cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0103442.10fu
title: SH0103442.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive111719.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0103443.10fu
title: SH0103443.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive111719.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive111720.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0103444.10fu
title: SH0103444.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive111720.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive111721.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0103445.10fu
title: SH0103445.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive111721.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive111722.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0103446.10fu
title: SH0103446.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive111722.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0103447.10fu
title: SH0103447.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive111723.20241212.9.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive111723.20251217.10
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0103448.10fu
title: SH0103448.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.7uhv6r
title: Occurrence Download

description: A dataset containing 126 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Smutsia temminckii (Smuts, 1832)"
 ]
}

 The dataset includes 126 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007815-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/z9w44pc4dp.2
title: Development and validation of digital competence assessment scale for health professions students (DigiCAS-HPS) during post- COVID-19 new normal era

description: The emergence of the COVID-19 pandemic triggered a swift transition to online learning, remote work and an increased demand for proficiency in telehealth and digital health among health professions students as they prepare for their future careers. In responding to the question: “What are the essential constructs and the validity of a digital competence assessment scale for health professions students", this study sought to develop and validate a digital competence assessment scale (DigiCAS-HPS). The present study followed a mixed-methods approach: qualitative methods (phase 1) for generating and refining items in the scale through literature review on digital frameworks, pilot testing and expert review, and quantitative methods (phase 2) including exploratory and confirmatory factor analysis for its validation. The study revealed a two-factor structure, encompassing Digital Communication, Collaboration, and Online Security (Factor 1) and Digital Content Development and Software Mastery (Factor 2), demonstrating strong construct validity and reliability. Regarding differences in digital competence across groups, older and soon-to-graduate students exhibited higher proficiency in digital content development and software mastery. The two critical facets of DigiCAS-HPS scale could tailor training programs and ensure that health professions students are well-prepared for the evolving telehealthcare landscape. This promotes the growth and accessibility of telehealth, which is increasingly vital in the post-COVID-19 new normal era.
DOI: 10.15468/dl.qtuuec
title: Occurrence Download

description: A dataset containing 351012 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cytisus scoparius (L.) Link"
 ]
}

 The dataset includes 351012 records from 1563 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0250921-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tetq9w
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Goyazia Taub."
 ]
}

 The dataset includes 144 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0243937-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nw4jgt
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Homalomena lauterbachii Engl."
 ]
}

 The dataset includes 34 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0248489-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f7f5rr
title: Occurrence Download

description: A dataset containing 1491 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Cucurbita pepo L."
 ]
}

 The dataset includes 1491 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007816-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bwd98nkhx6.1
title: Photo archive of in situ benthic imagery from the Eastern Shore Islands Area of Interest - Part 2 of 2

description: An Area of Interest (AOI) for DFO (Fisheries and Oceans Canada) is a marine area that has been identified as a potential location for a long-term Marine Protected Area (MPA) under the Oceans Act. The Eastern Shore Islands Area of Interest is found on the continental shelf south of Nova Scotia in Atlantic Canada. Four benthic imagery transects were positioned perpendicular to the shoreline of Nova Scotia and extending from ~30 to ~120 m depth across the study site, with three of the four transects further offshore from the AOI boundary. A collection of 6960 images of the seafloor were captured along these transects using a towed system’s (Campod) downward-facing camera during the HUD2018021 survey between June 30th and July 4th, 2018. Of these, 672 images were analyzed using the online image annotation software BIIGLE to record taxa presence. Here we provide the files for each of those analyzed images, organized by transect. The organisms identified from those images have been summarized in a technical report and statistically analyzed for a forthcoming publication.
DOI: 10.34740/kaggle/dsv/13321286
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.4225/15/588811d206493
title: Geoelectrical environment - Vostok - 1998 to 2004
DOI: 10.48364/isimip.240282
title: ISIMIP3a reconstructed fishing activity data

description: This data set provides fishing efforts to be used as input data for ISIMIP3a (www.isimip.org, Frieler et al. 2024). The data describes fishing effort by year, targeted functional group, and fishing gear. Fishing effort estimates were derived from country-level fishing fleet capacity data publicly available, following the method described in Rousseau et al (2019) and methods improvement reported in Rousseau et al. (2024).
DOI: 10.48610/2c8cbf6
title: Mining, responsible investment and ESG: a global spatial dataset of mining companies and properties

description: This dataset combines geospatial data on 37,434 mining properties and 9,843 mining companies with institutional ownership records and environmental, social, and governance proxies. Institutional ownership of mining companies is categorised in three investor types: PRI investors (i.e. finance organisations that are signatories of the Principles for Responsible Investment), non-PRI investors, and GICM 2030 investors (a small cohort of PRI investors that support the Global Investor Commission on Mining 2030). The dataset sheds light on the relationship between institutional ownership and Environmental, Social and Governance (ESG) topics at company and property level. The dataset covers seven ESG topics: tailings management, coal properties, corruption risk, conflict areas, threatened species, protected areas, and water scarcity. ESG topics are assessed at the property level, except for tailings management which assesses a company's commitment to the Global Industry Standard on Tailings Management (GISTM) or equivalent.
DOI: 10.5066/p91h4a18
title: Data to Assess Nitrogen Export from Forested Watersheds in and near the Long Island Sound Basin with Weighted Regressions on Time, Discharge, and Season (WRTDS)

description: The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency's Long Island Sound Study (https://longislandsoundstudy.net), characterized nitrogen export from forested watersheds and whether nitrogen loading has been increasing or decreasing to help inform Long Island Sound management strategies. The Weighted Regressions on Time, Discharge, and Season (WRTDS; Hirsch and others, 2010) method was used to estimate annual concentrations and fluxes of nitrogen species using long-term records (14 to 37 years in length) of stream total nitrogen, dissolved organic nitrogen, nitrate, and ammonium concentrations and daily discharge data from 17 watersheds located in the Long Island Sound basin or in nearby areas of Massachusetts, New Hampshire, or New York. This data release contains the input water-quality and discharge data, annual outputs (including concentrations, fluxes, yields, and confidence intervals about these estimates), statistical tests for trends between the periods of water years 1999-2000 and 2016-2018, and model diagnostic statistics. These datasets are organized into one zip file (WRTDSeLists.zip) and six comma-separated values (csv) data files (StationInformation.csv, AnnualResults.csv, TrendResults.csv, ModelStatistics.csv, InputWaterQuality.csv, and InputStreamflow.csv). The csv file (StationInformation.csv) contains information about the stations and input datasets. Finally, a short R script (SampleScript.R) is included to facilitate viewing the input and output data and to re-run the model.

Reference:
Hirsch, R.M., Moyer, D.L., and Archfield, S.A., 2010, Weighted Regressions on Time, Discharge, and Season (WRTDS), with an application to Chesapeake Bay River inputs: Journal of the American Water Resources Association, v. 46, no. 5, p. 857–880.
DOI: 10.5066/p929kmvk
title: Five-minute discharge; daily precipitation, stream runoff, and maximum and minimum air temperature; and annual precipitation and runoff for W-9 catchment, Sleepers River Research Watershed near Danville, Vermont, 1991-2018

description: This data release supports publications on the Sleepers River Research Watershed near Danville, Vermont. Most of the research at Sleepers River takes place at W-9, the 40.5-hectare forested headwater site. Topics include understanding hydrologic flow paths, biogeochemical cycling, and organic carbon dynamics. Flow and precipitation data are integral to understanding these processes, for example by combining flow and chemical concentrations to compute solute export from the catchment. These records begin in late September 1991 and extend through calendar year 2018. The release includes five-minute data for discharge, daily data for precipitation, runoff,and maximum and minimum air temperature, and an annual tabulation of precipitation and runoff.
DOI: 10.5066/p96cphot
title: GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow

description: These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. This dataset, termed "GAGES II", an acronym for Geospatial Attributes of Gages for Evaluating Streamflow, version II, provides geospatial data and classifications for 9,322 stream gages maintained by the U.S. Geological Survey (USGS). It is an update to the original GAGES, which was published as a Data Paper on the journal Ecology's website (Falcone and others, 2010b) in 2010. The GAGES II dataset consists of gages which have had either 20+ complete [...]
DOI: 10.5067/aqua/modis/l2/oc/2022
title: Aqua MODIS Level 2 Ocean Color Data, Version R2022.0
DOI: 10.5067/aura/mls/data2511
title: MLS/Aura Level 2 Nitric Acid (HNO3) Mixing Ratio V005
DOI: 10.5067/f6jmovy5navz
title: Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 7
DOI: 10.5067/txbmlx370xx8
title: GLDAS Catchment Land Surface Model L4 daily 0.25 x 0.25 degree GRACE-DA1, Version 2.2
DOI: 10.5067/ubko5zui7i5v
title: SMAP L4 Global Daily 9 km Carbon Net Ecosystem Exchange, Version 2
DOI: 10.5281/zenodo.10495462
title: XBeach morphological modelling Maldives

description: The XBeach dataset for modelling the morphological response of a coral island (Fiyoaree, Maldives) to sea level rise and hazard mitigation strategies.

The XBeach results support the findings and conclusions of the paper:

Climate adaptation for a natural atoll island in the Maldives- predicting the long-term morphological response of coral islands to sea level rise and the effect of hazard mitigation strategies

F. E. Roelvink, G. Masselink, C. Stokes, and R. T. McCall