cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8h3uzh
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tapinotaspis Holmberg, 1903",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008693-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ucahvy
title: Occurrence Download

description: A dataset containing 154 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Microlophus tigris (Tschudi, 1845)"
 ]
}

 The dataset includes 154 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008290-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.29t6yf
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Indigofera thymoides Baker"
 ]
}

 The dataset includes 26 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030932-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.phdhmh
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corsia crenata J.J.Sm."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008703-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m9zkfn
title: Occurrence Download

description: A dataset containing 210 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lasthenia ferrisiae Ornduff"
 ]
}

 The dataset includes 210 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008290-160822134323880/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y6rz4b
title: Occurrence Download

description: A dataset containing 198257 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hydrocotyle vulgaris L."
 ]
}

 The dataset includes 198257 records from 949 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030952-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tfvuuj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"12222470","matchCase":false},{"type":"equals","key":"OCCURRENCE_STATUS","value":"PRESENT","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"HAS_GEOSPATIAL_ISSUE","value":"false","matchCase":false},{"type":"lessThan","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"in","key":"YEAR","values":["2008","2009","2010","2011","2012","2013","2014","2015","2016","2017","2018","2019","2020","2021","2022","2023","2024"],"matchCase":false},{"type":"in","key":"BASIS_OF_RECORD","values":["LIVING_SPECIMEN","HUMAN OBSERVATION","OBSERVATION","OCCURRENCE","MACHINE_OBSERVATION"],"matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023188-241024112534372/datasets/export for details.
DOI: 10.6084/m9.figshare.27612186
title: amea figshare

description: Impact of a Three-Month Training Break on Swimming Performance in Athletes with Intellectual Disability
DOI: 10.6084/m9.figshare.27612186.v1
title: amea figshare

description: Impact of a Three-Month Training Break on Swimming Performance in Athletes with Intellectual Disability
DOI: 10.15468/dl.jyygxx
title: Occurrence Download

description: A dataset containing 1013 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((120.67285 25.51505,118.95829 23.53205,119.43309 21.77948,121.46419 21.26417,122.28191 21.63244,122.96773 23.41107,123.15238 24.56782,121.64884 26.06993,120.67285 25.51505))",
 "HasGeospatialIssue is false",
 "TaxonKey is Tsuga chinensis (Franch.) E.Pritz."
 ]
}

 The dataset includes 1013 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023187-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10461732
title: Doppler Lidar virtual tower horizontal wind speed, wind direction, TKE, and gust data measured between 01 June and 14 September 2020 in Falkenberg (Tauche), Germany

description: The data presented here was collected between 01 June and 14 September 2020 in Falkenberg (Tauche), Germany, during the FESST@MOL (Field Experiment on sub-mesoscale spatio-temporal variability at the Meteorological Observatory Lindenberg) 2020 campaign, which was initiated by the Hans-Ertel-Center for Weather Research. The measurements took place at the boundary layer field site (GM) Falkenberg, Germany. The data collected in this campaign were measured by three Doppler Lidars (DL) set-up as a virtual tower (VT) testing five different VT scanning methods, operated by the Karlsruhe Institute of Technology. We tested different step/stare and range-height-indicator (RHI) scanning methods.

NetCDF_to_VirtualTower.R contains the R code used to read in the Lidar data, apply the data filters and calculate the mean horizontal wind speed and wind direction.

Further details on this data set can be found in the attached data documentation.
description: This work has been funded by the German Federal Ministry for Digital and Transport (BMDV) within the framework of the DWD program for extramural research, project: Quality Assessment of ground-based Lidar measurements in the Boundary layer (QALiBo): evaluation and verification of scanning strategies, quality tests and uncertainty quantification / contract number: 4819EMF05.
DOI: 10.5281/zenodo.10461733
title: Doppler Lidar virtual tower horizontal wind speed, wind direction, TKE, and gust data measured between 01 June and 14 September 2020 in Falkenberg (Tauche), Germany

description: The data presented here was collected between 01 June and 14 September 2020 in Falkenberg (Tauche), Germany, during the FESST@MOL (Field Experiment on sub-mesoscale spatio-temporal variability at the Meteorological Observatory Lindenberg) 2020 campaign, which was initiated by the Hans-Ertel-Center for Weather Research. The measurements took place at the boundary layer field site (GM) Falkenberg, Germany. The data collected in this campaign were measured by three Doppler Lidars (DL) set-up as a virtual tower (VT) testing five different VT scanning methods, operated by the Karlsruhe Institute of Technology. We tested different step/stare and range-height-indicator (RHI) scanning methods.

NetCDF_to_VirtualTower.R in Version 2 contains the R code used to read in the Lidar data, apply the data filters and calculate the mean horizontal wind speed and wind direction.

Further details on this data set can be found in the attached data documentation.
description: This work has been funded by the German Federal Ministry for Digital and Transport (BMDV) within the framework of the DWD program for extramural research, project: Quality Assessment of ground-based Lidar measurements in the Boundary layer (QALiBo): evaluation and verification of scanning strategies, quality tests and uncertainty quantification / contract number: 4819EMF05.
DOI: 10.15468/dl.drbdgn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"12222643","matchCase":false},{"type":"equals","key":"OCCURRENCE_STATUS","value":"PRESENT","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"HAS_GEOSPATIAL_ISSUE","value":"false","matchCase":false},{"type":"lessThan","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"in","key":"YEAR","values":["2008","2009","2010","2011","2012","2013","2014","2015","2016","2017","2018","2019","2020","2021","2022","2023","2024"],"matchCase":false},{"type":"in","key":"BASIS_OF_RECORD","values":["LIVING_SPECIMEN","HUMAN OBSERVATION","OBSERVATION","OCCURRENCE","MACHINE_OBSERVATION"],"matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023189-241024112534372/datasets/export for details.
DOI: 10.15468/dl.ybe8zp
title: Occurrence Download

description: A dataset containing 232197 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA.21.16_1",
 "Year is 2021"
 ]
}

 The dataset includes 232197 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023127-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9gk34j
title: Occurrence Download

description: A dataset containing 786 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Tribulus pentandrus Forssk."
 ]
}

 The dataset includes 786 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023190-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dbaf9z
title: Occurrence Download

description: A dataset containing 240076 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA.21.16_1",
 "Year is 2022"
 ]
}

 The dataset includes 240076 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023136-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brbua5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"12222994","matchCase":false},{"type":"equals","key":"OCCURRENCE_STATUS","value":"PRESENT","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"HAS_GEOSPATIAL_ISSUE","value":"false","matchCase":false},{"type":"lessThan","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"in","key":"YEAR","values":["2008","2009","2010","2011","2012","2013","2014","2015","2016","2017","2018","2019","2020","2021","2022","2023","2024"],"matchCase":false},{"type":"in","key":"BASIS_OF_RECORD","values":["LIVING_SPECIMEN","HUMAN OBSERVATION","OBSERVATION","OCCURRENCE","MACHINE_OBSERVATION"],"matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023191-241024112534372/datasets/export for details.
DOI: 10.15468/dl.cmrj9a
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"12223055","matchCase":false},{"type":"equals","key":"OCCURRENCE_STATUS","value":"PRESENT","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"HAS_GEOSPATIAL_ISSUE","value":"false","matchCase":false},{"type":"lessThan","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"in","key":"YEAR","values":["2008","2009","2010","2011","2012","2013","2014","2015","2016","2017","2018","2019","2020","2021","2022","2023","2024"],"matchCase":false},{"type":"in","key":"BASIS_OF_RECORD","values":["LIVING_SPECIMEN","HUMAN OBSERVATION","OBSERVATION","OCCURRENCE","MACHINE_OBSERVATION"],"matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023192-241024112534372/datasets/export for details.
DOI: 10.15468/dl.ajvuk6
title: Occurrence Download

description: A dataset containing 24443 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Vicia americana Muhl. ex Willd."
 ]
}

 The dataset includes 24443 records from 269 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023186-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10072864
title: Wind power plants layouts according to arbitrary reference points, Thanet, West of Duddon Sands, Ormonde, Westermost Rough, Horns Rev 1 & 2, Anholt, and London Array

description: If this dataset helps your research, please cite it and the papers further below (according to which OWPP you study).

This dataset contains the layouts of the Thanet, West of Duddon Sands, Ormonde, Westermost Rough, Horns Rev 1 & 2, Anholt, and London Array offshore wind power plants (OWPPs), which can be utilized in a variety of studies. 

The X and Y coordinates, in kilometers, were written according to arbitrary reference points. The positions of wind turbine generators (WTGs) and substations (SS) for the OWPPs came from the sources below.

Thanet: WTGs from [1] (page 7), SS based on [3] (page 9).West of Duddon Sands: WTGs from [2] (page 5), SS based on [3] (page 9).Ormonde: WTGs and SS from [4] (page 2).Westermost Rough:  WTGs and SS from [5] (page 4).Horns Rev 1: WTGs and SS from [6] (page 6).Horns Rev 2: WTGs and SS from [7] (page 5).Anholt: WTGs and SS from [8] (page 3).London Array: WTGs from [9] (page 15), SS based on [10] (page 2).

From the OWPPs' layout figures [1-9], I used Graph Grabber 2.0.2* to extract the data points. Then, based on visual inspection of layouts in [1-9], I utilized 2D projections to align WTGs that should be aligned. References [1], [2], and [9] do not provide the SS positions. Thus, I carefully overlapped the layouts with other layouts from [3] and [10] to approximate the SS locations.

Regarding the arbitrary reference points for the coordinates, although the values in the X and Y axes differ from [1-9], note that the distances among the WTGs are the same from [1-9]. Furthermore, there are no axes in [1,5]. Instead, distances are given, which are enough to obtain the layout. Values in meters were converted to kilometers.

As seen in the attachments, the coordinates can be obtained via either "h5" or "csv" files, which can be easily read by Matlab, Julia, and Python, among others. The name of the datasets in the "h5" file are: "Thanet", "WDS", "Ormonde", "WMR", "HornsRev1", "HornsRev2", "Anholt", and "LondonArray".

Except for the London Array OWPP,  the first row in all data matrices represents the SS coordinates, whereas the subsequent rows represent the WTGs. London Array has 2 substations, thus the first and second rows represent their coordinates. In all matrices, the first and second columns are the X and Y coordinates, respectively.

*Graph Grabber 2.0.2 | Downloads And Demos | Software | Quintessa Limited | Scientific and Mathematical Consultancy
DOI: 10.5281/zenodo.10072865
title: Wind power plants layouts according to arbitrary reference points, Thanet and West of Duddon Sands

description: This dataset contains the layout of the Thanet and West of Duddon Sands (WDS) offshore wind power plants (OWPPs), which can be utilized in a variety of studies. 
The x and y coordinates, in kilometers, were written according to arbitrary reference points. The data in its entirety came from the literature. The positions of the Thanet wind turbine generators (WTGs) came from [1], whereas the ones regarding West of Duddon Sands came from [2]. 
From figures of the OWPPs' layouts, I used Graph Grabber 2.0.2* to extract the data points. Then, based on visual inspection of [1,2], I utilized 2D projection to align WTGs that should be aligned. Neither [1] nor [2] provided the positions of the substations (SS). Thus, I approximated them based on [3]. The resulting layouts can be immediately seen in the png attachment.
Regarding the arbitrary reference points for the coordinates, although the values in the x and y axes differ from [2], note that the distances among the WTGs are the same from [2]. Furthermore, the values in [2] are in meters, so they were converted to kilometers. There were no axes in [1]. Instead, a distance measurement was given, which is enough to obtain the layout.
As seen in the attachments, the coordinates can be obtained either via the h5 file or via the csv files, which can be easily read by Matlab, Julia and Python, among others.
If this dataset is helpful for your research, please be kind to cite not only the dataset itself, but also the papers below, which originally enabled me to create this dataset.
 
*Graph Grabber 2.0.2 | Downloads And Demos | Software | Quintessa Limited | Scientific and Mathematical Consultancy
[1] Pearce, B., Fariñas-Franco, J. M., Wilson, C., Pitts, J., deBurgh, A., & Somerfield, P. J. (2014). Repeated mapping of reefs constructed by Sabellaria spinulosa Leuckart 1849 at an offshore wind farm site. Continental Shelf Research, 83, 3-13. https://doi.org/10.1016/j.csr.2014.02.003
[2] Kallehave, D., Byrne, B. W., LeBlanc Thilsted, C., & Mikkelsen, K. K. (2015). Optimization of monopiles for offshore wind turbines. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2035), 20140100. https://doi.org/10.1098/rsta.2014.0100
[3] Pérez-Rúa, J. A., Stolpe, M., Das, K., & Cutululis, N. A. (2019). Global optimization of offshore wind farm collection systems. IEEE Transactions on Power Systems, 35(3), 2256-2267. https://doi.org/10.1109/TPWRS.2019.2957312
DOI: 10.5281/zenodo.10108262
title: Wind power plants layouts according to arbitrary reference points, Thanet and West of Duddon Sands

description: If this dataset is helpful for your research, please be kind to cite not only the dataset itself, but also the papers further below, which originally enabled me to create this dataset.
This dataset contains the layout of the Thanet and West of Duddon Sands (WDS) offshore wind power plants (OWPPs), which can be utilized in a variety of studies. 
The x and y coordinates, in kilometers, were written according to arbitrary reference points. The data in its entirety came from the literature. The positions of the Thanet wind turbine generators (WTGs) came from [1], whereas the ones regarding West of Duddon Sands came from [2]. 
From figures of the OWPPs' layouts, I used Graph Grabber 2.0.2* to extract the data points. Then, based on visual inspection of [1,2], I utilized 2D projection to align WTGs that should be aligned. Neither [1] nor [2] provided the positions of the substations (SS). Thus, I approximated them based on [3]. The resulting layouts can be immediately seen in the png attachment.
Regarding the arbitrary reference points for the coordinates, although the values in the x and y axes differ from [2], note that the distances among the WTGs are the same from [2]. Furthermore, the values in [2] are in meters, so they were converted to kilometers. There were no axes in [1]. Instead, a distance measurement was given, which is enough to obtain the layout.
As seen in the attachments, the coordinates can be obtained either via the h5 file or via the csv files, which can be easily read by Matlab, Julia and Python, among others.
 
*Graph Grabber 2.0.2 | Downloads And Demos | Software | Quintessa Limited | Scientific and Mathematical Consultancy
[1] Pearce, B., Fariñas-Franco, J. M., Wilson, C., Pitts, J., deBurgh, A., & Somerfield, P. J. (2014). Repeated mapping of reefs constructed by Sabellaria spinulosa Leuckart 1849 at an offshore wind farm site. Continental Shelf Research, 83, 3-13. https://doi.org/10.1016/j.csr.2014.02.003
[2] Kallehave, D., Byrne, B. W., LeBlanc Thilsted, C., & Mikkelsen, K. K. (2015). Optimization of monopiles for offshore wind turbines. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2035), 20140100. https://doi.org/10.1098/rsta.2014.0100
[3] Pérez-Rúa, J. A., Stolpe, M., Das, K., & Cutululis, N. A. (2019). Global optimization of offshore wind farm collection systems. IEEE Transactions on Power Systems, 35(3), 2256-2267. https://doi.org/10.1109/TPWRS.2019.2957312
DOI: 10.5281/zenodo.10108274
title: Wind power plants layouts according to arbitrary reference points, Thanet and West of Duddon Sands

description: If this dataset is helpful for your research, please be kind to cite not only the dataset itself, but also the papers further below, which originally enabled me to create this dataset.
This dataset contains the layout of the Thanet and West of Duddon Sands (WDS) offshore wind power plants (OWPPs), which can be utilized in a variety of studies. 
The x and y coordinates, in kilometers, were written according to arbitrary reference points. The data in its entirety came from the literature. The positions of the Thanet wind turbine generators (WTGs) came from [1], whereas the ones regarding West of Duddon Sands came from [2]. 
From figures of the OWPPs' layouts, I used Graph Grabber 2.0.2* to extract the data points. Then, based on visual inspection of [1,2], I utilized 2D projection to align WTGs that should be aligned. Neither [1] nor [2] provided the positions of the substations (SS). Thus, I approximated them based on [3]. The resulting layouts can be immediately seen in the png attachment.
Regarding the arbitrary reference points for the coordinates, although the values in the x and y axes differ from [2], note that the distances among the WTGs are the same from [2]. Furthermore, the values in [2] are in meters, so they were converted to kilometers. There were no axes in [1]. Instead, a distance measurement was given, which is enough to obtain the layout.
As seen in the attachments, the coordinates can be obtained either via the h5 file or via the csv files, which can be easily read by Matlab, Julia and Python, among others.
 
*Graph Grabber 2.0.2 | Downloads And Demos | Software | Quintessa Limited | Scientific and Mathematical Consultancy
[1] Pearce, B., Fariñas-Franco, J. M., Wilson, C., Pitts, J., deBurgh, A., & Somerfield, P. J. (2014). Repeated mapping of reefs constructed by Sabellaria spinulosa Leuckart 1849 at an offshore wind farm site. Continental Shelf Research, 83, 3-13. https://doi.org/10.1016/j.csr.2014.02.003
[2] Kallehave, D., Byrne, B. W., LeBlanc Thilsted, C., & Mikkelsen, K. K. (2015). Optimization of monopiles for offshore wind turbines. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2035), 20140100. https://doi.org/10.1098/rsta.2014.0100
[3] Pérez-Rúa, J. A., Stolpe, M., Das, K., & Cutululis, N. A. (2019). Global optimization of offshore wind farm collection systems. IEEE Transactions on Power Systems, 35(3), 2256-2267. https://doi.org/10.1109/TPWRS.2019.2957312