cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.970663
title: Laser altimeter data obtained over sea-ice during the IceBird Summer campaign in Sep, 2020; profile P6_222_IceBird_MOSAiC_2020_SBLA_20200907T1116_81.39_-5.89_thr06_data_Vers5

description: Sea ice surface roughness data were obtained during the IceBird Summer campaign in Sep, 2020 with a Single Beam Laser Altimeter (SBLA) mounted inside an electromagnetic system (EM-Bird) towed at 10-30 m height above surface by an Airplane (Basler BT-67, Polar-6). A method developed by Hibler (1972) was used to a) isolate the surface profile from low-frequency variations associated with the aircraft motion and b) to identify pressure ridge sails. The processing steps are described in https://epic.awi.de/id/eprint/56364/. We applied a ridge detection threshold of 0.6 m, which means that only sails higher 0.6 m are detected. Version and name of the processing routine: Laser_Altimeter_Processing_VS5_06_20.py (vers.5, Feb 22, 2024, https://gitlab.awi.de/sitem/sbla_processing.git). SBLA records (ASTECH - LDM) are provided at a sampling rate of 100 Hz. Sensor accuracy is 2 cm with a beam diameter at surface of 6.3 cm. This specific dataset was obtained on 20200907T1116. It includes recorded altimeter readings, the derived surface elevation and width/height/spacing of detected pressure ridge sails. Note on data quality: 6.3 cm . File name: [DMS/PANGAEA Campaing Identifier] + [DEVICE] + [DATE/TIME] + [LAT/LON] + [Detection Threshold] + [Object] + [Version] + [Format]
DOI: 10.1594/pangaea.970664
title: Laser altimeter data obtained over sea-ice during the IceBird Summer campaign in Sep, 2020; profile P6_222_IceBird_MOSAiC_2020_SBLA_20200907T1145_81.39_-4.84_thr06_data_Vers5

description: Sea ice surface roughness data were obtained during the IceBird Summer campaign in Sep, 2020 with a Single Beam Laser Altimeter (SBLA) mounted inside an electromagnetic system (EM-Bird) towed at 10-30 m height above surface by an Airplane (Basler BT-67, Polar-6). A method developed by Hibler (1972) was used to a) isolate the surface profile from low-frequency variations associated with the aircraft motion and b) to identify pressure ridge sails. The processing steps are described in https://epic.awi.de/id/eprint/56364/. We applied a ridge detection threshold of 0.6 m, which means that only sails higher 0.6 m are detected. Version and name of the processing routine: Laser_Altimeter_Processing_VS5_06_20.py (vers.5, Feb 22, 2024, https://gitlab.awi.de/sitem/sbla_processing.git). SBLA records (ASTECH - LDM) are provided at a sampling rate of 100 Hz. Sensor accuracy is 2 cm with a beam diameter at surface of 6.3 cm. This specific dataset was obtained on 20200907T1145. It includes recorded altimeter readings, the derived surface elevation and width/height/spacing of detected pressure ridge sails. Note on data quality: 6.3 cm . File name: [DMS/PANGAEA Campaing Identifier] + [DEVICE] + [DATE/TIME] + [LAT/LON] + [Detection Threshold] + [Object] + [Version] + [Format]
DOI: 10.1594/pangaea.970665
title: Laser altimeter data obtained over sea-ice during the IceBird Summer campaign in Sep, 2020; profile P6_222_IceBird_MOSAiC_2020_SBLA_20200907T1010_81.83_-5.64_thr06_data_Vers5

description: Sea ice surface roughness data were obtained during the IceBird Summer campaign in Sep, 2020 with a Single Beam Laser Altimeter (SBLA) mounted inside an electromagnetic system (EM-Bird) towed at 10-30 m height above surface by an Airplane (Basler BT-67, Polar-6). A method developed by Hibler (1972) was used to a) isolate the surface profile from low-frequency variations associated with the aircraft motion and b) to identify pressure ridge sails. The processing steps are described in https://epic.awi.de/id/eprint/56364/. We applied a ridge detection threshold of 0.6 m, which means that only sails higher 0.6 m are detected. Version and name of the processing routine: Laser_Altimeter_Processing_VS5_06_20.py (vers.5, Feb 22, 2024, https://gitlab.awi.de/sitem/sbla_processing.git). SBLA records (ASTECH - LDM) are provided at a sampling rate of 100 Hz. Sensor accuracy is 2 cm with a beam diameter at surface of 6.3 cm. This specific dataset was obtained on 20200907T1010. It includes recorded altimeter readings, the derived surface elevation and width/height/spacing of detected pressure ridge sails. Note on data quality: 6.3 cm . File name: [DMS/PANGAEA Campaing Identifier] + [DEVICE] + [DATE/TIME] + [LAT/LON] + [Detection Threshold] + [Object] + [Version] + [Format]
DOI: 10.1594/pangaea.970666
title: Laser altimeter data obtained over sea-ice during the IceBird Summer campaign in Sep, 2020; profile P6_222_IceBird_MOSAiC_2020_SBLA_20200907T1052_81.23_-4.19_thr06_data_Vers5

description: Sea ice surface roughness data were obtained during the IceBird Summer campaign in Sep, 2020 with a Single Beam Laser Altimeter (SBLA) mounted inside an electromagnetic system (EM-Bird) towed at 10-30 m height above surface by an Airplane (Basler BT-67, Polar-6). A method developed by Hibler (1972) was used to a) isolate the surface profile from low-frequency variations associated with the aircraft motion and b) to identify pressure ridge sails. The processing steps are described in https://epic.awi.de/id/eprint/56364/. We applied a ridge detection threshold of 0.6 m, which means that only sails higher 0.6 m are detected. Version and name of the processing routine: Laser_Altimeter_Processing_VS5_06_20.py (vers.5, Feb 22, 2024, https://gitlab.awi.de/sitem/sbla_processing.git). SBLA records (ASTECH - LDM) are provided at a sampling rate of 100 Hz. Sensor accuracy is 2 cm with a beam diameter at surface of 6.3 cm. This specific dataset was obtained on 20200907T1052. It includes recorded altimeter readings, the derived surface elevation and width/height/spacing of detected pressure ridge sails. Note on data quality: 6.3 cm . File name: [DMS/PANGAEA Campaing Identifier] + [DEVICE] + [DATE/TIME] + [LAT/LON] + [Detection Threshold] + [Object] + [Version] + [Format]
DOI: 10.15468/dl.wbbxff
title: Occurrence Download

description: A dataset containing 11048783 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "Year 2020-2025"
 ]
}

 The dataset includes 11048783 records from 266 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061840-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14613607
title: Connectivity performance metrics Grain Automate GRDC Northern Region farm 2024-10 (1st of 2 uploads)

description: A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime and WAN quality, captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms for the monthh of October 2024.
DOI: 10.5281/zenodo.14523085
title: Connectivity performance metrics Grain Automate GRDC Southern Region farm 2024-10

description: A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime and wan quality captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms, for the month of October 2024
DOI: 10.5281/zenodo.14523142
title: Connectivity performance metrics Grain Automate GRDC Western Region farm 2024-10

description: A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime, wan quality captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms, for the month of October 2024.
DOI: 10.5281/zenodo.14613608
title: Connectivity performance metrics Grain Automate GRDC Northern Region farm 2024-10 (1st of 2 uploads)

description: A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime and WAN quality, captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms for the monthh of October 2024.
DOI: 10.5281/zenodo.14613632
title: Connectivity performance metrics Grain Automate GRDC Northern Region farm 2024-10 (2nd of 2 uploads)

description: A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime and WAN quality, captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms, for the month of October 2024.
DOI: 10.5281/zenodo.14613633
title: Connectivity performance metrics Grain Automate GRDC Northern Region farm 2024-10 (2nd of 2 uploads)

description: A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime and WAN quality, captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms, for the month of October 2024.
DOI: 10.57841/casdc.0004668
title: 水稻新品种“植优701”推广面积证明
DOI: 10.57841/casdc.0004669
title: 水稻新品种“科珞优4302”审定材料
DOI: 10.57841/casdc.0004670
title: 水稻新品种“科天优4312”审定相关材料
DOI: 10.15468/dl.sv3rrm
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-65.97619 51.21179,-54.7462 51.21179,-54.7462 60.73992,-65.97619 60.73992,-65.97619 51.21179))",
 "HasGeospatialIssue is false",
 "TaxonKey is Dactylorhiza viridis (L.) R.M.Bateman, Pridgeon & M.W.Chase"
 ]
}

 The dataset includes 28 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061843-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0004671
title: 水稻新品种“科荃优4302”审定及推广证明
DOI: 10.5281/zenodo.14619017
title: Possible surface fault trace of Dingri Earthquake

description: The possible surface fault trace of Dingri Earthquake found from LT-1 interfergram for your reference.

Please feel free to get intouch with us at wenbin.xu@csu.edu.cn
DOI: 10.5281/zenodo.14619018
title: Possible surface fault trace of Dingri Earthquake

description: The possible surface fault trace of Dingri Earthquake found from LT-1 interfergram for your reference.

Please feel free to get intouch with us at wenbin.xu@csu.edu.cn
DOI: 10.15468/dl.g49f5z
title: Occurrence Download

description: A dataset containing 9182 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Zonotrichia capensis (P.L.S.Müller, 1776)"
 ]
 },
 "HasCoordinate is TRUE",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2023",
 "DecimalLatitude is greater than or equal to -13.0",
 "DecimalLatitude is less than or equal to -10.0",
 "DecimalLongitude is greater than or equal to -77.0",
 "DecimalLongitude is less than or equal to -75.0",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 9182 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061844-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0004672
title: 水稻新品种“泰优203”审定及推广证明材料
DOI: 10.6084/m9.figshare.28169672
title: Wildman's Cave drip hydrology 2014-2017

description: Drip logger dataset from Wildman’s cave at Wombeyan, southeast Australia, 2014-2017. Data is collected every 15 minutes from multiple drip sites.
DOI: 10.15468/dl.csnsdb
title: Occurrence Download

description: A dataset listing the 221 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Database on Forest Disturbances in Europe"
 ]
}

 The dataset's 221 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061842-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0004673
title: 水稻新品种“科贵优4302”审定及推广面积证明
DOI: 10.15468/dl.8dcc25
title: Occurrence Download

description: A dataset containing 2237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Corylus colurna L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2237 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061845-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0004674
title: 水稻新品种“天优4302”审定及推广面积证明
DOI: 10.15468/dl.xsdrm2
title: Occurrence Download

description: A dataset containing 3749 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Corynocarpus laevigatus J.R.Forst. & G.Forst.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3749 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061846-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57841/casdc.0004675
title: 水稻新品种“弘优2903”审定及推广面积证明
DOI: 10.25903/6cr5-dx39
title: Data from: Operationalizing and measuring climate change adaptation success

description: <p>Data used for thesis chapter and journal article on relationship between adaptive responses implemented in response to climate change impacts and experienced outcomes by Asian-Pacific reef tourism operators</p>

<p>Please refer to the thesis and article (Related publications) for further details and the full methods.</p>

<p>This dataset consists of:</p>

<p>Raw dataset (CSV file), dataset with chi-square analyses results (CSV file), and seven anonymized lists with reef tourism operators (population) by location (CSV files). R Markdown file can be found in the SI of the published journal article.</p>

<p>These files are open access and can be downloaded from the links provided.</p>

<p>Software/equipment used to create/collect the data: <a href="https://www.kobotoolbox.org/">https://www.kobotoolbox.org/</a></p>

<p>Software/equipment used to manipulate/analyse the data: Excel and R programming language</p>
DOI: 10.15468/dl.beuvtu
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-65.97619 51.21179,-54.7462 51.21179,-54.7462 60.73992,-65.97619 60.73992,-65.97619 51.21179))",
 "HasGeospatialIssue is false",
 "TaxonKey is Cypripedium parviflorum Salisb."
 ]
}

 The dataset includes 24 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061847-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u3ca5p
title: Occurrence Download

description: A dataset containing 460 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Corypha utan Lam.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 460 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061848-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/ds/6449742
title: 📃40K Movie Scripts from Springfield! Springfield!
DOI: 10.15468/dl.4ncq9k
title: Occurrence Download

description: A dataset containing 7837 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lasiodiplodia theobromae (Pat.) Griffon & Maubl."
 ]
}

 The dataset includes 7837 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061849-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ux2yn4
title: Occurrence Download

description: A dataset containing 64710 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cotinus coggygria Scop.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 64710 records from 421 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061850-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14619028
title: Using Technology to Promote Excellence: Approaches, Difficulties, and Consequences for International Language Learning

description: The demand for creative and pertinent language education methods has grown in the age of constantly changing globalization. Recent research has demonstrated how well techniques like task-based learning, content-based approaches, and the incorporation of technology like augmented reality may raise student motivation, engagement, and competency. However, a number of issues still need to be resolved, such as how to maintain the effects of technology, modify teaching strategies for students with different skill levels, and ensure the well-being of educators in the face of technological pressure. In order to highlight research gaps and offer practical suggestions for more inclusive and sustainable language instruction, this article attempts to compile findings from a number of recent studies.There is an increasing need for innovation and relevance in the methods for teaching language in the age of globalization. It has been shown recently how effective task-based learning, Content Based Instruction, and integrating technology such as augmented reality can be in increasing student motivation, involvement, and competency. However, there are a number of challenges that need to be addressed, for example, overcoming challenges of sustaining the impacts of the technology, addressing the instructional needs of learners with diverse abilities, and maintaining teacher wellbeing under the pressure of technology. This article seeks to bring together the outcomes of a range of Contemporary studies in order to identify the gaps and suggest how language teaching could be made more impactful and inclusive.
DOI: 10.5281/zenodo.14619029
title: Using Technology to Promote Excellence: Approaches, Difficulties, and Consequences for International Language Learning

description: The demand for creative and pertinent language education methods has grown in the age of constantly changing globalization. Recent research has demonstrated how well techniques like task-based learning, content-based approaches, and the incorporation of technology like augmented reality may raise student motivation, engagement, and competency. However, a number of issues still need to be resolved, such as how to maintain the effects of technology, modify teaching strategies for students with different skill levels, and ensure the well-being of educators in the face of technological pressure. In order to highlight research gaps and offer practical suggestions for more inclusive and sustainable language instruction, this article attempts to compile findings from a number of recent studies.There is an increasing need for innovation and relevance in the methods for teaching language in the age of globalization. It has been shown recently how effective task-based learning, Content Based Instruction, and integrating technology such as augmented reality can be in increasing student motivation, involvement, and competency. However, there are a number of challenges that need to be addressed, for example, overcoming challenges of sustaining the impacts of the technology, addressing the instructional needs of learners with diverse abilities, and maintaining teacher wellbeing under the pressure of technology. This article seeks to bring together the outcomes of a range of Contemporary studies in order to identify the gaps and suggest how language teaching could be made more impactful and inclusive.
DOI: 10.15468/dl.wnkrpy
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-65.97619 51.21179,-54.7462 51.21179,-54.7462 60.73992,-65.97619 60.73992,-65.97619 51.21179))",
 "HasGeospatialIssue is false",
 "TaxonKey is Cypripedium acaule Aiton"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061854-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13852434
title: Dataset Hydrogeological Units in Mexico Basin

description: Description
This is the initial release of the Mexico Basin project, which includes essential components for hydrogeological studies and topographic section generation. This project aims to provide users with the necessary tools and data to analyze hydrogeological units within the Mexico Basin region.

Included Files
Hydrogeological_Units/lineal: Contains shapefiles representing linear hydrogeological units.
Hydrogeological_Units/Polygon: Contains shapefiles representing polygonal hydrogeological units.
Surface/: Contains Shapefiles as length and directions of sections, faults, and hydrological units in the surface.
Sections.py: A Python script that automates the creation of topographic sections based on provided shapefiles and DEM data.
Topography/: Contains topographic sections.
README.md: Instructions and documentation for using the project.
requirements.txt: Lists the dependencies required to run the code.
Usage
The provided shapefiles can be used for academic purposes related to hydrogeological research.
To generate topographic sections, ensure you have the required dependencies installed as specified in requirements.txt.
Execute the Sections.py script to automate the section creation process.
License
This project is licensed under the CC License. See the LICENSE file for more details.
DOI: 10.5281/zenodo.14619021
title: Dataset Hydrogeological Units in Mexico Basin

description: Description This is release 2.0  of the Mexico Basin project, which includes essential components for hydrogeological studies and topographic section generation. This project aims to provide users with the necessary tools and data to analyze hydrogeological units within the Mexico Basin region.

Included Files Hydrogeological_Units/lineal: Contains shapefiles representing linear hydrogeological units. Hydrogeological_Units/Polygon: Contains shapefiles representing polygonal hydrogeological units. Surface/: Contains Shapefiles as length and directions of sections, faults, and hydrological units in the surface. Topography/: Contains topographic sections.  Graphics and Sorces/: Image and PDF used as inputs, Graphical abstract, Figures used in the document, and hydrogeological sections in format image. Sections.py: A Python script that automates the creation of topographic sections based on provided shapefiles and DEM data. Azimuth.py: A Python script that computes Azimuth and Dip direction. README.md: Instructions and documentation for using the project. requirements.txt: Lists the dependencies required to run the code. Usage The provided shapefiles can be used for academic purposes related to hydrogeological research. To generate topographic sections, ensure you have the required dependencies installed as specified in requirements.txt. Execute the Sections.py script to automate the section creation process. License This project is licensed under the CC License. See the LICENSE file for more details.