/zenodo.18019915
title: REMIND-MFA input data
DOI: 10.15468/dl.r3f8dz
title: Occurrence Download

description: A dataset containing 24114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pitangus sulphuratus",
 "Country is Bermuda",
 "HasCoordinate is true"
 ]
}

 The dataset includes 24114 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014336-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jkef8x
title: Occurrence Download

description: A dataset containing 29466 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fraxinus ornus",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 29466 records from 278 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014337-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.26855.30881
title: Современный мир,природа и человек.Технологии стран БРИКС.pdf. Статья: Основные проблемы естествознания. Автор: Аскарова Роза Исмаиловна
DOI: 10.15468/dl.a4s3qt
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trifolium ochroleucon)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014339-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rear8t
title: Occurrence Download

description: A dataset listing the 467791 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is iNaturalist Research-grade Observations"
 ]
}

 The dataset's 467791 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014321-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17343532
title: Machine perception liquid biopsy identifies brain tumors via systemic immune and tumor microenvironment signature

description: The detection and identification of intracranial tumors is limited by the lack of accurate biomarkers and requires invasive biopsy procedures. We investigated a machine perception liquid biopsy approach to detect and identify intracranial tumors from peripheral blood and to discover biomarkers responsible for the predictions. Quantum well defect-modified single-walled carbon nanotubes stabilized with single standed DNA, interrogating 739 plasma samples from brain tumor patients, were used to train and validate machine learning models to detect intracranial tumors with 98% accuracy and identify tumor type. The protein corona of the top model-contributing nanosensor was interrogated using quantitative proteomics, resulting in the identification of tumor ecosystem-secreted factors, both previously-reported and newly-discovered, originating from intracranial tumor cells, the tumor microenvironment, and the innate immune system of patients with glioblastoma and meningioma. Newly-discovered factors elicited linear nanosensor responses and were elevated in one or both tumor types, matching the original protein corona enrichment. This investigation reveals that a perception-based detection of disease in blood can identify biomarkers responsible for the signal and also amplify cancer detection signals by detecting factors beyond tumour cells, thereby recruiting the entire tumour ecosystem for cancer diagnosis.
DOI: 10.5281/zenodo.17343533
title: Machine perception liquid biopsy identifies brain tumors via systemic immune and tumor microenvironment signature

description: The detection and identification of intracranial tumors is limited by the lack of accurate biomarkers and requires invasive biopsy procedures. We investigated a machine perception liquid biopsy approach to detect and identify intracranial tumors from peripheral blood and to discover biomarkers responsible for the predictions. Quantum well defect-modified single-walled carbon nanotubes stabilized with single standed DNA, interrogating 739 plasma samples from brain tumor patients, were used to train and validate machine learning models to detect intracranial tumors with 98% accuracy and identify tumor type. The protein corona of the top model-contributing nanosensor was interrogated using quantitative proteomics, resulting in the identification of tumor ecosystem-secreted factors, both previously-reported and newly-discovered, originating from intracranial tumor cells, the tumor microenvironment, and the innate immune system of patients with glioblastoma and meningioma. Newly-discovered factors elicited linear nanosensor responses and were elevated in one or both tumor types, matching the original protein corona enrichment. This investigation reveals that a perception-based detection of disease in blood can identify biomarkers responsible for the signal and also amplify cancer detection signals by detecting factors beyond tumour cells, thereby recruiting the entire tumour ecosystem for cancer diagnosis.
DOI: 10.5281/zenodo.18269482
title: SUN'IY INTELLEKT VOSITALARIDAN TA'LIM JARAYONIDA FOYDALANISH IMKONIYATLARI

description: Bugungi kunda ta’lim sohasida raqamlashtirish jarayonlari jadallashar ekan, sun’iy intellekt (SI)texnologiyalardan foydalanish ehtiyoji yanada ortib bormoqda. SI vositalari nafaqat o’quv jarayonini yengillashtiradi,balki bilim olish samaradorligini oshiradigan yangi pedagogik yechimlarni yaratish imkonini ham beradi.Innovatsion ta’lim muhitini shaklantiradi va kelajakda raqamli jamiyat uchun malakali kadrlar tayyorlashga xizmat qiladi.
DOI: 10.5281/zenodo.18269481
title: SUN'IY INTELLEKT VOSITALARIDAN TA'LIM JARAYONIDA FOYDALANISH IMKONIYATLARI

description: Bugungi kunda ta’lim sohasida raqamlashtirish jarayonlari jadallashar ekan, sun’iy intellekt (SI)texnologiyalardan foydalanish ehtiyoji yanada ortib bormoqda. SI vositalari nafaqat o’quv jarayonini yengillashtiradi,balki bilim olish samaradorligini oshiradigan yangi pedagogik yechimlarni yaratish imkonini ham beradi.Innovatsion ta’lim muhitini shaklantiradi va kelajakda raqamli jamiyat uchun malakali kadrlar tayyorlashga xizmat qiladi.
DOI: 10.5281/zenodo.15323984
title: HRA Knowledge Graph v2.2

description: The Human Reference Atlas (HRA) for the healthy, adult body is being developed by a team of international, interdisciplinary experts across 20+ consortia. It provides standard terminologies and data structures for describing specimens, biological structures, and spatial positions of experimental datasets and ontology-linked reference anatomical structures (AS), cell types (CT), and biomarkers (B). We introduce the HRA Knowledge Graph (KG) as central data resource for the HRA, supporting cross-scale, biological queries to Resource Description Framework graphs using SPARQL. In April 2025, the HRA KG covers 71 organs with 5,800 AS, 2,268 CTs, 2,531 Bs; it has 10,064,033 nodes, 171,250,177 edges, and a size of 125.84 GB. The HRA KG comprises 13 types of Digital Objects (DOs) using the Common Coordinate Framework Ontology to standardize core concepts and relationships across DOs. We (1) provide data and code for HRA KG construction; (2) detail HRA KG deployment by Linked Open Data principles; and (3) illustrate HRA KG usage via application programming interfaces, user interfaces, data products. A companion website is at cns-iu.github.io/hra-kg-supporting-information.
DOI: 10.5281/zenodo.15323983
title: HRA Knowledge Graph v2.4

description: The Human Reference Atlas (HRA) for the healthy, adult body is being developed by a team of international, interdisciplinary experts across 20+ consortia. It provides standard terminologies and data structures for describing specimens, biological structures, and spatial positions of experimental datasets and ontology-linked reference anatomical structures (AS), cell types (CT), and biomarkers (B). We introduce the HRA Knowledge Graph (KG) as central data resource for the HRA, supporting cross-scale, biological queries to Resource Description Framework graphs using SPARQL. In April 2025, the HRA KG covers 71 organs with 5,800 AS, 2,268 CTs, 2,531 Bs; it has 10,064,033 nodes, 171,250,177 edges, and a size of 125.84 GB. The HRA KG comprises 13 types of Digital Objects (DOs) using the Common Coordinate Framework Ontology to standardize core concepts and relationships across DOs. We (1) provide data and code for HRA KG construction; (2) detail HRA KG deployment by Linked Open Data principles; and (3) illustrate HRA KG usage via application programming interfaces, user interfaces, data products. A companion website is at cns-iu.github.io/hra-kg-supporting-information.
DOI: 10.5281/zenodo.18269258
title: TABLE 3 in A stellar configuration in Gonyleptidae: Nyctaster, a new genus of Neopachylinae from the Brazilian Atlantic rainforest (Arachnida: Opiliones)

description: TABLE 3. TNT values of consistency index (CI), retention index (RI), and number of steps of the trees analyzed in this work.
k-valuesCIRIStepsEqual weights47743911, 24573401346733974, 5, 6, 10, 154674392204774391
description: Published as part of Carvalho, Rafael N. & Kury, Adriano B., 2025, A stellar configuration in Gonyleptidae: Nyctaster, a new genus of Neopachylinae from the Brazilian Atlantic rainforest (Arachnida: Opiliones), pp. 57 in Zootaxa 5729 (1) on page 57, DOI: 10.11646/zootaxa.5729.1.2, http://zenodo.org/record/17907601