cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7636109
title: MOKE-microscopy-Skyrmion-dataset

description: Magnetic skyrmions in thin-film systems are heavily under investigation due to their potential applicability for spintronic applications.


An often used imagning techniqe is the magneto-optical Kerr effect (MOKE-)microscopy. Here we provide approximately 2400 MOKE images of around 30 different thin film measurements, focused on magnetic skyrmions and material defects. The dataset counts more than 1 million skyrmions. Corresponding labels are also provided pixelwise as a 3-class label (Background, skyrmion, defect) for training neural network devices on detection.


Own U-Net based pre-trained models are available for direct usage.


The corresponding publication is in preparation. Statistics and models used for publication are also included.
description: We thank all the experimentalists in the Kläui-Lab that took the MOKE measurements over the past for their own projects.
The data is split in fixed training/validation and test set, as the training labels are considered to be relatively weak - due to some relabeling process -, while the validation and test set are labeled carefully by hand.
DOI: 10.15468/dl.7vem74
title: Occurrence Download

description: A dataset containing 2433 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Isthmura bellii (Gray, 1850)"
 ]
}

 The dataset includes 2433 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021937-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t2zckx
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Phrynopus horstpauli Lehr, Köhler & Ponce, 2000)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060301-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.axtsjy
title: Occurrence Download

description: A dataset containing 171 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 "Geometry POLYGON((-78.79394 1.49843,-80.49683 0.56476,-81.48559 -1.24788,-80.33203 -2.34596,-80.66162 -3.77211,-80.22217 -4.59388,-78.79394 -5.30532,-78.0249 -3.498,-77.47558 -2.8947,-75.22339 -1.90681,-75.22339 -0.53386,-76.43188 0.72954,-76.81641 0.39997,-78.79394 1.49843))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Puma concolor (Linnaeus, 1771)"
 ]
}

 The dataset includes 171 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0319478-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-46874
title: Redemption tidings, vol. 20, nos. 1-26, 1 Jan. - 15 Dec. 1944

description: [description english/roman)] Issued fortnightly (every two weeks). "A full gospel magazine for all believers" -- subtitle. Includes Tidings from our missionaries in each issue (1 Jan. - 5 May, 2 June - 11 Aug., 8 Sept. - 15 Dec. 1944) except vol. 20, nos. 11 & 18. Bound with Redemption tidings vol. 19.
DOI: 10.5066/p9uet694
title: MODFLOW-NWT model used in simulation of groundwater availability in reaches 3 and 4 of the Washita River aquifer, southern Oklahoma, 1980&amp;amp;amp;amp;ndash;2017

description: The U.S. Geological Survey (USGS), in cooperation with the Oklahoma Water Resources Board (OWRB), constructed a finite-difference numerical groundwater-flow model of the Washita River aquifer by using MODFLOW-2005 (Harbaugh, 2005) with the Newton formulation solver (MODFLOW-NWT). The 1973 Oklahoma Groundwater Law requires that the OWRB conduct hydrologic investigations of the State&rsquo;s aquifers to determine the maximum annual yield (MAY) for each groundwater basin. The MAY is defined as the total amount of fresh groundwater that can be annually withdrawn while allowing a minimum 20-year life of that groundwater basin. For alluvium and terrace groundwater basins, the life requirement is satisfied if, after 20 years of MAY withdrawals, 50 percent of the groundwater basin (hereinafter referred to as an &ldquo;aquifer&rdquo;) retains a saturated thickness of at least 5 ft. Once a MAY has been established, the amount of land owned or leased by a groundwater-use permit applicant determines the annual volume of water allocated to that groundwater-use permit applicant. The annual volume of groundwater allocated per acre of land is known as the equal-proportionate-share (EPS) pumping rate. The OWRB issued a final order on November 13, 1990, that established the MAY (81,840 and 46,935 acre-feet per year [acre-ft/yr]) and EPS pumping rate (1.5 and 1.0 acre-foot per acre per year) for reaches 3 and 4, respectively, of the Washita River aquifer in southern Oklahoma. Because more than 20 years have elapsed since the final order was issued, the USGS, in cooperation with the OWRB, conducted an updated hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in the Washita River aquifer in southern Oklahoma. Reach 3 extends from near Anadarko, Okla., to Alex, Okla., and reach 4 extends from near Alex to south of Davis, Okla. Twenty-four simulations are included in this data release: a simulation for the calibrated numerical groundwater-flow model, 18 scenario simulations to evaluate the EPS pumping rate, 4 scenario simulations to evaluate groundwater storage over a 50-year period, and 1 scenario simulation to evaluate effects of a hypothetical drought. This USGS data release contains all of the input and output files for the simulations described in the associated model documentation report (https://doi.org/10.3133/sir20235072).
DOI: 10.5281/zenodo.10993540
title: Spatial Data Recovery and Resilience of Oyster Reefs in the Big Bend of Florida
title: Recovery and Resilience of Oyster Reefs in the Big Bend of Florida

description: Project: Recovery and Resilience of Oyster Reefs in the Big Bend of Florida

https://wec.ifas.ufl.edu/oysterproject/

Lone Cabbage Reef Restoration Spatial Data (2017-2023) Repository:

https://zenodo.org/communities/lonecabbagereef

Contact: Joe Aufmuth, University of Florida, George A. Smathers Libraries, Academic Research and Consulting Services Department, mapper@ufl.edu, (352) 273-0371.

Clarifying Publication: Aufmuth, Moore, Pine, and Ennis (2024 in progress), An Oyster’s Pearl: Restoring the Elevation of Lone Cabbage Reef, Florida.

The repository contains ArcGIS Map Packages (v3.2.0) that are listed in the repository file Descriptions_Lone_Cabbage_Reef_map_package_list_xls. 

Purpose: Data collected varies in scale as well as positional and attribute accuracy.  It is the responsibility of the user to verify that the data are appropriate for their project.  No warranties or guarantees are made that the data are appropriate for uses other than the Recovery and Resilience of Oyster Reefs in the Big Bend of Florida project.

Data Collection:  Elevation data was collected through professional certified surveyors (Lone Cabbage Reef 2017, 2018, and 2021) as well as through field data collection efforts using Trimble survey grade GPS equipment (University of Florida 2019).  Oyster count data locations were collected through field efforts and mapped to field transects using Juniper GPS survey equipment (2018, 2019, 2020, 2021, 2022, 2023).  Other spatial data layers included in this data set are credited in the layouts that produce the individual maps in the map packages.
DOI: 10.5281/zenodo.10993541
title: Spatial Data Recovery and Resilience of Oyster Reefs in the Big Bend of Florida
title: Recovery and Resilience of Oyster Reefs in the Big Bend of Florida

description: Project: Recovery and Resilience of Oyster Reefs in the Big Bend of Florida

https://wec.ifas.ufl.edu/oysterproject/

Lone Cabbage Reef Restoration Spatial Data (2017-2023) Repository:

https://zenodo.org/communities/lonecabbagereef

Contact: Joe Aufmuth, University of Florida, George A. Smathers Libraries, Academic Research and Consulting Services Department, mapper@ufl.edu, (352) 273-0371.

Clarifying Publication: Aufmuth, Moore, Pine, and Ennis (2024 in progress), An Oyster’s Pearl: Restoring the Elevation of Lone Cabbage Reef, Florida.

The repository contains ArcGIS Map Packages (v3.2.0) that are listed in the repository file Descriptions_Lone_Cabbage_Reef_map_package_list_xls. 

Purpose: Data collected varies in scale as well as positional and attribute accuracy.  It is the responsibility of the user to verify that the data are appropriate for their project.  No warranties or guarantees are made that the data are appropriate for uses other than the Recovery and Resilience of Oyster Reefs in the Big Bend of Florida project.

Data Collection:  Elevation data was collected through professional certified surveyors (Lone Cabbage Reef 2017, 2018, and 2021) as well as through field data collection efforts using Trimble survey grade GPS equipment (University of Florida 2019).  Oyster count data locations were collected through field efforts and mapped to field transects using Juniper GPS survey equipment (2018, 2019, 2020, 2021, 2022, 2023).  Other spatial data layers included in this data set are credited in the layouts that produce the individual maps in the map packages.
DOI: 10.5281/zenodo.10997391
title: Raw datasets and code generation for the strength prediction of TBC incorporating CCA and GOS
DOI: 10.5281/zenodo.10997392
title: Raw datasets and code generation for the strength prediction of TBC incorporating CCA and GOS
DOI: 10.5281/zenodo.10997481
title: DIGIPART - Digitalisation in Parties dataset (v.0)

description: The Digitalisation in Parties (DIGIPART) dataset (v.0) contains information on party digitalisation features from 62 parties from five major European countries: Germany, Italy, France, Spain and the United Kingdom. The dataset is stored in Excel format (xlsx) as well as the codebook. The information and evidence from the different parties was gathered and coded between July 2021 and September 2022.

The DIGIPART dataset (v.0) compiles information on the digitalisation features of 62 political parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. It is stored in Excel format (xlsx), along with a codebook, serving as a valuable resource for researchers.

While numerous studies examine the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to fill this gap by mapping and analysing parties' digitalisation efforts.

DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov.

Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.
DOI: 10.5281/zenodo.10997482
title: DIGIPART - Digitalisation in Parties dataset (v.0)

description: The Digitalisation in Parties (DIGIPART) dataset (v.0) contains information on party digitalisation features from 62 parties from five major European countries: Germany, Italy, France, Spain and the United Kingdom. The dataset is stored in Excel format (xlsx) as well as the codebook. The information and evidence from the different parties was gathered and coded between July 2021 and September 2022.

The DIGIPART dataset (v.0) compiles information on the digitalisation features of 62 political parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. It is stored in Excel format (xlsx), along with a codebook, serving as a valuable resource for researchers.

While numerous studies examine the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to fill this gap by mapping and analysing parties' digitalisation efforts.

DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov.

Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.
DOI: 10.15468/dl.qm5px8
title: Occurrence Download

description: A dataset containing 8013 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dictamnus albus L., Digitalis viridiflora Lindl., Dipsacus sativus (L.) Honck., Dipsacus sativus (L.) Honck., Draba hispanica Boiss., Draba bruniifolia Steven)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 8013 records from 126 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0158555-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dgu75m
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Craugastor tabasarae (Savage, Hollingsworth, Lips & Jaslow, 2004))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 37 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060330-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tub89m
title: Occurrence Download

description: A dataset containing 7709 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astyanax mexicanus (De Filippi, 1853)"
 ]
}

 The dataset includes 7709 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0338578-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-46470
title: Redemption tidings, vol. 18, nos. 1-26, 2 Jan. - 18 Dec. 1942

description: [description english/roman)] Issued fortnightly (every two weeks). "A full gospel magazine for all believers" -- subtitle. Includes Tidings from our missionaries in each issue (1 Jan. - 22 May, 19 June, 17 July - 4 Dec. 1942) except vol. 18, nos. 11, 14 & 26.
DOI: 10.5281/zenodo.10991102
title: Dataset: Machine Learning Based Prediction of Polaron-Vacancy Patterns on the TiO$_2$(110) Surface
DOI: 10.5281/zenodo.10991103
title: Dataset: Machine Learning Based Prediction of Polaron-Vacancy Patterns on the TiO$_2$(110) Surface
DOI: 10.15468/dl.277smj
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Dalbergia benthamii Prain"
 ]
}

 The dataset includes 64 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0144370-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tfxm5u
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gastrotheca pachachacae Catenazzi & von May, 2011)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060372-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v2xhg6
title: Occurrence Download

description: A dataset containing 272 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Petrochromis trewavasae Poll, 1948"
 ]
}

 The dataset includes 272 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0338570-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-47174
title: Redemption tidings, vol. 22, nos. 1-26, 4 Jan. - 20 Dec. 1946

description: [description english/roman)] Issued fortnightly (every two weeks). "A full gospel magazine for all believers" -- subtitle. Includes Tidings from our missionaries in each issue (4 Jan. - 20 Dec. 1946). Bound with vol. 23.
DOI: 10.5281/zenodo.10997394
title: DIGIPART - Digitalisation in Parties dataset (v.1.1)

description: The Digitalisation in Parties (DIGIPART) dataset (v.1) comprises information on party digitalisation features from 72 parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. Compared to the initial version (v.0), which included data from 62 parties, version 1.1 of the DIGIPART dataset has been expanded to include new data on additional regional parties within these countries (n=76).

The dataset, stored in Excel format (xlsx) along with a codebook, captures information and evidence from various parties, collected and coded between July 2021 and September 2022.

Despite numerous studies examining the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to address this gap by mapping and analysing parties' digitalisation efforts.

DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov.

Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.
DOI: 10.5281/zenodo.10997395
title: DIGIPART - Digitalisation in Parties dataset (v.1.1)

description: The Digitalisation in Parties (DIGIPART) dataset (v.1) comprises information on party digitalisation features from 72 parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. Compared to the initial version (v.0), which included data from 62 parties, version 1.1 of the DIGIPART dataset has been expanded to include new data on additional regional parties within these countries (n=76).

The dataset, stored in Excel format (xlsx) along with a codebook, captures information and evidence from various parties, collected and coded between July 2021 and September 2022.

Despite numerous studies examining the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to address this gap by mapping and analysing parties' digitalisation efforts.

DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov.

Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.