cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.qvc6q9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sphyraena obtusata",
 "Country is Libya",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031259-250811113504898/datasets/export for details.
DOI: 10.15468/dl.ak97fu
title: Occurrence Download

description: A dataset containing 1728 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Passer domesticus",
 "Country is Lao People’s Democratic Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1728 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031261-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/jewpvk/iuvzue
title: NiGWModel_final_18Aug2025.pdf

description: Method documentation, illustrated for Ni
DOI: 10.22008/fk2/jewpvk/obbikl
title: ID15_metals_20231004.csv

description: csv fiel
DOI: 10.22008/fk2/jewpvk/zkoc42
title: ID15_mean_50pctile_20231004-1.zip

description: shape-file
DOI: 10.22008/fk2/jewpvk
title: Estimating potential groundwater contribution of nickel, copper, cadmium, lead, and zinc concentrations to surface water catchments in Denmark

description: This dataset includes estimates of the typical groundwater contribution of nickel, copper, cadmium, lead, and zinc to the ID15 catchments. The methodology is described in detail and illustrated for nickel (see pdf file). The data is provided as a shapefile and csv file. This work was funded by the Danish EPA (Miljøstyrelsen) in relation to "Videreudvikling og klargøring af MetalStat for landsdækkende beregninger." (Sørensen et al., 2024) and "Unifying monitoring and modelling of water concentration levels in surface waters (Version 2)" (Sorensen et al., 2025).
DOI: 10.22008/fk2/jewpvk/w6yc8z
title: READ_ME.txt

description: Readme file, data-file contents
DOI: 10.15468/dl.us3m47
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Chiloglanis longibarbis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031262-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16909125
title: SWC files of 18,621 reconstructed cortical neurons

description: The dataset contains the SWC files of reconstructed cortical neurons that have been mapped to Allen CCFv3.
DOI: 10.5281/zenodo.16909126
title: SWC files of 18,621 reconstructed cortical neurons

description: The dataset contains the SWC files of reconstructed cortical neurons that have been mapped to Allen CCFv3.
DOI: 10.15468/dl.memxks
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sphyraena obtusata",
 "Country is Ukraine",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031263-250811113504898/datasets/export for details.
DOI: 10.15468/dl.3q5pf4
title: Occurrence Download

description: A dataset containing 15973 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Vegetation data from sheep grazing experiment at alpine site in Hol, Norway"
 ]
}

 The dataset includes 15973 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031265-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15071077
title: A Multi-Year Forecast Dataset of Arctic Sea Ice Concentration Based on Spectral Analysis and Modeling

description: 1. Data Description

This dataset contains both observed and forecasted Arctic sea ice concentration (SIC) data, as well as the code repository for data processing and forecasting.





Forecasted Data: Daily SIC predictions from January 1, 2020 – December 31, 2029.




Observed Data: Daily SIC from January 1, 2013 – December 31, 2024, provided by the University of Bremen.



2. SIC data



Observed Data (in Input_data.zip):



Temporal Coverage: January 1, 2013, to December 31, 2024.

Data Formats: NetCDF, format.

Naming Convention: Files are named according to the date in the format asi-AMSR2-n6250-YYYYMMDD-v5.4.nc.



Forecasted Data ( Forecasted_data.zip):



Temporal Coverage: January 1, 2020, to December 31, 2029.

 Data Formats: GeoTIFF format.

both based each-pixel and mean-seried forecasts are included






Projection System: Northern Polar Stereographic.

Spatial Resolution: 6.25 km.


3. code





This repository provides a complete pipeline for long-term daily Arctic sea ice concentration (SIC) prediction based on time series modeling. The included code consists of four major functional components:

🔧 1. Data Preprocessing (Input_data.zip)





preprocess.py: This script processes raw NetCDF-format Sea Ice Concentration (SIC) data from the Bremen University dataset.





The preprocessed data is also provided as input_data for direct use in 2Time Series Forecasting.


📈 2. Time Series Forecasting (Forecasting_process.zip)





forecast.py: Main forecasting script that uses a hybrid model (Least Squares + AutoRegressive).




ls_each_pixel.py: Performs least squares fitting period singal for each individual pixel.


ls_mean_series.py: Performs least squares fitting period singal for mean series.



ar.py: Applies an AutoRegressive model to residuals for further prediction refinement.


ls_ar.py: Combines LS and AR forecasts.




The output is a predicted .npy file containing daily SIC forecasts for a full year.


🗺 3. GeoTIFF Export (Forecasted_data.zip)





npy2tif.py: Converts the predicted SIC .npy data into daily GeoTIFF images using georeferencing from a sample NetCDF file and a North Polar Stereographic projection.
DOI: 10.5281/zenodo.16909302
title: A Multi-Year Forecast Dataset of Arctic Sea Ice Concentration Based on Spectral Analysis and Modeling

description: 1. Data Description

This dataset contains both observed and forecasted Arctic sea ice concentration (SIC) data, as well as the code repository for data processing and forecasting.





Forecasted Data: Daily SIC predictions from January 1, 2020 – December 31, 2029.




Observed Data: Daily SIC from January 1, 2013 – December 31, 2024, provided by the University of Bremen.



2. SIC data



Observed Data (in Input_data.zip):



Temporal Coverage: January 1, 2013, to December 31, 2024.

Data Formats: NetCDF, format.

Naming Convention: Files are named according to the date in the format asi-AMSR2-n6250-YYYYMMDD-v5.4.nc.



Forecasted Data ( Forecasted_data.zip):



Temporal Coverage: January 1, 2020, to December 31, 2029.

 Data Formats: GeoTIFF format.

both based each-pixel and mean-seried forecasts are included






Projection System: Northern Polar Stereographic.

Spatial Resolution: 6.25 km.


3. code





This repository provides a complete pipeline for long-term daily Arctic sea ice concentration (SIC) prediction based on time series modeling. The included code consists of four major functional components:

🔧 1. Data Preprocessing (Input_data.zip)





preprocess.py: This script processes raw NetCDF-format Sea Ice Concentration (SIC) data from the Bremen University dataset.





The preprocessed data is also provided as input_data for direct use in 2Time Series Forecasting.


📈 2. Time Series Forecasting (Forecasting_process.zip)





forecast.py: Main forecasting script that uses a hybrid model (Least Squares + AutoRegressive).




ls_each_pixel.py: Performs least squares fitting period singal for each individual pixel.


ls_mean_series.py: Performs least squares fitting period singal for mean series.



ar.py: Applies an AutoRegressive model to residuals for further prediction refinement.


ls_ar.py: Combines LS and AR forecasts.




The output is a predicted .npy file containing daily SIC forecasts for a full year.


🗺 3. GeoTIFF Export (Forecasted_data.zip)





npy2tif.py: Converts the predicted SIC .npy data into daily GeoTIFF images using georeferencing from a sample NetCDF file and a North Polar Stereographic projection.
DOI: 10.22000/vnz5vq78c8t11r05
title: PeakForce Tapping Measurements Belonging to the Publication: "From single microgels to dense microgel monolayers – investigation by atomic force microscopy"

description: AFM images of single microgels and microgels in dense monolayers at the solid-liquid interface, recorded in PeakForce Tapping mode
description: Atomic Force Microscopy (AFM)
description: .SPM files (Bruker file format)
description: Dimension Icon AFM
DOI: 10.15468/dl.t5yv9n
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Passer domesticus",
 "Country is Liberia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 66 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031264-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11588/portal.gsi.68a823d82b63a
title: Sotheby, Wilkinson & Hodge
DOI: 10.15468/dl.k235cc
title: Occurrence Download

description: A dataset containing 619 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Passer domesticus",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 619 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031266-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9gqeu3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oncorhynchus clarkii",
 "Country is Cyprus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031268-250811113504898/datasets/export for details.
DOI: 10.15468/dl.zc36ez
title: Occurrence Download

description: A dataset containing 211948 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cycadales, Ginkgoales, Ephedrales, Gnetales, Welwitschiales, Acorales, Alismatales, Arecales, Asparagales, Commelinales, Dioscoreales, Liliales, Pandanales, Petrosaviales, Poales, Zingiberales, Apiales, Aquifoliales, Asterales, Austrobaileyales, Boraginales, Brassicales, Buxales, Caryophyllales, Celastrales, Ceratophyllales, Chloranthales, Cornales, Crossosomatales, Cucurbitales, Dilleniales, Dipsacales, Ericales, Fabales, Fagales, Garryales, Gentianales, Geraniales, Gunnerales, Huerteales, Icacinales, Lamiales, Laurales, Magnoliales, Malpighiales, Malvales, Myrtales, Nymphaeales, Oxalidales, Piperales, Proteales, Ranunculales, Rosales, Santalales, Sapindales, Saxifragales, Solanales, Trochodendrales, Vitales, Zygophyllales, Pinales, Bruniales, Escalloniales)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 "Year is greater than or equal to 1970",
 "CoordinateUncertaintyInMeters is less than 3000"
 ]
}

 The dataset includes 211948 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031244-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ccq4p2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Congochromis pugnatus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031267-250811113504898/datasets/export for details.
DOI: 10.15468/dl.j8hnw5
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oncorhynchus clarkii",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031270-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22000/0b754r92k72b6ngg
title: Data belonging to the Publication: "From single microgels to dense microgel monolayers – investigation by atomic force microscopy"

description: This dataset serves as a wrapper to all datasets belonging to the published article "From single microgels to dense microgel monolayers – investigation by atomic force microscopy". See related identifiers for the individual DOIs as well as README.
DOI: 10.5281/zenodo.14892925
title: Seismic Avalanche Signals recorded in Dischma Valley above Davos, Switzerland

description: This repository hosts the seismic event data accompanying our publication, Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data.

It contains seismic events recorded with an array of five sensors (CS, CT, NE, SE, WE) in Dischma Valley, above Davos, Switzerland. The central sensor (CT) is a three-component LE-3Dlite seismometer (eigenfrequency 1Hz, sensitivity 800 V/(m/s)), while the other four are single-component Lennartz LE-1D/V seismometers (eigenfrequency 1Hz, sensitivity 800 V/(m/s)). All waveform data have been converted to ground motion [m/s] for ease of use.

In addition to the waveform data, a CSV file provides event labels for avalanches and earthquakes. Some events were verified using camera footage and a Doppler radar. For events where verification was not possible, three experts labelled them independently to ensure reliability. In total, this dataset contains 84 avalanches, 183 earthquakes and 645 unrelated (noise) events.
description: Description of the columns in the labels.csv file:

Event_id: unique event identifier

starttime: start time in UTC of the corresponding ObsPy file

initial_time / end_time: manual picks of the event onset and end in samples (= seconds x sampling_rate) 

duration: duration of the picked event in seconds

label: label according to the rule: sum_of_expert_scores >= 2

av_score / eq_score: sum of expert scores = expert_1 + expert_2 + expert_3 (+ earthquake catalogue)
DOI: 10.5281/zenodo.14892926
title: Seismic Avalanche Signals recorded in Dischma Valley above Davos, Switzerland

description: This repository hosts the seismic event data accompanying our publication, Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data.

It contains seismic events recorded with an array of five sensors (CS, CT, NE, SE, WE) in Dischma Valley, above Davos, Switzerland. The central sensor (CT) is a three-component LE-3Dlite seismometer (eigenfrequency 1Hz, sensitivity 800 V/(m/s)), while the other four are single-component Lennartz LE-1D/V seismometers (eigenfrequency 1Hz, sensitivity 800 V/(m/s)). All waveform data have been converted to ground motion [m/s] for ease of use.

In addition to the waveform data, a CSV file provides event labels for avalanches and earthquakes. Some events were verified using camera footage and a Doppler radar. For events where verification was not possible, three experts labelled them independently to ensure reliability. In total, this dataset contains 84 avalanches, 183 earthquakes and 645 unrelated (noise) events.
description: Description of the columns in the labels.csv file:

Event_id: unique event identifier

starttime: start time in UTC of the corresponding ObsPy file

initial_time / end_time: manual picks of the event onset and end in samples (= seconds x sampling_rate) 

duration: duration of the picked event in seconds

label: label according to the rule: sum_of_expert_scores >= 2

av_score / eq_score: sum of expert scores = expert_1 + expert_2 + expert_3 (+ earthquake catalogue)
DOI: 10.15468/dl.nxxh2z
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oncorhynchus clarkii",
 "Country is Denmark",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031269-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y9bzkm
title: Occurrence Download

description: A dataset containing 984 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Passer domesticus",
 "Country is Malawi",
 "HasCoordinate is true"
 ]
}

 The dataset includes 984 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031271-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14679432
title: Adaptation of Methanogenic Microbial Assemblages to Antibiotics: The Role of Resistance Genes and Taxonomic Composition

description: This dataset features data and code of the associated publication in Environmental Pollution (https://doi.org/10.1016/j.envpol.2025.126828). To reproducibly run the code you should download the entire .zip archive and open the *.RProj file ideally with the same R version (4.3.1). To achieve maximum reproducibility of the code you should run renv::restore() to restore the packages recorded in renv.lock. Scripts within the folder code are named in the order in which they should be run. Note that running the Bayesian models requires a C++ toolchain. A web search of "RStan Getting Started" will yield up to date information about how to install this on your device. The models ran for the publication are provided as .rds file in case you don't want to run it yourself. Some figures required post-export editing in the paid program "Affinity photo". The edited and unedited versions are included in this repository to allow for comparisons. Also the .afphoto files are included for users that own a license.
DOI: 10.5281/zenodo.14679433
title: Adaptation of Methanogenic Microbial Assemblages to Antibiotics: The Role of Resistance Genes and Taxonomic Composition

description: This dataset features data and code of the associated publication in Environmental Pollution (https://doi.org/10.1016/j.envpol.2025.126828). To reproducibly run the code you should download the entire .zip archive and open the *.RProj file ideally with the same R version (4.3.1). To achieve maximum reproducibility of the code you should run renv::restore() to restore the packages recorded in renv.lock. Scripts within the folder code are named in the order in which they should be run. Note that running the Bayesian models requires a C++ toolchain. A web search of "RStan Getting Started" will yield up to date information about how to install this on your device. The models ran for the publication are provided as .rds file in case you don't want to run it yourself. Some figures required post-export editing in the paid program "Affinity photo". The edited and unedited versions are included in this repository to allow for comparisons. Also the .afphoto files are included for users that own a license.
DOI: 10.15468/dl.u7rzts
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Quercus marlipoensis"
 ]
}

 The dataset includes 10 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031272-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m7vqc2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Leptobotia brachycephala)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031275-250811113504898/datasets/export for details.
DOI: 10.15468/dl.gfxmpf
title: Occurrence Download

description: A dataset containing 418 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Italy",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (CR, EN, VU, LC, DD, NT, NE, EX, EW)",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (28eb1a3f-1c15-4a95-931a-4af90ecb574d, e2e717bf-551a-4917-bdc9-4fa0f342c530, da86174a-a605-43a4-a5e8-53d484152cd3, c1b1455b-18ec-4637-9e0f-18cb0524b7ed, 0870a77b-587c-4369-a8ed-bc3d347b8e1c, c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f, 64ee55c9-570a-42af-b7da-3f13c6b4e5a9, bb646dff-a905-4403-a49b-6d378c2cf0d9, 2d6e0e40-2aee-11d8-aa2d-b8a03c50a862, 7c0177c0-1c0d-4c6c-bb0b-77e61759495d)",
 "TaxonKey is one of (Megachilidae, Andrenidae, Apidae, Halictidae, Colletidae, Melittidae, Anthophoridae)"
 ]
}

 The dataset includes 418 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031273-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8wgsuk
title: Occurrence Download

description: A dataset containing 18783 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oncorhynchus clarkii",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 18783 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031274-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.