cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gejk82
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-43.85305 -22.88371,-44.00774 -23.09159,-43.54997 -23.06395,-43.82085 -22.87776,-43.85305 -22.88371))",
 "TaxonKey is Anhinga anhinga"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019786-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hgk2g2
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salacia chinensis",
 "Country is Bangladesh",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019787-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d4qqrd
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melanotaenia oktediensis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019789-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7a4nuj
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Globivenus orientalis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019788-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jhhffg
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia auriculiformis",
 "Country is Bangladesh",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019790-250914085247600/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.30167950
title: wisconsinlakesupdateclean.csv

description: Data associated with "Declining Ice Duration and Changing Ice Quality Drive Key Under-Ice Ecological Changes in Wisconsin Lakes" submitted to JGR Biogeosciences.
DOI: 10.6084/m9.figshare.30167950.v1
title: wisconsinlakesupdate_clean.csv

description: Data associated with "Declining Ice Duration and Changing Ice Quality Drive Key Under-Ice Ecological Changes in Wisconsin Lakes" submitted to JGR Biogeosciences.
DOI: 10.6084/m9.figshare.30167950.v2
title: wisconsinlakesupdateclean.csv

description: Data associated with "Declining Ice Duration and Changing Ice Quality Drive Key Under-Ice Ecological Changes in Wisconsin Lakes" submitted to JGR Biogeosciences.
DOI: 10.15468/dl.krf5xz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia auriculiformis",
 "Country is Burundi",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019792-250914085247600/datasets/export for details.
DOI: 10.15468/dl.yjbpym
title: Occurrence Download

description: A dataset containing 6158 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia auriculiformis",
 "Country is Benin",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6158 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019791-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uapvbu
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Globivenus rigida",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 27 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019793-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p13koghk
title: Pitcher's thistle (Cirsium pitcheri) experimental reintroduction stage and spatial pattern at Indiana Dunes National Park, Indiana, USA, 1994-2023

description: This data release contains three datasets for the Pitcher's thistle (Cirsium pitcheri) reintroduction experiment, started in 1994, at the Portage Lakefront unit (formerly called Ogden Dunes), Indiana Dunes National Park, Porter County, Indiana. This plant species is a Federally threatened monocarpic perennial plant endemic to the sand dunes of the western Great Lakes. There are three csv files included in this data release. One file contains count data for plants from 1994 to 2000 from early-, mid-, and late-successional habitats. The other two files, with identical structure, contain demography data for two populations (Mid- and late-successional habitats) from 2001 through 2023. These data sets provide the spatial distribution of plants in the population and the life stages encountered from 2001, when we began tracking individual tagged plants, through 2023.
DOI: 10.25574/27025
title: Chandra X-ray Observatory ObsId 27025

description: AO-24 Calibration Observations of A1795
DOI: 10.15468/dl.tv87k3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Microsynodontis polli)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "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/0019794-250914085247600/datasets/export for details.
DOI: 10.6084/m9.figshare.28334405.v2
title: Lambin, X., M. Begon, S. Burthe, I. M. Graham, J. L. McKinnon, S. Telfer, and M. K. Oli. 2025. Data from "Density-dependent recruitment but not survival drives the cyclic dynamics of a field vole population". Figshare. Available at https://figshare.com/s/c115e0f08161e6e9bc30. Deposited 18 April 2025.

description: <b>Description of files:</b><b>Lambin_et_al_CMR_code_20250203.R:</b>R script that loads necessary R packages, reads the data, performs 3 sets of Pradel capture-mark-recapture CMR) analysis in Program MARK via RMark interface.The first set of models is designed to test for the additive and interactive effects of phase and season on the model parameters, and determines and best model structures for the capture probability (p).The second set of models is designed to test for the influence of single density (with and without time lag) covariates, singularly as well as additively and interactively with phase and season phase and season on the model parameters, and determines and best model structures for the capture probability (p).The final set of models is designed to test for the influence of single density (with and without time lag) covariates, singularly as well as additively and interactively with phase and season phase and season on the model parameters, and determines and best model structures for the capture probability (p).<br><b>Vole_processed_and_design_data2.RData:</b>This image file contains two R objects for constructing and analyzing CMR models in program MARK using RMark interface:<b>pradel.process2</b>: This is a processed data list resulting from process.data () function in RMark. It contains a list of contains capture history and other data and information needed to perform CMR analyses.data processed data list resulting from process.data<b>pradel.ddl2:</b> This is the design dataframe, initially created with make.design.data() function in RMark. It contains a list of design matrices for fitting linear models to each model parameters as functions of phase, season and various density covariates, with and without time lags.
DOI: 10.6084/m9.figshare.28334405.v1
title: Lambin, X., M. Begon, S. Burthe, I. M. Graham, J. L. McKinnon, S. Telfer, and M. K. Oli. 2025. Data from "Density-dependent recruitment but not survival drives the cyclic dynamics of a field vole population". Figshare. Available at https://figshare.com/s/c115e0f08161e6e9bc30. Deposited 19 September 2025.

description: <b>Description of files:</b><b>Lambin_et_al_CMR_code_20250203.R:</b>R script that loads necessary R packages, reads the data, performs 3 sets of Pradel capture-mark-recapture CMR) analysis in Program MARK via RMark interface.The first set of models is designed to test for the additive and interactive effects of phase and season on the model parameters, and determines and best model structures for the capture probability (p).The second set of models is designed to test for the influence of single density (with and without time lag) covariates, singularly as well as additively and interactively with phase and season phase and season on the model parameters, and determines and best model structures for the capture probability (p).The final set of models is designed to test for the influence of single density (with and without time lag) covariates, singularly as well as additively and interactively with phase and season phase and season on the model parameters, and determines and best model structures for the capture probability (p).<br><b>Vole_processed_and_design_data2.RData:</b>This image file contains two R objects for constructing and analyzing CMR models in program MARK using RMark interface:<b>pradel.process2</b>: This is a processed data list resulting from process.data () function in RMark. It contains a list of contains capture history and other data and information needed to perform CMR analyses.data processed data list resulting from process.data<b>pradel.ddl2:</b> This is the design dataframe, initially created with make.design.data() function in RMark. It contains a list of design matrices for fitting linear models to each model parameters as functions of phase, season and various density covariates, with and without time lags.
DOI: 10.25976/stvm-sn87
title: Fraser River Long-term Water Quality Monitoring Data

description: Long-term freshwater quality monitoring data for over 14 sites in the Fraser River Basin for the past 15 years or longer for nutrients, metals, major ions, and other physical-chemical variables are included in this dataset. Monitoring is conducted by Environment and Climate Change Canada (ECCC) and under the Canada-British Columbia Water Quality Monitoring Agreement to assess water quality status and long-term trends, detect emerging issues, establish water quality guidelines and track the effectiveness of remedial measures and regulatory decisions.
description: Fraser River Long-term Water Quality Monitoring Data employs standardized approaches and tools to assess and report on water quality. This dataset is part of the larger Canada Water Quality Monitoring and Surveillance (WQM&S) which monitors: nutrients, major ions, trace metals.
DOI: 10.25934/pr00011206
title: Evaluating the Impact of Cobimetinib on the Quality of Life in Melanoma Patients Using Patient Data

description: Melanoma is a type of skin cancer that can spread quickly to other parts of the body if not treated early. Each year, thousands of people worldwide are affected by melanoma, making it a significant health concern. Cobimetinib is a medicine used to treat melanoma by blocking certain signals that help cancer cells grow and spread. By interrupting these signals, cobimetinib helps slow or stop the growth of cancer.

Our lab developed special computer tools called "population modeling tools," which analyze information that patients report about their own health, known as patient-reported outcomes (PROs). These outcomes help researchers understand how patients feel during and after treatment, including their quality of life. In many cancer studies, it's difficult to clearly see how well a medicine is working because each patient can respond very differently. This is called variability or heterogeneity. Often, clinical trials compare patients who get the new medicine (the drug group) with patients who get no medicine (the placebo group) to see if the drug makes a real difference. Sometimes, because of patient differences, trials struggle to show clearly if a drug is helping based on these patient-reported outcomes. Our tools help to manage this variability better, making it easier to detect if a treatment truly helps patients feel better. We previously tested our methods using de-identified individual patient information and special analysis methods (pharmacometrics modeling), successfully demonstrating how a medicine can impact patient-reported outcomes.

For this project, we want to use anonymized data (data that does not contain information identifying any patient) from a previous melanoma trial (coBRIM) available through Vivli. Using this data, our methods will examine how effectively cobimetinib improves patient-reported outcomes, such as quality of life. Our research is important because it will help doctors and patients better understand the real-life benefits of cobimetinib, guiding decisions about treatment based on what truly matters to patients. This will contribute valuable insights into improving patient care and defining meaningful goals in future melanoma treatments.
DOI: 10.5066/p13yxhpb
title: Soil data release of Open-File Report 02-277, collected on marine terraces near Santa Cruz, California in 1981

description: This data release represents samples collected in 1981 along a series of five marine terraces between Ano Nuevo and Santa Cruz in California as a part of a U.S. Geological Survey project led by Dennis Marchand to study soil chronosequences in the Western United States. These sequential surfaces of soils have similar key elements for development in the slope, climate, vegetation, and parent material, but differ in geologic age. These five variables are known as the soil-forming factors. When the lone soil forming variable between surfaces is time, this forms what is known as a soil chronosequence. These samples are homogeneous in soil order, with all five profiles being classified as Mollisols. The surfaces for these soils have age estimates that range from 65 to 226 kiloyears old and are composed of Tertiary Santa Cruz mudstone and Santa Margarita sandstone. The dataset includes profile-level information, such as sample location and elevation, as well as physical properties of the layers (e.g., texture and particle size analysis). Additionally, pH, extractive chemistry, mineralogy, and analytical chemistry for major elements that was obtained through x-ray fluorescence are included in this dataset. There are also four digitized photos that were taken at various locations within the site area during sample collection. The purpose of this data release is to improve to digital availability of the previously published data from the Open-File Report 02-277 for future studies. The physical samples associated with this dataset are available through the U.S. Geological Survey Soil Sample Archive (https://doi.org/10.5066/P90KTZW4).
DOI: 10.15468/dl.dfan6e
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia auriculiformis",
 "Country is Cameroon",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019797-250914085247600/datasets/export for details.
DOI: 10.15468/dl.7a44ek
title: Occurrence Download

description: A dataset containing 211 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-43.85281 -22.88507,-44.00701 -23.09253,-43.54961 -23.06423,-43.8204 -22.87576,-43.85281 -22.88507))",
 "TaxonKey is Platalea ajaja"
 ]
}

 The dataset includes 211 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019796-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bzz9u7
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia auriculiformis",
 "Country is Cambodia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019795-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z57hut
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia auriculiformis",
 "Country is Côte d’Ivoire",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019798-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.68r7rk
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hysteroconcha dione",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 91 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019799-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ujf7k
title: Occurrence Download

description: A dataset containing 413509 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Iberis amara, Lepidium chalepensis, Lepidium heterophyllum, Lepidium perfoliatum, Lepidium ruderale, Lobularia maritima, Microthlaspi perfoliatum, Sinapis alba, Thlaspi alliaceum, Thlaspi arvense, Reseda alba, Conicosia pugioniformis, Malephora crocea, Tetragonia tetragonioides, Kochia scoparia, Dianthus armeria, Dianthus deltoides, Dianthus plumarius, Gypsophila scorzonerifolia, Lepyrodiclis holosteoides)",
 "BasisOfRecord is one of (Machine Observation, Human Observation, Observation)",
 "HasCoordinate is true",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 413509 records from 1816 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019770-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p6mv3p
title: Occurrence Download

description: A dataset containing 38215 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 acceptedtaxonkey,
 acceptedscientificname,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.taxonkey = 9 OR occurrence.acceptedtaxonkey = 9 OR occurrence.kingdomkey = 9 OR occurrence.phylumkey = 9 OR occurrence.classkey = 9 OR occurrence.orderkey = 9 OR occurrence.familykey = 9 OR occurrence.genuskey = 9 OR occurrence.specieskey = 9)
 AND (occurrence."year" &gt;= 2000 AND occurrence."year" &lt;= 2025)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.acceptedtaxonkey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence.acceptedtaxonkey,
 occurrence.acceptedscientificname,
 occurrence."year"

 The dataset's 38215 records were derived from 1419 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059366-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4nc5zp
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gyrosigma A.H.Hassall, 1845",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((30.0251 -31.3959,30.5701 -30.7329,30.5701 -28.5786,25.5395 -28.5786,25.5395 -32.9007,28.2048 -32.9007,28.5753 -32.6569,29.4902 -31.7517,30.0251 -31.3959))"
 ]
}

 The dataset includes 22 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059384-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.