cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-22ce-n609
title: Extreme Precipitation Event Catalogue (EPEC)

description: The EPEC is a catalogue of labelled extreme precipitation events resolved at 0.03332 degrees (~4km) hourly across the Contiguous United States (CONUS) from January 2002 through May 2025. This event-based approach offers novel insights into the space and time evolving structure of extreme precipitation, enabling understanding of extreme precipitation event characteristics and trends at local scales. EPEC includes 31,140 storms labelled as microscale (n = 2,340), mesoscale (n = 28,034), synoptic (n = 554), and Tropical Cyclone (n = 248). The intended audience includes flood hazard research scientists interested in modeling hydrologic and hydraulic response from extreme precipitation events, civil engineers, city managers, and watershed planners interested in understanding recent trends in extreme precipitation events at scales relevant to planning design, and private industry including banking, insurance, and reinsurance organizations interested in reducing portfolio-scale risks.

EPEC is created by combining NOAA Analysis of Record for Calibration (AORC), NOAA Atlas 14 Annual Recurrence Intervals (ARIs), unsupervised clustering using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and supervised classification using Random Forest (RF). Each event within the EPEC includes both a PNG file and a GeoTIFF file. Each included PNG file plots the spatial extent of the event and is colored by the maximum exceeded return period at that location. The start and end date times are also included in the subtitle of each PNG image. Each included GeoTIFF file is named using the convention 'YYYY-MM-DD-XXX.tif' where YYYY-MM-DD is the year-month-day associated with the first day of the precipitation event and XXX is the storm ID number within that day. GeoTIFF layers are named using the convention 'tYYYYMMDD_HHMMSS' which represents the date time for each time step. Raster values represent hourly precipitation derived from NOAA AORC and are in units of millimeters per hour (mm/hr). A csv file is included (cluster_characteristics_label_all_predict.csv) which describes individual event characteristics and the probability of each event's classification as one of four storm types (microscale, mesoscale, synoptic, and tropical cyclone). Storm types were determined using a Random Forest classification model trained (80%) and tested (20%) using a 10-fold cross-validation on a 10% sample of hand-labelled events from the catalogue. Hand-labeled events are defined under the 'label' column and all event predictions are defined under the 'predicted_class' column where 'MICRO' ~ microscale, 'MCS' ~ mesoscale, 'SYN' ~ synoptic, and 'TC' ~ tropical cyclone.
DOI: 10.15468/dl.zhbecs
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hymenocallis astrostephana"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003037-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17863/cam.119282
title: Research data supporting ‘Facile synthesis of zeolitic imidazolate framework coated glass microspheres’

description: Data set contains information for Manuscript and Supplementary data for all figures except SEM images and schematics. Separate folders are available for each figure. Originpro graphing software was used to plot all graphs. • Raw (.raw) files generated from PXRD diffractometer directly, these were then converted to .xy files using PowDLL and can be directly opened in excel. xy files contain the PXRD patterns of the samples. OriginPro used to plot the figure. These were used in the Pawley refinement Topas input file (.inp) generated using jEdit Programmer’s text editor. • .UA files (SDT files) generated directly from Discovery SDT 650; raw data were opened using TA Instruments Thermal Analysis software (Advantage/Universal Analysis (UA) Software) and exported as an excel spreadsheet. • DSC: .ngb-ddg files generated directly from NETSCH DSC 214 Polyma calorimeter, these files were opened in Netzsch Proteus® software package and exported as .csv files. • FTIR .txt files were exported directly from the FTIR spectrometer. These can be opened in notepad or excel or equivalent programmes. The .SPA files are the raw data taken directly from the spectrometer and exported using Thermo Fisher Scientific’s Omnic Series Software. • UV/VIS: .dsw and .bsw files were generated directly on Agilent UV-VIS spectrophotometer; data were exported as .xlsx or .csv files using Agilent’s Cary WinUV Software platform. • Mass loss data (Figure S30) generated by physically weighing samples and recording mass in Microsoft Excel spreadsheet. • pH values (Figure S32) were generated by physically recording pH values obtained and inputted in Microsoft Excel spreadsheet. • Microsphere sizes (Figure S5) were recorded using the associated SEM images directly in software on the FEI Nova Nano SEM 450 electroscope used to take the images and were inputted in Microsoft Excel spreadsheet.
DOI: 10.21227/8mk9-w740
title: "Data for Backorder Time Prediction in a DDMRP Managed Production System - IEEEDataPort"

description: "In the interest of transparency and reproducibility, the full dataset used for backorder time prediction in a DDMRP production model, along with the associated machine learning model code, has been made publicly available. The resulting dataset, generated from the simulation of all scenarios, comprises 10,620 rows and 15 columns. The target variable is the backorder time of a delayed customer order in a DDMRP-managed system, measured from the moment the order is received until it is fulfilled. The input features were selected based on insights from the literature and include key factors known to influence backorder times in DDMRP systems."
DOI: 10.15468/dl.yh3wep
title: Occurrence Download

description: A dataset containing 1006 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-73.044 4.744157, -73.114502 4.738586, -73.183266 4.722013, -73.248594 4.694846, -73.308875 4.657755, -73.36262499999999 4.611655, -73.40852 4.557683, -73.445429 4.497168, -73.47244600000001 4.431603, -73.488908 4.362603, -73.494412 4.291867, -73.488826 4.221138, -73.472291 4.152156, -73.445215 4.08662, -73.40826800000001 4.026141, -73.36236 3.972209, -73.308623 3.926149, -73.248379 3.889095, -73.18311 3.861956, -73.11442099999999 3.845402, -73.044 3.839838, -72.973579 3.845402, -72.90488999999999 3.861956, -72.83962099999999 3.889095, -72.779377 3.926149, -72.72564 3.972209, -72.679732 4.026141, -72.642785 4.08662, -72.615709 4.152156, -72.599174 4.221138, -72.593588 4.291867, -72.599092 4.362603, -72.615554 4.431603, -72.642571 4.497168, -72.67948 4.557683, -72.725375 4.611655, -72.77912499999999 4.657755, -72.839406 4.694846, -72.904734 4.722013, -72.97349800000001 4.738586, -73.044 4.744157))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1006 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003039-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.grfv28
title: Occurrence Download

description: A dataset containing 105 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Senega appressa"
 ]
}

 The dataset includes 105 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003038-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gamcxh
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Schima brevifolia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is Asia"
 ]
}

 The dataset includes 70 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003040-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fr33nt
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Adela septentrionella",
 "Year 2000-2026"
 ]
}

 The dataset includes 45 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003041-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z9tp75
title: Occurrence Download

description: A dataset containing 773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Polygala appressa"
 ]
}

 The dataset includes 773 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003042-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ey5kz4
title: Occurrence Download

description: A dataset containing 228 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vipera nikolskii"
 ]
}

 The dataset includes 228 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003043-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aa5c6t
title: Occurrence Download

description: A dataset containing 312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heteropneustes fossilis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 312 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003045-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.72mxut
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Capreolus capreolus (Linnaeus, 1758))",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 82 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015683-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.908971
title: Current measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during October, 2014
DOI: 10.1594/pangaea.908927
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during March, 2012
DOI: 10.1594/pangaea.908950
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during January, 2013
DOI: 10.1594/pangaea.908962
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during May, 2014
DOI: 10.1594/pangaea.908916
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during October, 2011
DOI: 10.1594/pangaea.908931
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during May, 2012
DOI: 10.1594/pangaea.902655
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during December, 2015
DOI: 10.1594/pangaea.902657
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during December, 2015
DOI: 10.1594/pangaea.884592
title: (Figure 3) Ten day mean buoyancy frequency and turbulence dissipation rate of the mooring
DOI: 10.1594/pangaea.908913
title: Current measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during September, 2011
DOI: 10.1594/pangaea.923037
title: Land cover fraction map of Austria at 10m spatial resolution based on Sentinel-1 and Sentinel-2 spectral temporal metrics

description: The increasing impact of humans on land and ongoing global population growth requires an improved understanding of land cover (LC) processes in general and of those related to settlements in particular. The heterogeneity of settlements and landscapes as well as the importance of not only mapping, but also characterizing anthropogenic and landscape structures suggests using a sub-pixel mapping approach for analysing related LC from space.This map has been created using a regression-based unmixing approach for mapping built-up surfaces and infrastructure, woody vegetation and non-woody vegetation for all of Austria at 10 m spatial resolution. Spectral-temporal metrics from all Sentinel-1 and Sentinel-2 observation in 2018 have been used to create synthetically mixed training data for regression. An elevation threshold of 1350m has been applied above which built-up surfaces and infrastructures were masked out.The mapping workflow has been established in the corresponding publication. This dataset is an enhanced dataset that uses an alternative set of spectral-temporal metrics for land cover modeling, including:- 25th, 50th and 75th quantile of Sentinel-2 reflectance- Average Sentinel-1 VH polarized backscatter- 90th quantile and standard deviation of Sentinel-2 Tasseled Cap GreennessThis enhanced set makes use of Sentinel-1 imagery, which reduces confusion of built-up features and seasonal soil-covered surfaces. Sentinel-2 Tasseled Cap Greenness is a more robust indicator for vegetation in temperate regions than the NDVI, which was used in the corresponding publication. The file is of GeoTiff format and contains three bands:Band 1 - Fraction of built-up surfaces and infrastructureBand 2 - Fraction of woody vegetationBand 3 - Fraction of non-woody vegetationFor further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de).Sentinel-1 data was kindly provided by TU Vienna (https://www.geo.tuwien.ac.at/) through EODC (https://www.eodc.eu/).This research has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 741950).
DOI: 10.1594/pangaea.908956
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during February, 2014
DOI: 10.1594/pangaea.909473
title: Geochemistry at BIGO station POS518/2_3-1 on given timesteps
DOI: 10.1594/pangaea.893538
title: Physical oceanography during towed CTD track POS518/1_9-1 (VCTD04)
DOI: 10.1594/pangaea.902675
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during February, 2017
DOI: 10.1594/pangaea.910586
title: Physical oceanography during towed CTD track POS534_15-1 (VCTD05)
DOI: 10.1594/pangaea.902686
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during December, 2017
DOI: 10.1594/pangaea.902392
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during March, 2011
DOI: 10.1594/pangaea.902669
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during May, 2016
DOI: 10.1594/pangaea.902677
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during April, 2017
DOI: 10.1594/pangaea.902370
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during September, 2009
DOI: 10.1594/pangaea.902399
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during June, 2011
DOI: 10.1594/pangaea.902618
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during March, 2014
DOI: 10.1594/pangaea.902632
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during February, 2015
DOI: 10.1594/pangaea.902467
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during March, 2013
DOI: 10.1594/pangaea.902625
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during September, 2014
DOI: 10.1594/pangaea.902673
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during December, 2017
DOI: 10.1594/pangaea.883202
title: Oxygen optode measurements collected during the first EGIM deployment at the OBSEA cabled observatory, March, 2017

description: Uncalibrated sensor data
DOI: 10.1594/pangaea.902730
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during January, 2018
DOI: 10.1594/pangaea.902628
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during November, 2014
DOI: 10.1594/pangaea.902629
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during December, 2014
DOI: 10.1594/pangaea.908910
title: Wave measurements (Nortec AWAC 1 Mhz ADCP) collected at the OBSEA underwater observatory during July, 2011
DOI: 10.1594/pangaea.893430
title: Swath sonar multibeam bathymetry during POSEIDON cruise POS518/1 with links to raw data files

description: Data acquisition was performed using a multibeam sonar system ELAC Nautik SeaBeam 3050. L-3 (.xse) files can be processed using the software packages CARIS HIPS/SIPS, Caraibes or with the open source software package MB-System ((http://www.ldeo.columbia.edu/res/pi/MB-System/).
DOI: 10.1594/pangaea.910409
title: Methane and carbon dioxide concentrations measured during POSEIDON cruise POS527, 2018-08-20

description: A gas inlet was installed at the bow of RV Poseidon.Atmospheric gas concentrations of CH4 and CO2 were measured continuously with a Picarro G2301-f analyzer.Concentrations are given as “ppmV in dry air”.
DOI: 10.1594/pangaea.903273
title: Weather station (Meteo Sarti Vantage Pro2) measurements collected at the OBSEA shore station (UPC) during October, 2016
DOI: 10.1594/pangaea.903305
title: Weather station (Meteo Buoy WeatherStation Instrument 150WX) measurements collected at the OBSEA underwater observatory buoy during September, 2018
DOI: 10.1594/pangaea.902612
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during January, 2014
DOI: 10.1594/pangaea.902617
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during February, 2014
DOI: 10.1594/pangaea.902620
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during April, 2014
DOI: 10.1594/pangaea.902621
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during May, 2014
DOI: 10.1594/pangaea.902622
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during June, 2014
DOI: 10.1594/pangaea.902480
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during August, 2013
DOI: 10.1594/pangaea.902482
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during September, 2013
DOI: 10.1594/pangaea.902487
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during December, 2013
DOI: 10.1594/pangaea.902484
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during October, 2013
DOI: 10.1594/pangaea.902436
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during January, 2012
DOI: 10.1594/pangaea.902442
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during May, 2012
DOI: 10.1594/pangaea.902441
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during April, 2012
DOI: 10.1594/pangaea.902443
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during May, 2012
DOI: 10.1594/pangaea.902485
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during November, 2013
DOI: 10.1594/pangaea.902444
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during June, 2012
DOI: 10.1594/pangaea.902488
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during December, 2013
DOI: 10.1594/pangaea.902475
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during June, 2013
DOI: 10.1594/pangaea.902388
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during August, 2010
DOI: 10.1594/pangaea.902477
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during July, 2013
DOI: 10.1594/pangaea.902389
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during August, 2010
DOI: 10.1594/pangaea.902393
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during April, 2011
DOI: 10.1594/pangaea.902394
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during April, 2011
DOI: 10.1594/pangaea.902384
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during June, 2010
DOI: 10.1594/pangaea.902387
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during July, 2010
DOI: 10.1594/pangaea.883196
title: Oxygen optode measurements collected during the first EGIM deployment at the OBSEA cabled observatory, January, 2017

description: Uncalibrated sensor data
DOI: 10.1594/pangaea.902367
title: CTD (SBE 37 SMP) measurements collected at the OBSEA underwater observatory during June, 2009
DOI: 10.1594/pangaea.902386
title: CTD (SBE 16 PLUS V2) measurements collected at the OBSEA underwater observatory during July, 2010
DOI: 10.1594/pangaea.883880
title: Tsunameter measurements collected during the first EGIM deployment at the OBSEA cabled observatory, January, 2017

description: Uncalibrated sensor data
DOI: 10.1594/pangaea.884751
title: Tsunameter measurements collected during the first EGIM deployment at the OBSEA cabled observatory, March, 2017

description: Uncalibrated sensor data
DOI: 10.1594/pangaea.886764
title: ADCP measurements collected during the first EGIM deployment at the OBSEA cabled observatory, March, 2017

description: Uncalibrated sensor data