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

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Zimbabwe",
 "TaxonKey is Spodoptera exempta"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007236-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9m7as2
title: Occurrence Download

description: A dataset containing 1683 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Nylanderia bourbonica"
 ]
}

 The dataset includes 1683 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007235-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qw3nz4
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Holothuria moebii",
 "Year 1000-2026"
 ]
}

 The dataset includes 17 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007234-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ynsnvb
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.15253 42.7434,2.0632 42.68502,2.11056 42.61116,2.28152 42.57588,2.35748 42.63988,2.34482 42.74445,2.24869 42.7557,2.19008 42.74515,2.15253 42.7434))",
 "TaxonKey is Lagopus muta"
 ]
}

 The dataset includes 12 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007237-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25405/data.ncl.26062555
title: Household Survey Data from Ganges Brahmaputra Meghna (GBM) delta (India)

description: The Indian Sundarbans are under tremendous pressure from both climate change and anthropogenic activities, where recurring natural disasters are impacting the lives and livelihoods of the local population. The Sundarbans ecosystem and forest-based livelihoods of the adjacent delta dwellers are in discreet balance, and disrupting the delicate balance between nature and human habitation could pose a serious threat to the socioeconomic structure of the region. Understanding the complex delta-dynamics is crucial for developing conservation policies, so the Living Delta Research Hub has undertaken a major project to apprehend the issues and subsequent changes observed in the coastal regions of the GBM-India delta. The four community development blocks, Sagar, Sandeshkhali-I, Gosaba, and Hingalganj, were chosen for this research as they are situated in the coastal stretch of Indian Sundarbans. To perceive the main challenges faced by the marginal community in terms of lives and livelihoods, the key objective of this project is to organize a thorough household survey, which will provide the foundation of this comprehensive analysis. These four blocks will represent the broader GBM delta and will help to recognize the diverse challenges faced by the coastal community. The Living Delta Research Hub aspires to obtain detailed information from the surveys, which will help the stakeholders and policymakers to make informed decisions aimed at promoting a sustainable society and increasing resilience. The detailed information gathered via a household survey will curate the right path towards mitigation and adaptation strategies in GBM Delta, India. Therefore, the household survey is not only a means of collecting data for this research but also a strategic requirement to recognize the distribution and magnitude of the problems encountered daily by the local population. Identifying the intricate interactions of physical, social, and economic parameters pertaining to the coastal regions of the Sundarbans is essential for a viable sustainable policy which will also help build a resilient community. This meticulous examination is crucial for developing a holistic understanding of the challenges faced by the communities in Sagar Island, Sandeshkhali-I, Gosaba, and Hingalganj. By identifying and analyzing the risks, the Living Delta Research Hub aspires to contribute valuable insights that can inform targeted measures for adaptation, thereby fostering resilience and ensuring the sustainable development of these vulnerable coastal regions within the Sundarbans.In the year 2022, a comprehensive cross-sectional study was undertaken, employing a robust methodology to gather data from the diverse landscape of the GBM-I delta. This involved the administration of a semi-structured questionnaire to a substantial cohort of over 1200 adult respondents.<br>
DOI: 10.25405/data.ncl.26062555.v1
title: Household Survey Data from Ganges Brahmaputra Meghna (GBM) delta (India)

description: The Indian Sundarbans are under tremendous pressure from both climate change and anthropogenic activities, where recurring natural disasters are impacting the lives and livelihoods of the local population. The Sundarbans ecosystem and forest-based livelihoods of the adjacent delta dwellers are in discreet balance, and disrupting the delicate balance between nature and human habitation could pose a serious threat to the socioeconomic structure of the region. Understanding the complex delta-dynamics is crucial for developing conservation policies, so the Living Delta Research Hub has undertaken a major project to apprehend the issues and subsequent changes observed in the coastal regions of the GBM-India delta. The four community development blocks, Sagar, Sandeshkhali-I, Gosaba, and Hingalganj, were chosen for this research as they are situated in the coastal stretch of Indian Sundarbans. To perceive the main challenges faced by the marginal community in terms of lives and livelihoods, the key objective of this project is to organize a thorough household survey, which will provide the foundation of this comprehensive analysis. These four blocks will represent the broader GBM delta and will help to recognize the diverse challenges faced by the coastal community. The Living Delta Research Hub aspires to obtain detailed information from the surveys, which will help the stakeholders and policymakers to make informed decisions aimed at promoting a sustainable society and increasing resilience. The detailed information gathered via a household survey will curate the right path towards mitigation and adaptation strategies in GBM Delta, India. Therefore, the household survey is not only a means of collecting data for this research but also a strategic requirement to recognize the distribution and magnitude of the problems encountered daily by the local population. Identifying the intricate interactions of physical, social, and economic parameters pertaining to the coastal regions of the Sundarbans is essential for a viable sustainable policy which will also help build a resilient community. This meticulous examination is crucial for developing a holistic understanding of the challenges faced by the communities in Sagar Island, Sandeshkhali-I, Gosaba, and Hingalganj. By identifying and analyzing the risks, the Living Delta Research Hub aspires to contribute valuable insights that can inform targeted measures for adaptation, thereby fostering resilience and ensuring the sustainable development of these vulnerable coastal regions within the Sundarbans.In the year 2022, a comprehensive cross-sectional study was undertaken, employing a robust methodology to gather data from the diverse landscape of the GBM-I delta. This involved the administration of a semi-structured questionnaire to a substantial cohort of over 1200 adult respondents.<br>
DOI: 10.25405/data.ncl.26097049
title: Calculating wave orbital velocity from Acoustic Doppler Velocimeter data

description: This dataset was used to derive near-bottom wave orbital velocities using two methods: linear wave theory and direct velocity measurements. Both methods were then used to compare calibrations between velocity and acceleration data gathered by low-cost and open-source bottom-mounted floats called ‘Mini Buoys’. The dataset contains water velocity data gathered by Acoustic Doppler Velocimeters, and acceleration data gathered from the B4+ Mini Buoy design.<b>Data collection method:</b> Data to build a calibration between wave orbital velocity and acceleration was gathered at Caerlaverock, Scotland (54°58′05′′ N, 3°31′58′′ W) and Black Scar, Wales (51°45′54′′ N, 4°26′12′′ W).<i>Acceleration</i>B4+ Mini Buoys sampled y-axis acceleration at 1 Hz within 5 m of an ADV.<i>Velocity</i>Wave orbital velocities were measured using an ADV. Height of the ADV pressure sensor and velocity cell being measured above the bed at Black Scar was 4 and 30 cm respectively. For the ADV deployed at Caerlaverock, the pressure sensor and velocity cell were 9 and 32 cm above the tidal flat respectively. Velocities were recorded at a rate of 16 Hz in 13-minute bursts every 30 minutes at Black Scar and 1Hz frequency in 20-minute bursts every 1 hour at Caerlaverock. Nominal velocity range was set to 0.3 m/s and ‘Surf Zone’ default settings were used.<b>Data processing:</b> <i>Acceleration</i>No processing was done to the acceleration data.<br><i>Velocity</i>Mean beam correlation of all three receiver arms was calculated.
DOI: 10.25405/data.ncl.26097049.v1
title: Calculating wave orbital velocity from Acoustic Doppler Velocimeter data

description: This dataset was used to derive near-bottom wave orbital velocities using two methods: linear wave theory and direct velocity measurements. Both methods were then used to compare calibrations between velocity and acceleration data gathered by low-cost and open-source bottom-mounted floats called ‘Mini Buoys’. The dataset contains water velocity data gathered by Acoustic Doppler Velocimeters, and acceleration data gathered from the B4+ Mini Buoy design.<b>Data collection method:</b> Data to build a calibration between wave orbital velocity and acceleration was gathered at Caerlaverock, Scotland (54°58′05′′ N, 3°31′58′′ W) and Black Scar, Wales (51°45′54′′ N, 4°26′12′′ W).<i>Acceleration</i>B4+ Mini Buoys sampled y-axis acceleration at 1 Hz within 5 m of an ADV.<i>Velocity</i>Wave orbital velocities were measured using an ADV. Height of the ADV pressure sensor and velocity cell being measured above the bed at Black Scar was 4 and 30 cm respectively. For the ADV deployed at Caerlaverock, the pressure sensor and velocity cell were 9 and 32 cm above the tidal flat respectively. Velocities were recorded at a rate of 16 Hz in 13-minute bursts every 30 minutes at Black Scar and 1Hz frequency in 20-minute bursts every 1 hour at Caerlaverock. Nominal velocity range was set to 0.3 m/s and ‘Surf Zone’ default settings were used.<b>Data processing:</b> <i>Acceleration</i>No processing was done to the acceleration data.<br><i>Velocity</i>Mean beam correlation of all three receiver arms was calculated.
DOI: 10.15468/dl.7rybue
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pristidactylus alvaroi"
 ]
}

 The dataset includes 21 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007240-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z8dzhh
title: Occurrence Download

description: A dataset containing 99 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Mexico",
 "TaxonKey is Crotalus morulus",
 "Year 1960-2026"
 ]
}

 The dataset includes 99 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007241-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17182/hepdata.167818.v1/t1
title: "Efficiencies of $B^- \to D^{+} \mu^- \mu^-$ channel" of "Search for lepton-number-violating $B^-\to D^{(*)+}μ^-μ^-$ decays"

description: Binned efficiencies across the Dalitz plane for $B^- \to D^{+} \mu^- \mu^-$ decay. Here $\mu_1^-$ and $\mu_2^-$ represent the two muons produced in the decay, and the index specifies their ordering in transverse momentum. Efficiencies are normalized to the average over the full simulated sample.
description: The lepton-number-violating $B^- \to D^{(*)+} \mu^- \mu^-$ decays are searched in this analysis. 
No excessive signal is observed, and upper limits of their branching fractions are measured 
at a proton-proton centre-of-mass energy $\sqrt{s} = 13\,\mathrm{TeV}$.

Signal yields are normalized to the normalization channel $B^-\to \psi(\mathrm{2S}) K^-$, and 
efficiency corrections are applied in the normalized based on Monte Carlo simulation. 
The standard deviation of efficiencies arocess Dalitz plane is considered as the major
systematic uncertainty in the efficiency correction.

The efficiencies in each bin are provided in this HepData entry.
DOI: 10.17182/hepdata.167818.v1/t2
title: "Efficiencies of $B^- \to D^{*+} \mu^- \mu^-$ channel" of "Search for lepton-number-violating $B^-\to D^{(*)+}μ^-μ^-$ decays"

description: Binned efficiencies across the Dalitz plane for $B^- \to D^{*+} \mu^- \mu^-$ decay. Here $\mu_1^-$ and $\mu_2^-$ represent the two muons produced in the decay, and the index specifies their ordering in transverse momentum. Efficiencies are normalized to the average over the full simulated sample.
description: The lepton-number-violating $B^- \to D^{(*)+} \mu^- \mu^-$ decays are searched in this analysis. 
No excessive signal is observed, and upper limits of their branching fractions are measured 
at a proton-proton centre-of-mass energy $\sqrt{s} = 13\,\mathrm{TeV}$.

Signal yields are normalized to the normalization channel $B^-\to \psi(\mathrm{2S}) K^-$, and 
efficiency corrections are applied in the normalized based on Monte Carlo simulation. 
The standard deviation of efficiencies arocess Dalitz plane is considered as the major
systematic uncertainty in the efficiency correction.

The efficiencies in each bin are provided in this HepData entry.
DOI: 10.15468/dl.45cx3t
title: Occurrence Download

description: A dataset containing 3510 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Rhypophila decipiens, Schizothecium conicum, Schizothecium glutinans, Schizothecium hispidulum, Schizothecium miniglutinans, Schizothecium tetrasporum, Sordaria humana, Triangularia setosa, Tympanopsis confertula, Zygospermella insignis)"
 ]
}

 The dataset includes 3510 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007238-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17909/ch30-7y40
title: TESS observations of ZTF-CBO-1
DOI: 10.25405/data.ncl.26275057
title: Hydrodynamics at the interface between expanding and eroding mangrove forests in the Indian GBM delta

description: This dataset contains acceleration data measured from low-cost and open-source bottom-mounted floats called ‘Mini Buoys’, to identify hydrological tipping points between expanding and eroding mangrove edges in the Indian GBM delta.<b>Data collection method:</b> Data to assess the hydrological tipping point between expanding and eroding mangrove edges was gathered at western (21°38′53″N, 088°18′45″E) and eastern (21°40′05″N, 088°20′44″E) Lothian island, Indian GBM delta. B4+ Mini Buoys were deployed along seaward mangrove edges where there was a transition from expansion to erosion. Each logger sampled y-axis acceleration at 1 Hz. Coordinates showing the location of each Mini Buoy deployment are expressed in WGS84 standard. No processing was done to acceleration dataData was collected between: 15/12/2021 and 08/01/2022Published resources related to this data set:https://livingdeltas.org/blog/mini-buoys-in-the-indian-sundarban-a-story-of-challenges-collaboration-and-commitmenthttps://livingdeltas.org/publications/monitoring-tidal-hydrology-in-coastal-wetlands-with-the-mini-buoy-applications-for-mangrove-restorationhttps://livingdeltas.org/publications/the-mini-buoy-a-novel-hydrodynamics-sensor-for-long-term-deployments-in-coastal-wetlandshttps://livingdeltas.org/blog/inexpensive-amp-open-source-sensors-could-dramatically-improve-the-success-of-mangrove-plantation-schemeshttps://livingdeltas.org/resources/hydrodynamics-survey-along-embankments-of-kumirmari-island-gosaba-indian-sundarban<br>
DOI: 10.25405/data.ncl.26275057.v1
title: Hydrodynamics at the interface between expanding and eroding mangrove forests in the Indian GBM delta

description: This dataset contains acceleration data measured from low-cost and open-source bottom-mounted floats called ‘Mini Buoys’, to identify hydrological tipping points between expanding and eroding mangrove edges in the Indian GBM delta.<b>Data collection method:</b> Data to assess the hydrological tipping point between expanding and eroding mangrove edges was gathered at western (21°38′53″N, 088°18′45″E) and eastern (21°40′05″N, 088°20′44″E) Lothian island, Indian GBM delta. B4+ Mini Buoys were deployed along seaward mangrove edges where there was a transition from expansion to erosion. Each logger sampled y-axis acceleration at 1 Hz. Coordinates showing the location of each Mini Buoy deployment are expressed in WGS84 standard. No processing was done to acceleration dataData was collected between: 15/12/2021 and 08/01/2022Published resources related to this data set:https://livingdeltas.org/blog/mini-buoys-in-the-indian-sundarban-a-story-of-challenges-collaboration-and-commitmenthttps://livingdeltas.org/publications/monitoring-tidal-hydrology-in-coastal-wetlands-with-the-mini-buoy-applications-for-mangrove-restorationhttps://livingdeltas.org/publications/the-mini-buoy-a-novel-hydrodynamics-sensor-for-long-term-deployments-in-coastal-wetlandshttps://livingdeltas.org/blog/inexpensive-amp-open-source-sensors-could-dramatically-improve-the-success-of-mangrove-plantation-schemeshttps://livingdeltas.org/resources/hydrodynamics-survey-along-embankments-of-kumirmari-island-gosaba-indian-sundarban<br>
DOI: 10.15468/dl.jbetej
title: Occurrence Download

description: A dataset containing 2872905342 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quadrulella, Penardochlamys, Nebela, Multicilia, Erpobdella, Theromyzon, Haemadipsa, Haemopis, Alma, Eiseniella, Animalia, Dero, Tubificoides, Barbronia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2872905342 records from 55930 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006998-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15047873
title: Seismic Events in an Industrial Corridor of the Chicago Area

description: Dataset of 1262 seismic events recorded by seismic station NW.HQIL (Chicago area) between June 2017 and June 2019. Events were detected by a PSD misfit detector applied to overlapping (50%) 10-s windows of HQIL  waveforms. Detected events were then clustered using a k-means clustering model. The clustering results were used to create this labeled datset.

Dataset .zip file contains miniSEED files of 3-component, 20-s seismograms of each labeled event (10 seconds before and after event onset). Metadata CSV file contains the atrributes listed in the following table:

 




Attribute
Description


ID
Event ID


type


Event type (A-D). 

A: Long-duration (> 10 s) man-made noise, dominated by 11 Hz energy (characteristic of 8-pole motors). Potential source: operation of industrial machinery (e.g. conveyor belt with an 8-pole motor)

B: Transitional signals (Turning ON signals) with similar waveform and spectral features as Type A events. Potential source: Turning ON of Type A machinery.

C: High-amplitude, short-duration (< 10 s) blasts, dominated by high frequency energy (> 30 Hz). Potential source: Surface blasts at the nearest quarry (< 1 km from HQIL)

D: Low-amplitude blast-like events of mixed sources. Potential sources: Quarry blasts with source distances > 1 km from station HQIL (D1), underground explosions at the nearest quarry (D2), wind interaction with local structures (D3)



subtype
Event subtype. Only applicable for Type D events.


window_starttime_utc
Start time (in UTC) of 10-s window that was detected by the PSD detector. Event onsets may not always coincide with the window start time


onset_time_utc
Start time (in UTC) of event onset. For Type A events, this attribute is not applicable and is equal to window_starttime_utc


uncertainty_onset_s
Uncertainty (in seconds) of manually-picked event onset. Not applicable for Type A events.


potential_source
Potential source of event.
DOI: 10.5281/zenodo.15047874
title: Seismic Events in an Industrial Corridor of the Chicago Area

description: Dataset of 1262 seismic events recorded by seismic station NW.HQIL (Chicago area) between June 2017 and June 2019. Events were detected by a PSD misfit detector applied to overlapping (50%) 10-s windows of HQIL  waveforms. Detected events were then clustered using a k-means clustering model. The clustering results were used to create this labeled datset.

Dataset .zip file contains miniSEED files of 3-component, 20-s seismograms of each labeled event (10 seconds before and after event onset). Metadata CSV file contains the atrributes listed in the following table:

 




Attribute
Description


ID
Event ID


type


Event type (A-D). 

A: Long-duration (> 10 s) man-made noise, dominated by 11 Hz energy (characteristic of 8-pole motors). Potential source: operation of industrial machinery (e.g. conveyor belt with an 8-pole motor)

B: Transitional signals (Turning ON signals) with similar waveform and spectral features as Type A events. Potential source: Turning ON of Type A machinery.

C: High-amplitude, short-duration (< 10 s) blasts, dominated by high frequency energy (> 30 Hz). Potential source: Surface blasts at the nearest quarry (< 1 km from HQIL)

D: Low-amplitude blast-like events of mixed sources. Potential sources: Quarry blasts with source distances > 1 km from station HQIL (D1), underground explosions at the nearest quarry (D2), wind interaction with local structures (D3)



subtype
Event subtype. Only applicable for Type D events.


window_starttime_utc
Start time (in UTC) of 10-s window that was detected by the PSD detector. Event onsets may not always coincide with the window start time


onset_time_utc
Start time (in UTC) of event onset. For Type A events, this attribute is not applicable and is equal to window_starttime_utc


uncertainty_onset_s
Uncertainty (in seconds) of manually-picked event onset. Not applicable for Type A events.


potential_source
Potential source of event.