cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.kd34yb
title: Occurrence Download

description: A dataset containing 6516286 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "DatasetKey is EOD – eBird Observation Dataset",
 "OccurrenceStatus is Present",
 "Year 1000-2024"
 ]
}

 The dataset includes 6516286 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030446-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.er6ayc
title: Occurrence Download

description: A dataset containing 798 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen, Observation)",
 "Country is Spain",
 "DatasetKey is one of (FloraCAT: Banco de datos de los cormófitos de Cataluña, DIBA-Parc Natural del Montseny, CSIC-Real Jardín Botánico-Anthos. Sistema de Información de las Plantas de España, CeDoc de Biodiversitat Vegetal: BCN-Cormophyta, CSIC-Real Jardín Botánico-Colección de Plantas Vasculares (MA), VIT Herbarium - Vascular Plants (The Natural History Museum of Alava))",
 "Geometry POLYGON((3.20136 42.77672,2.67695 42.84823,0.97261 43.49183,0.16215 43.25346,0.00721 42.55027,-0.08814 41.60871,-0.00471 40.63139,0.78191 40.20233,1.50894 40.35727,2.60544 40.59564,3.3563 41.0247,3.69002 41.91859,3.20136 42.77672))",
 "OccurrenceStatus is Present",
 "TaxonKey is Senecio inaequidens DC."
 ]
}

 The dataset includes 798 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030529-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10586728
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10873936
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.11051272
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.11225198
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.12613331
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10586730
title: Linked collectors and determiners for: CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project).

description: Natural history specimen data linked to collectors and determiners held within, "CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10706761
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10873937
title: Linked collectors and determiners for: CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project).

description: Natural history specimen data linked to collectors and determiners held within, "CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.11051277
title: Linked collectors and determiners for: CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project).

description: Natural history specimen data linked to collectors and determiners held within, "CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.11225201
title: Linked collectors and determiners for: CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project).

description: Natural history specimen data linked to collectors and determiners held within, "CRSN-Lwiro Herbarium, Kahuzi-Biega National Park (CABIN project)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a91ff89-2dcc-4cfc-a4fb-a8ab97f28102. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.13124907
title: Linked collectors and determiners for: Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil.

description: Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Coniceromyia Borgmeier (Diptera: Phoridae), with the description of three new species from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8a8e4192-9016-40bd-b2e7-819f5da9613a. Formatted as a Frictionless Data package.
DOI: 10.4231/h73k-ge42
title: SDOF Analysis of Blast Loaded SC Panels in Two-Way Bending

description: &lt;p&gt;This package contains six MATLAB programs for conducting single-degree-of-freedom (SDOF) dynamic analysis of blast loaded steel-plate composite (SC) two-way panels. The programs can be used to run a SDOF analysis of a single blast pressure loading acting on a SC panel with either fixed or simply-supported boundary conditions. The programs can also be used to generate iso-damage pressure-impulse diagrams for a given pressure pulse shape. These programs allow quick analysis of SC panels to blast loadings for use in a parametric study or initial design stages of sizing a structural member.&lt;/p&gt;

&lt;ul&gt;
 &lt;li&gt;Program &quot;SC_SDOF_FIXED_V1_7.m&quot; conducts a SDOF analysis for a single blast pressure loading on a SC panel with fixed boundary conditions. The program version is 1.7.&lt;/li&gt;
 &lt;li&gt;Program &quot;SC_SDOF_SS_V1_7.m&quot; conducts a SDOF analysis for a single blast pressure loading on a SC panel with simply-supported (SS) boundary conditions. The program version is 1.7.&lt;/li&gt;
 &lt;li&gt;Program &quot;SC_SDOF_FIXED_PI_MAIN.m&quot; conducts SDOF analyses to develop iso-damage pressure-impulse (PI) diagrams for a given pressure pulse shape on a SC panel with fixed boundary conditions. This program uses &quot;SC_SDOF_FIXED_PI_V1_5.m&quot; as a subroutine for creating the PI diagrams. The program version is 1.5.&lt;/li&gt;
 &lt;li&gt;Program &quot;SC_SDOF_SS_PI_MAIN.m&quot; conducts SDOF analyses to develop iso-damage pressure-impulse diagrams for a given pressure pulse shape on a SC panel with simply-supported boundary conditions. This program uses &quot;SC_SDOF_SS_PI_V1_5.m&quot; as a subroutine for creating the PI diagrams. The program version is 1.5.&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;The input parameters for the programs and the operations performed in the program are fully described and annotated within each program file at each step of the program. Further background information and validation of the expressions used within the programs are described in detail in the reference below.&lt;/p&gt;

&lt;p&gt;Harmon, Joshua R. 2023. &quot;Blast Resistant Design of Two-Way Steel-Plate Composite (SC) Panels&quot; PhD. Dissertation. Purdue University, West Lafayette, IN.&lt;/p&gt;
description: These files contain quick running MATLAB programs which conduct a SDOF analysis of a blast loaded two-way SC panels with fixed or simply-supported edge constraints. The programs can also generate isodamage pressure-impulse diagrams for two-way SC panels.
DOI: 10.4231/0643-am58
title: Lunar Hydration at the South Pole observed by Deep Impact

description: &lt;p&gt;The dataset contains the information used to investigate the variability of the 3 micron hydration absorption feature  on the southern hemisphere of the Moon as observed by the Deep Impact spacecraft during the lunar flybys in 2009. We used this data to determine the dependencies (temperature, latitude, time of day) for the strength of the 3 micron feature, to understand what processes lead to the formation and loss of OH/H2O on the lunar surface.&lt;/p&gt;
description: Files used for calibration and analysis of hydration feature as observed by Deep Impact during the 2009 lunar flyby of the south pole
DOI: 10.4231/3akw-vx52
title: Dataset/Codes for the project: A Model for the Tropical Cyclone Wind Field Response to Idealized Landfall

description: &lt;p&gt;Here we design simplified landfall experiments. This set of experiments is designed to systematically understand how the TC wind field responds to each surface forcing with varying magnitudes, and how each individual forcing affects the wind field in comparison to applying both forcings simultaneously. Idealized landfall experiments are performed using the Bryan Cloud Model (CM1v19.8) in an axisymmetric geometry (see documents). &lt;/p&gt;
description: This dataset provides the CM1 scripts to reproduce the idealized TC landfalls, and simulation outputs of the landfall experiments examined in the paper.
DOI: 10.4231/4wn4-s032
title: Linking biogeochemical and hydrodynamic processes to model methane fluxes in shallow, tropical floodplain lakes.

description: &lt;p&gt;We modified a 1-dimensional process-based, lake biogeochemical model (ALBM) and combined a 3-dimensional hydrodynamic model to suit Amazon floodplains. We evaluated the combined model&#39;s performance simulating methane concentrations and fluxes and several related processes in the open lake and an embayment of a well-studied Amazon lake. Parameters for calibration were selected through sensitivity tests using a machine learning-based algorithm, classification and regression trees. This dataset contains the revised ALBM code for the study.&lt;/p&gt;
description: This dataset contains the revised Arctic Lake Biogeochemistry Model (ALBM) code for the study of Linking biogeochemical and hydrodynamic processes to model methane fluxes in shallow, tropical floodplain lakes.
DOI: 10.4231/0pg5-kc30
title: Data for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

description: &lt;p&gt;This study aims to build a Prediction in Ungauged Basins (PUB) model to predict daily streamflow series in ungauged basins in Ohio Region (HUC2; 05) from 2010 to 2020. Daily streamflow data from USGS gaging reaches are the output variable of PUB models. The input variables of PUB models in this study are watershed characteristics and meteorological variables. The watershed characteristics include drainage area, soil, and land-use condition of watersheds. The meteorological variables include daily observations of rainfall, snowfall, snow depth, and temperature. This dataset includes the input and output for the PUB models used in the study &quot;Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins&quot;. &lt;/p&gt;

&lt;p&gt;Article Abstract:&lt;/p&gt;

&lt;p&gt;Machine learning (ML) models are attractive alternatives to traditional hydrologic modeling for streamflow predictions in ungauged basins (PUB). However, the ungauged basins with highly variable watershed characteristics add uncertainties to PUB frameworks based on ML models. This uncertainty in the PUB frameworks may be due to the improper data splitting process of training/testing sets and the resulting covariate shift. Covariate shift refers to the inconsistency between the dataset used to train and test a ML model and the real-world (global) dataset on which the trained model is implemented. In real-world applications, covariate shift remains a thorny issue for ML but has seldom been investigated in a hydrologic setting. This study aims to evaluate the uncertainty in ML-based PUB under the influence of data splitting and covariate shift using the Monte Carlo method. The Monte Carlo method accumulates simulation results with different data split arrangements into the predictive distributions of pseudo ungauged reaches. Results indicate that ML performance is not robust under covariate shift. ML performance is influenced by the number of heterogeneous variables and specific watershed characteristics displaying heterogeneity, such as drainage area, dam influence, and urbanized percentage. Additionally, a comparison of predictive distributions between the ML performance in the best/worst group and overall reaches shows that the ML algorithm is significantly influenced by the variability in basin characteristics, such as dam density, drainage area, and meteorological variables, such as snowfall and precipitation.&lt;/p&gt;
description: This resource contains the data used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)
DOI: 10.4231/b783-2c47
title: Codes for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

description: &lt;p&gt;ML models have been successfully applied and found to consistently outperform physics-based PUB models. A machine learning (ML) algorithm can learn streamflow generation processes from input features, such as meteorological variables and watershed characteristics. In this study, the Random Forest (RF) and Artificial Neural Network (ANN) predict daily streamflow in ungauged basin (PUB). These ML models can be used to predict streamflow time series in any other large scale watersheds.&lt;/p&gt;

&lt;p&gt;Article Abstrct:&lt;/p&gt;

&lt;p&gt;Machine learning (ML) models are attractive alternatives to traditional hydrologic modeling for streamflow predictions in ungauged basins (PUB). However, the ungauged basins with highly variable watershed characteristics add uncertainties to PUB frameworks based on ML models. This uncertainty in the PUB frameworks may be due to the improper data splitting process of training/testing sets and the resulting covariate shift. Covariate shift refers to the inconsistency between the dataset used to train and test a ML model and the real-world (global) dataset on which the trained model is implemented. In real-world applications, covariate shift remains a thorny issue for ML but has seldom been investigated in a hydrologic setting. This study aims to evaluate the uncertainty in ML-based PUB under the influence of data splitting and covariate shift using the Monte Carlo method. The Monte Carlo method accumulates simulation results with different data split arrangements into the predictive distributions of pseudo ungauged reaches. Results indicate that ML performance is not robust under covariate shift. ML performance is influenced by the number of heterogeneous variables and specific watershed characteristics displaying heterogeneity, such as drainage area, dam influence, and urbanized percentage. Additionally, a comparison of predictive distributions between the ML performance in the best/worst group and overall reaches shows that the ML algorithm is significantly influenced by the variability in basin characteristics, such as dam density, drainage area, and meteorological variables, such as snowfall and precipitation.&lt;/p&gt;
description: This resource contains codes used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)
DOI: 10.4231/67yg-v518
title: A process-based biogeochemistry model and analysis for current and future global lake methane emissions

description: &lt;p&gt;Global lakes and reservoirs emit methane to the atmosphere.  Using diverse lake characteristics data and a lake biogeochemistry model, we estimate global lake methane emissions and investigate the effects of temperature increase, permafrost thaw, and thermokarst lake areal changes for the first and the last decades of the 21st century under different climate scenarios. This data deposit contains the code of the lake biogeochemistry model used for these emission estimates.&lt;/p&gt;
description: This data contains the source code of a lake biogeochemistry model - Arctic Lake Biogeochemistry Model (ALBM).
DOI: 10.4231/zbhc-3k73
title: Aerial imagery of the Purdue Agronomy Center for Research and Education (ACRE) – 1963

description: &lt;p&gt;Aerial imagery from 1963 covering the Purdue Agronomy Center for Research and Education (ACRE) (4530 US-52, West Lafayette, IN 47906; latitude / longitude in decimal degrees: 40.4698, -86.9927) and surrounding areas. The data were downloaded from the Indiana Geological and Water Survey website (https://igws.indiana.edu/) on January 9, 2017 and consisted of two individual images available in JPG format that had not been georeferenced. These original images are provided in the folder labeled &ldquo;Original_Scans.&rdquo; The images were georeferenced and projected using the Georeferencing tool in ArcGIS 10.6 and using as the standard base map the 2013 IndianaMap Data imagery from the same area that had previously been reprojected into the Indiana Geospatial Coordinate System NAD_1983_2011_InGCS_Tippecanoe-White_(m). For accurate georeferencing, stable and visible benchmarks such as roads, intersections, driveways, railroad tracks, culverts, etc. were used as control points. Sufficient control points (usually about 15) were added so that the spline transformation could be used for each image. The two individual images were then mosaicked into one georeferenced image using the Mosaic tool in ArcGIS 10.6. This mosaicked image, in the Indiana Geospatial Coordinate System NAD_1983_2011_InGCS_Tippecanoe-White_(m), is in the folder named &ldquo;Georeferenced.&rdquo;&lt;/p&gt;

&lt;p&gt;This data set was produced as part of a project funded by the Office of Agricultural Research and Graduate Education at Purdue University.&lt;/p&gt;
description: Aerial imagery from 1963 of the Purdue Agronomy Center for Research and Education (ACRE), West Lafayette, IN, USA.
DOI: 10.4231/f62q-w758
title: Coded data from: Risky behaviors in young adults during stair descent: males versus females

description: &lt;p&gt;Injuries commonly occur on stairs, with high injury rates in young adults, especially young adult females. The purpose was to quantify young adult male and female behaviors during stair descent. Behaviors of young adults (N=2,400) were coded (by two human coders) on two indoor campus staircases. The short staircase had two steps, and the long staircase had 17 steps. No one used the handrail on the short staircase, 65% of pedestrians did not use the handrail on the long staircase, and 13.7% used an electronic device. Risky behaviors observed more in females included: less likely to use the handrail, more likely to carry an item in their hands, more likely to engage in conversation, and more likely to wear sandals or heels (p&le;0.05). Protective behaviors observed more in females included: less likely to skip steps, and more likely to look at treads during transition steps (p&le;0.05). The observed behaviors may be related to the high injury rate of stair-related falls in young adults, and females specifically.&lt;/p&gt;
description: 2,400 young adult pedestrians were videotaped while descending staircases and the characteristics and behaviors were coded by humans offline. The file contains the coded characteristics and behaviors of each pedestrian.