cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13120/c8a7655e-b66f-11ef-2e96-cfbed2f49f87
title: European seas - DIVAnd 4D monthly analysis of Water_body_dissolved_inorganic_nitrogen 1960/2023 v2024
title: All Europeans Seas-Water body dissolved inorganic nitrogen (DIN)-v2024-ANA

description: Water_body_dissolved_inorganic_nitrogen - Monthly Climatology for the European Seas for the period 1960-2023 on the domain from longitude -45.0 to 70.0 degrees East and latitude 24.0 to 83.0 degrees North.
Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network.
Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length and vertical correlation length vary spatially depending on the topography and domain.
Depth range: 0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 125.0, 150.0, 175.0, 200.0, 225.0, 250.0, 275.0, 300.0, 325.0, 350.0, 375.0, 400.0, 425.0, 450.0, 475.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0, 1050.0, 1100.0, 1150.0, 1200.0, 1250.0, 1300.0, 1350.0, 1400.0, 1450.0, 1500.0, 1550.0, 1600.0, 1650.0, 1700.0, 1750.0, 1800.0, 1850.0, 1900.0, 1950.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0, 2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0, 3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0, 4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0, 5500.0 m.
Units: umol/l.
The horizontal resolution of the produced DIVAnd analysis is 0.25 degrees.
DOI: 10.48597/7ps7-kz2t
title: Measurement of OC/EC at Birkenes II

description: Measurement of OC/EC at Birkenes II
DOI: 10.15468/dl.5hvacz
title: Occurrence Download

description: A dataset containing 1288 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "OccurrenceStatus is Present",
 "TaxonKey is Michelia champaca L."
 ]
}

 The dataset includes 1288 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004711-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6g6ht7
title: Occurrence Download

description: A dataset containing 3093 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Felis chaus Schreber, 1777"
 ]
}

 The dataset includes 3093 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004712-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13936031
title: Datenanalyse zu aus DOAJ entfernten Zeitschriften

description: Dieser Datensatz wurde erstellt, um die Gründe für die Entfernung von Open-Access-Zeitschriften aus dem DOAJ (Directory of Open Access Journals) zu untersuchen. Insgesamt wurden 5.921 Entfernungen von Zeitschriften aus DOAJ in den Changelogs von DOAJ registriert. 

 

Beschreibung der Datensets

Datenformate



JSON: Das vollständige Datenset liegt im JSON-Format vor, das alle verfügbaren Felder aus OpenAlex enthält.

CSV und Excel: Ausgewählte Felder aus dem JSON-Datensatz sind zusätzlich im CSV- und Excel-Format verfügbar.


Bezeichnungen der Dateien

Es gibt insgesamt 9 Datensätze, unterteilt in 3 verschiedene Versionen, die jeweils in 3 Formaten (JSON, CSV, Excel) verfügbar sind:



DOAJ_journals_Removed_updated_14_24:   Diese Datei enthält die Rohdaten, die aus Google Sheets exportiert und mit OpenAlex-Daten angereichert wurden.

DOAJ_journals_Removed_updated_publisher_14_24:   Diese Datei enthält die angereicherten Datensätze, wobei die Verlage vereinheitlicht wurden.

DOAJ_journals_Removed_updated_publisher_deu_24:   Diese Datei enthält die angereicherten Datensätze, in denen die Verlage vereinheitlicht und die Gründe ins Deutsche übersetzt sowie konsolidiert wurden.


 

----------

Tipp/Hinweis zur Bearbeitung in Excel: Die Datumsangabe muss ggf. in ein als Datum lesbares Format geändert werden. Dazu die Daten markieren > "Text in Spalten" auswählen > als "Getrennt" markieren und "Weiter" drücken > Trennzeichen ignorieren und "Weiter" drücken > Format Datum auswählen. Fertig.
DOI: 10.5281/zenodo.13936032
title: Datenanalyse zu aus DOAJ entfernten Zeitschriften

description: Dieser Datensatz wurde erstellt, um die Gründe für die Entfernung von Open-Access-Zeitschriften aus dem DOAJ (Directory of Open Access Journals) zu untersuchen. Insgesamt wurden 5.921 Entfernungen von Zeitschriften aus DOAJ in den Changelogs von DOAJ registriert. 

 

Beschreibung der Datensets

Datenformate



JSON: Das vollständige Datenset liegt im JSON-Format vor, das alle verfügbaren Felder aus OpenAlex enthält.

CSV und Excel: Ausgewählte Felder aus dem JSON-Datensatz sind zusätzlich im CSV- und Excel-Format verfügbar.


Bezeichnungen der Dateien

Es gibt insgesamt 9 Datensätze, unterteilt in 3 verschiedene Versionen, die jeweils in 3 Formaten (JSON, CSV, Excel) verfügbar sind:



DOAJ_journals_Removed_updated_14_24:   Diese Datei enthält die Rohdaten, die aus Google Sheets exportiert und mit OpenAlex-Daten angereichert wurden.

DOAJ_journals_Removed_updated_publisher_14_24:   Diese Datei enthält die angereicherten Datensätze, wobei die Verlage vereinheitlicht wurden.

DOAJ_journals_Removed_updated_publisher_deu_24:   Diese Datei enthält die angereicherten Datensätze, in denen die Verlage vereinheitlicht und die Gründe ins Deutsche übersetzt sowie konsolidiert wurden.


 

----------

Tipp/Hinweis zur Bearbeitung in Excel: Die Datumsangabe muss ggf. in ein als Datum lesbares Format geändert werden. Dazu die Daten markieren > "Text in Spalten" auswählen > als "Getrennt" markieren und "Weiter" drücken > Trennzeichen ignorieren und "Weiter" drücken > Format Datum auswählen. Fertig.
DOI: 10.34740/kaggle/dsv/10592199
title: World Stock Prices ( Daily Updating )
DOI: 10.5281/zenodo.13643192
title: Raw NanoLuc and NanoBiT Data from "Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay"

description: This dataset includes raw NanoLuc and NanoBiT data supporting the manuscript titled 'Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay'.
DOI: 10.5281/zenodo.13643193
title: Raw NanoLuc and NanoBiT Data from "Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay"

description: This dataset includes raw NanoLuc and NanoBiT data supporting the manuscript titled 'Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay'.
DOI: 10.5281/zenodo.13902134
title: Analyzed NanoBiT Data from "Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay"

description: This dataset includes analyzed NanoBiT data supporting the manuscript titled 'Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay'.
DOI: 10.15468/dl.5947mf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aulopus elongatus Temminck & Schlegel, 1846",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004714-250123221155621/datasets/export for details.
DOI: 10.13120/b08cc3e2-b66f-11ef-0ef9-a3ec3d589a85
title: European seas - DIVAnd 4D monthly analysis of Water_body_ammonium 1960/2023 v2024
title: All Europeans Seas-Water body ammonium-v2024-ANA

description: Water_body_ammonium - Monthly Climatology for the European Seas for the period 1960-2023 on the domain from longitude -45.0 to 70.0 degrees East and latitude 24.0 to 83.0 degrees North.
Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network.
Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length and vertical correlation length vary spatially depending on the topography and domain.
Depth range: 0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 125.0, 150.0, 175.0, 200.0, 225.0, 250.0, 275.0, 300.0, 325.0, 350.0, 375.0, 400.0, 425.0, 450.0, 475.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0, 1050.0, 1100.0, 1150.0, 1200.0, 1250.0, 1300.0, 1350.0, 1400.0, 1450.0, 1500.0, 1550.0, 1600.0, 1650.0, 1700.0, 1750.0, 1800.0, 1850.0, 1900.0, 1950.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0, 2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0, 3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0, 4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0, 5500.0 m.
Units: umol/l.
The horizontal resolution of the produced DIVAnd analysis is 0.25 degrees.
DOI: 10.13120/120904a4-b644-11ef-23a9-674757d36073
title: European seas - DIVAnd 4D monthly analysis of Water_body_phosphate 1960/2023 v2024
title: All Europeans Seas-Water body phosphate-v2024-ANA

description: Water_body_phosphate - Monthly Climatology for the European Seas for the period 1960-2023 on the domain from longitude -45.0 to 70.0 degrees East and latitude 24.0 to 83.0 degrees North.
Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network.
Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length and vertical correlation length vary spatially depending on the topography and domain.
Depth range: 0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 125.0, 150.0, 175.0, 200.0, 225.0, 250.0, 275.0, 300.0, 325.0, 350.0, 375.0, 400.0, 425.0, 450.0, 475.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0, 1050.0, 1100.0, 1150.0, 1200.0, 1250.0, 1300.0, 1350.0, 1400.0, 1450.0, 1500.0, 1550.0, 1600.0, 1650.0, 1700.0, 1750.0, 1800.0, 1850.0, 1900.0, 1950.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0, 2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0, 3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0, 4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0, 5500.0 m.
Units: umol/l.
The horizontal resolution of the produced DIVAnd analysis is 0.25 degrees.
DOI: 10.13120/557c54be-b637-11ef-20ed-ad91bff5fe19
title: European seas - DIVAnd 4D monthly analysis of Water_body_silicate 1960/2023 v2024
title: All Europeans Seas-Water body silicate-v2024-ANA

description: Water_body_silicate - Monthly Climatology for the European Seas for the period 1960-2023 on the domain from longitude -45.0 to 70.0 degrees East and latitude 24.0 to 83.0 degrees North.
Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network.
Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length and vertical correlation length vary spatially depending on the topography and domain.
Depth range: 0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 125.0, 150.0, 175.0, 200.0, 225.0, 250.0, 275.0, 300.0, 325.0, 350.0, 375.0, 400.0, 425.0, 450.0, 475.0, 500.0, 550.0, 600.0, 650.0, 700.0, 750.0, 800.0, 850.0, 900.0, 950.0, 1000.0, 1050.0, 1100.0, 1150.0, 1200.0, 1250.0, 1300.0, 1350.0, 1400.0, 1450.0, 1500.0, 1550.0, 1600.0, 1650.0, 1700.0, 1750.0, 1800.0, 1850.0, 1900.0, 1950.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0, 2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0, 3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0, 4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0, 5500.0 m.
Units: umol/l.
The horizontal resolution of the produced DIVAnd analysis is 0.25 degrees.
DOI: 10.5281/zenodo.14747468
title: Raw data underlying the results presented in a manuscript, entitled: Multiplexed near-IR detection of single-molecule fluorescence fluctuations using a single superconducting nanowire single photon detector.

description: This folder contains all raw data underlying the results presented in a manuscript, entitled:

Multiplexed near-IR detection of single-molecule fluorescence fluctuations using a single superconducting nanowire single photon detector

Authored by:

Abhilash Kulkarni 1, Niusha Bagheri 1, Jerker Widengren 1,*

1 Royal Institute of Technology (KTH), Experimental Biomolecular Physics, Dept. Applied Physics, Albanova University Center 106 91 Stockholm, Sweden

* Corresponding author (jwideng@kth.se)

 

The data files are grouped into the different techniques used to generate them and refer to the figures/tables in the manuscript where the extracted results are presented. 

 

ABSTRACT:

Fluorescence-based single-molecule and fluctuation spectroscopy in the near-IR can open for biomolecular dynamic studies in biological media, with suppressed autofluorescence and scattering background. However, further implementation is limited by the lower brightness of NIR fluorophores, and available single-photon detector technologies that are still to be explored and adapted. Superconducting Nanowire Single Photon Detectors (snSPDs) have found increasing use in quantum optics and optical communication applications, much thanks to high sensitivity in the near-IR (NIR), low dark-counts, no after-pulsing, and high time resolution. Here, we present characterization of fluorescence intensity fluctuations from single vesicles and NIR fluorophores, based on fluorescence correlation spectroscopy (FCS), specifically taking advantage of these snSPD properties. We present a concept allowing multiplexed readouts based on only one snSPD, in which the emitted photons are separated by their emission wavelength into different optical paths, thereby translating the emission wavelengths into different arrival times onto the snSPD. This concept allows one-laser-one-detector, dual-color fluorescence cross-correlation spectroscopy (FCCS) measurements, with fluorescence intensity fluctuations of two fluorophore species separately analysed, and cross-correlated. It is shown how two fluorophore species in a sample can be distinguished by their different blinking kinetics, fluorescence lifetimes and/or diffusion properties. Apart from differences in emission spectra, the presented concept for multiplexing using a single detector can also be applied to distinguish emitters by properties such as polarization, coherence lengths, and fluorescence bunching and anti-bunching signatures. It can also be generalized to other modalities than FCS, including single-molecule detection, confocal microscopy and imaging.

ACKNOWLEDGMENTS

This work was supported by the Knut and Alice Wallenberg Foundation via Wallenberg Center for Quantum Technology (WACQT), and the Swedish Foundation for Strategic Research (SSF, ITM17-0491, BENVAC RMX18-0041).
DOI: 10.5281/zenodo.14747469
title: Raw data underlying the results presented in a manuscript, entitled: Multiplexed near-IR detection of single-molecule fluorescence fluctuations using a single superconducting nanowire single photon detector.

description: This folder contains all raw data underlying the results presented in a manuscript, entitled:

Multiplexed near-IR detection of single-molecule fluorescence fluctuations using a single superconducting nanowire single photon detector

Authored by:

Abhilash Kulkarni 1, Niusha Bagheri 1, Jerker Widengren 1,*

1 Royal Institute of Technology (KTH), Experimental Biomolecular Physics, Dept. Applied Physics, Albanova University Center 106 91 Stockholm, Sweden

* Corresponding author (jwideng@kth.se)

 

The data files are grouped into the different techniques used to generate them and refer to the figures/tables in the manuscript where the extracted results are presented. 

 

ABSTRACT:

Fluorescence-based single-molecule and fluctuation spectroscopy in the near-IR can open for biomolecular dynamic studies in biological media, with suppressed autofluorescence and scattering background. However, further implementation is limited by the lower brightness of NIR fluorophores, and available single-photon detector technologies that are still to be explored and adapted. Superconducting Nanowire Single Photon Detectors (snSPDs) have found increasing use in quantum optics and optical communication applications, much thanks to high sensitivity in the near-IR (NIR), low dark-counts, no after-pulsing, and high time resolution. Here, we present characterization of fluorescence intensity fluctuations from single vesicles and NIR fluorophores, based on fluorescence correlation spectroscopy (FCS), specifically taking advantage of these snSPD properties. We present a concept allowing multiplexed readouts based on only one snSPD, in which the emitted photons are separated by their emission wavelength into different optical paths, thereby translating the emission wavelengths into different arrival times onto the snSPD. This concept allows one-laser-one-detector, dual-color fluorescence cross-correlation spectroscopy (FCCS) measurements, with fluorescence intensity fluctuations of two fluorophore species separately analysed, and cross-correlated. It is shown how two fluorophore species in a sample can be distinguished by their different blinking kinetics, fluorescence lifetimes and/or diffusion properties. Apart from differences in emission spectra, the presented concept for multiplexing using a single detector can also be applied to distinguish emitters by properties such as polarization, coherence lengths, and fluorescence bunching and anti-bunching signatures. It can also be generalized to other modalities than FCS, including single-molecule detection, confocal microscopy and imaging.

ACKNOWLEDGMENTS

This work was supported by the Knut and Alice Wallenberg Foundation via Wallenberg Center for Quantum Technology (WACQT), and the Swedish Foundation for Strategic Research (SSF, ITM17-0491, BENVAC RMX18-0041).
DOI: 10.15468/dl.6ux8pp
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Squalus japonicus Ishikawa, 1908",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 64 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004716-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14701759
title: Submerged Aquatic Vegetation (SAV)

description: Algorithm description

This is a prototype product for a new Copernicus Service element which is being developed in the course of FOCCUS.  The algorithm computes the presence/absence of submerged aquatic vegetation (SAV; seagrass and macroalgae) in subtidal regions of the Balearic Islands based on temporally aggregated Sentinel-2 imagery and EMODNET bathymetry. Sentinel-2 data are atmospherically corrected using ACOLITE and water pixels are identified using IdePix. Images are processed and aggregated using the Copernicus Data Space Ecosystem. Aggregate images are classified as SAV (0) or non-SAV (1) using machine learning methods. Results are clipped to water depths shallower than 25 m and cleaned up using a 3x3 pixel median filter.

Limitations

Data availability depends on the number of usable observations (clouds, water clarity, glint) and may therefore vary spatially and temporally. The quality of the products depends on proper flagging by IdePix classification and other masks applied. The algorithm does not differentiate between different types of submerged aquatic vegetation (e.g., macroalgae or seagrass) and does not consider vegetation health. A known issue is are misclassifications of optically deep water in some areas.
DOI: 10.5281/zenodo.14701760
title: Submerged Aquatic Vegetation (SAV)

description: Algorithm description

This is a prototype product for a new Copernicus Service element which is being developed in the course of FOCCUS.  The algorithm computes the presence/absence of submerged aquatic vegetation (SAV; seagrass and macroalgae) in subtidal regions of the Balearic Islands based on temporally aggregated Sentinel-2 imagery and EMODNET bathymetry. Sentinel-2 data are atmospherically corrected using ACOLITE and water pixels are identified using IdePix. Images are processed and aggregated using the Copernicus Data Space Ecosystem. Aggregate images are classified as SAV (0) or non-SAV (1) using machine learning methods. Results are clipped to water depths shallower than 25 m and cleaned up using a 3x3 pixel median filter.

Limitations

Data availability depends on the number of usable observations (clouds, water clarity, glint) and may therefore vary spatially and temporally. The quality of the products depends on proper flagging by IdePix classification and other masks applied. The algorithm does not differentiate between different types of submerged aquatic vegetation (e.g., macroalgae or seagrass) and does not consider vegetation health. A known issue is are misclassifications of optically deep water in some areas.
DOI: 10.12757/bbk.bophh.202501
title: Bundesbank-Online-Panel-Households (BOP-HH)

description: The BOP-HH Scientific Use File 202501 Version 01 data set continues the BOPSOCE Scientific Use File Version 1.0. It consists of the Stata files bophh_suf_202501_v01_wave01.dta to bophh_suf_202501_v01_wave60.dta. For more details, see the BOP-HH documentation on the website of the Deutsche Bundesbank.
DOI: 10.6084/m9.figshare.28283072.v1
title: Supplemental Tables S1-S2

description: Supplemental Table S1 describes cardiovascular variables before and after the intervention, and Supplemental Table S2 describes cardiovascular variables during FMD test.
DOI: 10.15468/dl.yxnpbh
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myoxocephalus polyacanthocephalus (Pallas, 1814)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 35 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004717-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrnqxs
title: Occurrence Download

description: A dataset containing 1189817 species occurrences available in GBIF matching the query:
{
 "NetworkKey" : [
 "is 3aee7756-565e-4dc5-b22c-f997fbd7105c"
 ]
}

 The dataset includes 1189817 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004709-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14747463
title: Morphological Analysis and Geological Evolution of Pitted Cones in Isidis Planitia: Insights into Martian Mud Volcanism

description: This dataset serves as the supporting data for the manuscript "Morphological Analysis and Geological Evolution of Pitted Cones in Isidis Planitia: Insights into Martian Mud Volcanism". The dataset includes an Excel file that contains the morphological measurement results of the pitted cones in Isidis Planitia.