cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1055612.10fu
title: SH1055612.10FU

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: 10.15156/bio/sh1055613.10fu
title: SH1055613.10FU

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: 10.15156/bio/sh1055615.10fu
title: SH1055615.10FU

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: 10.15156/bio/sh1055616.10fu
title: SH1055616.10FU

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: 10.15156/bio/sh1055617.10fu
title: SH1055617.10FU

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: 10.15156/bio/sh1055620.10fu
title: SH1055620.10FU

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: 10.15156/bio/sh1055622.10fu
title: SH1055622.10FU

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: 10.15156/bio/sh1055628.10fu
title: SH1055628.10FU

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.vqk7g4
title: Occurrence Download

description: A dataset containing 10527 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-10000.0",
 "Country is Madagascar",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Anura, Squamata)"
 ]
}

 The dataset includes 10527 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010583-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/zhrtks
title: Colaboraciones Americanas Sobre Aves
DOI: 10.1594/pangaea.871920
title: COSTA v1.0: DGFI-TUM Along Track Sea Level Product for ERS-2 and Envisat (1996-2010) in the Mediterranean Sea and in the North Sea, links to data sets in NetCDF format

description: The COastal Sea level Tailored ALES (COSTA) dataset contains dedicated coastal altimetry sea level measurements based on the Adaptive Leading Edge Subwaveform (ALES) reprocessing. In this version, the missions involved are ERS-2 (1996-2002) and Envisat (2002-2010), and the data are available in the Mediterranean Sea and in the North Sea.The dataset is generated by the application of the ALES fitting algorithm to the radar signal provided by the official products of the missions. The ALES algorithm selects only a portion of the altimetric signal (waveform), in order to estimate the distance between the satellite and the sea surface (range) while avoiding the noise in the tail of the signal. The algorithm is based on the relation between estimated sea state, achievable precision and width of the subwaveform. The sea state bias correction, which accounts for the effects of waves and the tracking errors, is recomputed for the ALES output.Following this pre-processing, the data are post-processed with updated geophysical corrections, tidal and mean sea surface models. Finally, the sea level measurements are averaged at 1 Hz (one measurement every ~7 km along each track) after removing the outliers. To facilitate the temporal analysis, the sea level anomalies for each track are stored in matrices in which each row corresponds to the time series at one latitude-longitude location. The validation work, presented at the 10th Coastal Altimetry Workshop (2017-02-21 - 2017-02-24, Florence, Italy), has shown a 15% decrease in the high-rate noise of the measurements if compared to the standard product, with larger improvements in the last 20 km from the coastline and a better precision also in the open ocean. The COSTA dataset is made available to the scientific community in order to foster the application of coastal altimetry data by users, who are not necessarily trained in radar altimetry processing. Its objective is the provision of easy-to-use along-track sea level data that can be directly used for sea level and circulation studies not only in the open ocean, but also in the coastal regions.
DOI: 10.17632/zx8pfhdtnb.2
title: Mechanical faults in rotating machinery dataset (normal, unbalance, misalignment, looseness)

description: The dataset was developed aiming to address classic faults in rotating machines such as: unbalance, misalignment and mechanical looseness, in addition to the normal operating condition. The faults were introduced on a test bench, being: motor, frequency inverter, bearing house, two bearings, two pulleys, belt and rotor (disc).

20 tests were performed, 5 for each condition (normal, unbalance, misaligment and looseness). Each test consists of 4 sets of 420 signals collected continuously, each file consisting of 25,000 points with the sampling rate set at 25 kHz (420 signals per accelerometer). Resulting in the end of all tests, in a total of 8400 signals per accelerometer. The sequence of tests was randomly defined. Before starting any test, the bench was dismantled and returned to normal operating condition, to later introduce the fault. The experimental procedure allows variations to occur, making the tests closer to industrial reality. 

Each file has (4, 25000), where 4 represents the position of the accelerometers, and 25000 the number of points. The accelerometers were positioned in such a way that:
1 - Vertical side of the coupling (pulley)
2 - Horizontal side of the coupling (pulley)
3 - Vertical side opposite the coupling (disk)
4 - Horizontal side opposite the coupling (disk)

The sequence of tests and operating conditions are:
- Test 01: Normal Condition 
- Test 02: Misalignment 
- Test 03: Normal Condition 
- Test 04: Unbalance
- Test 05: Mechanical Looseness
- Test 06: Normal Condition 
- Test 07: Unbalance
- Test 08: Mechanical Looseness
- Test 09: Normal Condition 
- Test 10: Misalignment
- Test 11: Misalignment
- Test 12: Mechanical Looseness
- Test 13: Misalignment
- Test 14: Mechanical Looseness
- Test 15: Unbalance
- Test 16: Misalignment
- Test 17: Normal Condition 
- Test 18: Unbalance
- Test 19: Mechanical Looseness
- Test 20: Unbalance
DOI: 10.17909/d7vy-5145
title: Data from paper
DOI: 10.17909/yhfg-m926
title: Data from Lammers & Winn 2024

description: JWST GO program 2571
DOI: 10.18112/openneuro.ds002785.v2.0.0
title: AOMIC-PIOP1
DOI: 10.18112/openneuro.ds002790.v2.0.0
title: AOMIC-PIOP2
DOI: 10.18112/openneuro.ds003097.v1.2.1
title: AOMIC-ID1000
DOI: 10.18140/flx/1669370
title: FLUXNET-CH4 BW-Gum Guma

description: This is the FLUXNET-CH4 version of the carbon flux data for the site BW-Gum Guma.
DOI: 10.18140/flx/1669518
title: FLUXNET-CH4 BW-Nxr Nxaraga

description: This is the FLUXNET-CH4 version of the carbon flux data for the site BW-Nxr Nxaraga.
DOI: 10.18140/flx/1669639
title: FLUXNET-CH4 FI-Si2 Siikaneva-2 Bog

description: This is the FLUXNET-CH4 version of the carbon flux data for the site FI-Si2 Siikaneva-2 Bog.
DOI: 10.18140/flx/1669650
title: FLUXNET-CH4 MY-MLM Maludam National Park

description: This is the FLUXNET-CH4 version of the carbon flux data for the site MY-MLM Maludam National Park.
DOI: 10.18140/flx/1669652
title: FLUXNET-CH4 NZ-Kop Kopuatai

description: This is the FLUXNET-CH4 version of the carbon flux data for the site NZ-Kop Kopuatai.
DOI: 10.18140/flx/1669654
title: FLUXNET-CH4 RU-Ch2 Chersky reference

description: This is the FLUXNET-CH4 version of the carbon flux data for the site RU-Ch2 Chersky reference.
DOI: 10.18140/flx/1669656
title: FLUXNET-CH4 RU-Cok Chokurdakh

description: This is the FLUXNET-CH4 version of the carbon flux data for the site RU-Cok Chokurdakh.
DOI: 10.18140/flx/1669668
title: FLUXNET-CH4 US-BZB Bonanza Creek Thermokarst Bog

description: This is the FLUXNET-CH4 version of the carbon flux data for the site US-BZB Bonanza Creek Thermokarst Bog.
DOI: 10.18140/flx/1669669
title: FLUXNET-CH4 US-BZF Bonanza Creek Rich Fen

description: This is the FLUXNET-CH4 version of the carbon flux data for the site US-BZF Bonanza Creek Rich Fen.
DOI: 10.18140/flx/1669678
title: FLUXNET-CH4 US-ICs Imnavait Creek Watershed Wet Sedge Tundra

description: This is the FLUXNET-CH4 version of the carbon flux data for the site US-ICs Imnavait Creek Watershed Wet Sedge Tundra.
DOI: 10.18140/flx/1669699
title: FLUXNET-CH4 US-Tw5 East Pond Wetland

description: This is the FLUXNET-CH4 version of the carbon flux data for the site US-Tw5 East Pond Wetland.
DOI: 10.34740/kaggle/dsv/6107556
title: Blood Cell Segmentation Dataset
DOI: 10.3886/e200922v1
title: Code for: A Technology-Gap Model of 'Premature' Deindustrialization

description: Replication flies for "A Technology Gap Model of 'Premature' Deindustrialization."
DOI: 10.3886/e210402v1
title: Replication data - Alfani, Gierok and Schaff "Poverty in Germany from the Black Death until the Beginning of Industrialization"

description: The deposited data allows replication of the figures in "Poverty in Germany from the Black Death until the Beginning of Industrialization" (Explorations in Economic History. The paper provides macro-level estimates of the prevalence of poverty in preindustrial Germany, from the Black Death to the onset of industrialization in the nineteenth century. Based on a new body of evidence we show that poverty declined after two large-scale catastrophes: the Black Death in the fourteenth century and the Thirty Years’ War in the seventeenth. Poverty increased massively in the sixteenth century, and stagnated in the eighteenth and early nineteenth centuries. This pattern is broadly in line with a Malthusian model of the preindustrial economy, but also with several other explanations. Circa 1600, poverty and inequality extraction were at a historical peak – right when social conflict erupted in Germany.
DOI: 10.48443/c50b-qx77
title: Plant presence and percent cover (DP1.10058.001)
title: RELEASE-2024

description: This data product contains the quality-controlled, native sampling resolution data from NEON's plant diversity sampling. The presence and percent cover of species is documented in square, multi-scale plots. The presence and percent cover of plant species and ground cover is observed in six 1m2 subplots per plot. The presence of species is observed in six 10m2 subplots and four 100m2 subplots per plot, which can be combined for a list of species at the 400m2 plot scale. For additional details, see the data product user guide, protocol, and science design listed in the Documentation section in this data product's details webpage.

Latency: The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guide for more information.

div_10m2Data100m2Data: 135

div_1m2Data: 135

div_geneticarchive: 120

div_voucher: 215

div_identificationHistory: 7
description: Up to thirty Distributed Plots and three Tower Plots are measured at each site. Plots are sampled annually at most sites to correspond with peak greenness, and twice a year at select sites with bimodal peaks in greenness and species composition. The multi-scale plot design is consistent with methods of the Carolina Vegetation Project. The files provided with this data product also include records of plant vouchers and foliar tissue for analyses by the ecological community that are stored at external archives, and a table to facilitate the resolution of species not identified when encountered in the field during observation and data entry. Instrumentation:
DOI: 10.5066/p1kqjgvn
title: UAS products and field data for biocrust soil heterogeneity research, Beef Basin, Utah

description: This data release contains mapped UAS products and a spreadsheet of field plot observations for the paper: Havrilla, C.A. and M.L. Villarreal. 2024. Soil cover heterogeneity associated with biocrusts predicts patch-level plant diversity patterns. Landscape Ecology. Specifically the zipped folder contains a CSV of field data, classified Unoccupied Aerial Systems (UAS) imagery for 3 study plots and Soil Cover Heterogeneity maps generated from each of the classified maps.
DOI: 10.5066/p91ydwys
title: North American Bird Banding Program Dataset 1960-2021 retrieved 2021-07-25

description: The North American Bird Banding Program is directed in the United States by the U.S. Geological Survey (USGS) Bird Banding Laboratory (BBL), Eastern Ecological Science Center at the Patuxent Research Refuge (EESC) and in Canada by the Bird Banding Office (BBO), Environment and Climate Change Canada (ECCC). The respective banding offices have similar functions and policies and use the same bands, reporting forms and data formats. Data contributors are US and Canadian bird banding permit holders: federal, state, tribal, local government, non-government agencies, business, university and avocational biologists. Bird banders capture wild birds and mark them with a metal leg band with a unique 9-digit number. Extra markers may be added. Attributes of a bird such as age, sex, condition, molt and morphometrics may be taken before the bird is released. This long-term dataset is made up of over 76 million bird banding records with over 1,000 species, and 5 million encounter records with nearly 800 species. Federal bands are used on species included in the Migratory Bird Treaty Act (MBTA). Banding, encounter and recapture records are available for years 1960 to present. The data is curated at BBL on a daily basis, therefore each yearly version may differ from previous releases. The BBL produces one data release annually, beginning in 2020. Each yearly release is available for request. Data quality is established by contributors submitting their data. Incoming data must pass automatic validation rules to meet quality standards, and in some cases additional validation is conducted by staff at BBL and BBO. It is imperative to understand the codes used by the BBL and BBO. In early days of storage space restrictions for electronic data, an efficient system of codes was developed. Some examples include: bird status code, coordinate precision, inexact date, minimum age at encounter. BBL terminology is important as well: an encounter refers to a sighting or direct encounter with a banded or auxiliary-marked bird by any person; recapture denotes a banded bird recaptured during banding operations; recovery refers a harvested gamebird. Please cite as: Celis-Murillo A, M Malorodova, E Nakash. 2021. North American Bird Banding Dataset 1960-2021 retrieved 2021-07-25. U.S. Geological Survey, Eastern Ecological Science Center at the Patuxent Research Refuge.
DOI: 10.5066/p950h8hs
title: The Sagebrush Biome Range Extent, as Derived from Classified Landsat Imagery

description: This feature estimates the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency's (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures. This layer does not represent the realized distribution of sagebrush and should not be used to summarize statistics about the distribution or precise location of sagebrush across the landscape. This layer is intended to generalize the sagebrush biome distribution using Landsat derived classified vegetation rasters (Rigge at al. 2019), Bureau of Land Management-designated Habitat Management Areas, state-designated Priority Areas for Conservation for sage-grouse, the current range of the Greater Sage-grouse (Centrocercus urophasianus), Gunnison Sage-grouse (Centrocercus minimus) and Pygmy Rabbit (Brachylagus idahoensis). Rigge, M., Homer, C., Cleeves, L., Meyer, D., Bunde, B., Shi, H., Xian, G., and Bobo, M. 2019. Quantifying western U.S. Rangelands as Fractional Components with Landsat. Remote Sensing of Environment, in Review.
DOI: 10.5067/9sc1vntwgwv3
title: MERRA-2 statD_2d_slv_Nx: 2d,Daily,Aggregated Statistics,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4
DOI: 10.5067/modis/myd08_d3.006
title: MYD08_D3 MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG