cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10820812
title: Spherical harmonic models of the shape of (433) Eros

description: This archive contains two spherical harmonic models of the shape of asteroid 433 Eros. One model is based on laser altimetry from the instrument NLR and the other is based on a stereo photoclinometry shape.

The data used to generate the model based on laser altimetery were taken from the file nlr125ar.img on NASA's PDS website. This image file was first converted to netcdf format using the generic-mapping-tools function xyz2grd, and the resulting pixel registed map was then converted to a gridline registration using the function grdsample. Following this, the resulting netcdf file was read into the pyshtools software and expanded into spherical harmonics using the function SHCoeffs.expand(). The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)m. The units of the coefficients are meters.

The data used to generate the model based on the stereo photoclinometric shape model were taken from the file quad512q.tab on NASA's PDS website. The vertices from the ICQ shape model with Q=512 were first converted from Cartesian to spherical coordinates, from which a regular gridline registered netcdf file was created using the generic-mapping-tools function surface with a tension of 0.6 and with a grid spacing of 0.17578125 degrees. This file was then read into the pyshtools software and expanded into spherical harmonics in the same manner as the NLA based model.

The two files in this archive are



Eros_NLR_shape_719.bshc.gz

Eros_SPC_shape_511.bshc.gz


The numbers 719 and 511 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 8 and ~5.7 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip.
DOI: 10.5281/zenodo.10820811
title: Spherical harmonic models of the shape of (433) Eros

description: This archive contains two spherical harmonic models of the shape of asteroid 433 Eros. One model is based on laser altimetry from the instrument NLR and the other is based on a stereo photoclinometry shape.

The data used to generate the model based on laser altimetery were taken from the file nlr125ar.img on NASA's PDS website. This image file was first converted to netcdf format using the generic-mapping-tools function xyz2grd, and the resulting pixel registed map was then converted to a gridline registration using the function grdsample. Following this, the resulting netcdf file was read into the pyshtools software and expanded into spherical harmonics using the function SHCoeffs.expand(). The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)m. The units of the coefficients are meters.

The data used to generate the model based on the stereo photoclinometric shape model were taken from the file quad512q.tab on NASA's PDS website. The vertices from the ICQ shape model with Q=512 were first converted from Cartesian to spherical coordinates, from which a regular gridline registered netcdf file was created using the generic-mapping-tools function surface with a tension of 0.6 and with a grid spacing of 0.17578125 degrees. This file was then read into the pyshtools software and expanded into spherical harmonics in the same manner as the NLA based model.

The two files in this archive are



Eros_NLR_shape_719.bshc.gz

Eros_SPC_shape_511.bshc.gz


The numbers 719 and 511 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 8 and ~5.7 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip.
DOI: 10.5281/zenodo.10731728
title: Bottom up Isoprene emissions (open loop)

description: BVOC gas emissions from vegetation represent a hugely important contributor to the total emission of volatile organic compounds at the global scale. BVOCs in turn play a key role in tropospheric chemistry and impact both the formation of ozone photochemical smog and secondary organic aerosols, which both impact air quality. MEGAN is an open-sourced software package that has been adapted by researchers at NILU to operate with SURFEX model outputs and meteorological data from ECMWF. The MEGAN software calculates emissions of a wide range of BVOCs emitted by plants and aggregates these chemical components into representative chemical species defined in an external chemical mechanism. In our case, this done specifically is for the BVOCs defined (see Table 2 for full list) in the Regional Atmospheric Chemistry Mechanism (Stockwell et al., 1997) that is used in the MOCAGE (Guth et al., 2016) chemical transport model. MOCAGE is being used as the test model the SEEDS project since it is one of the CAMS regional atmospheric chemistry models.

https://www.seedsproject.eu/data/isop-ol
DOI: 10.5281/zenodo.10731727
title: Bottom up Isoprene emissions (open loop)

description: BVOC gas emissions from vegetation represent a hugely important contributor to the total emission of volatile organic compounds at the global scale. BVOCs in turn play a key role in tropospheric chemistry and impact both the formation of ozone photochemical smog and secondary organic aerosols, which both impact air quality. MEGAN is an open-sourced software package that has been adapted by researchers at NILU to operate with SURFEX model outputs and meteorological data from ECMWF. The MEGAN software calculates emissions of a wide range of BVOCs emitted by plants and aggregates these chemical components into representative chemical species defined in an external chemical mechanism. In our case, this done specifically is for the BVOCs defined (see Table 2 for full list) in the Regional Atmospheric Chemistry Mechanism (Stockwell et al., 1997) that is used in the MOCAGE (Guth et al., 2016) chemical transport model. MOCAGE is being used as the test model the SEEDS project since it is one of the CAMS regional atmospheric chemistry models.

https://www.seedsproject.eu/data/isop-ol
DOI: 10.5281/zenodo.10796383
title: Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

description: Dataset used to analyize role of climate variability
DOI: 10.5281/zenodo.10796384
title: Climate variability can outweigh the influence of climate mean changes for extreme precipitation under global warming

description: Dataset used to analyize role of climate variability
DOI: 10.5281/zenodo.10794059
title: Spherical harmonic models of the shape of Mars [MOLA]

description: This archive contains four spherical harmonic models of the shape of Mars truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a Mars shape model sampled at 64 pixels per degree.

The data used to generate these models are from the MOLA instrument on the Mars Global Surveyor spacecraft, as found in the files MEGR00N000GB.IMG, MEGR00N180GB.IMG, MEGR90N000GB.IMG and MEGR90N180GM.IMG on NASA's PDS website. These four image files were first converted to netcdf format using the generic-mapping-tools function xyz2grd, and then turned into a single file using the function grdpaste. The resulting pixel registed map was then converted to a gridline registration using the function grdsample. Following this, the resulting netcdf file was read into the pyshtools software and expanded into spherical harmonics using the function SHCoeffs.expand(). The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)m. The units of the coefficients are meters.

The four files in this archive are



Mars_shape_5759.sh.gz

Mars_shape_2879.sh.gz

Mars_shape_1439.sh.gz

Mars_shape_719.sh.gz


The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.

These models supercede Spherical harmonic model of the shape of Mars: MarsTopo2600 and Spherical harmonic model of the shape of Mars: MarsTopo719.
DOI: 10.5281/zenodo.10820719
title: Spherical harmonic models of the shape of Mars [MOLA]

description: This archive contains four spherical harmonic models of the shape of Mars truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a Mars shape model sampled at 64 pixels per degree.

The data used to generate these models are from the MOLA instrument on the Mars Global Surveyor spacecraft, as found in the files MEGR00N000GB.IMG, MEGR00N180GB.IMG, MEGR90N000GB.IMG and MEGR90N180GM.IMG on NASA's PDS website. These four image files were first converted to netcdf format using the generic-mapping-tools function xyz2grd, and then turned into a single file using the function grdpaste. The resulting pixel registed map was then converted to a gridline registration using the function grdsample. Following this, the resulting netcdf file was read into the pyshtools software and expanded into spherical harmonics using the function SHCoeffs.expand(). The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)m. The units of the coefficients are meters.

The four files in this archive are



Mars_MOLA_shape_5759.bshc.gz

Mars_MOLA_shape_2879.bshc.gz

Mars_MOLA_shape_1439.bshc.gz

Mars_MOLA_shape_719.bshc.gz


The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.

These models supercede Spherical harmonic model of the shape of Mars: MarsTopo2600 and Spherical harmonic model of the shape of Mars: MarsTopo719.
DOI: 10.5281/zenodo.10794058
title: Spherical harmonic models of the shape of Mars [MOLA]

description: This archive contains four spherical harmonic models of the shape of Mars truncated at different maximum spherical harmonic degrees. The highest resolution model has a maximum spherical harmonic degree of 5759, which was generated from a Mars shape model sampled at 64 pixels per degree.

The data used to generate these models are from the MOLA instrument on the Mars Global Surveyor spacecraft, as found in the files MEGR00N000GB.IMG, MEGR00N180GB.IMG, MEGR90N000GB.IMG and MEGR90N180GM.IMG on NASA's PDS website. These four image files were first converted to netcdf format using the generic-mapping-tools function xyz2grd, and then turned into a single file using the function grdpaste. The resulting pixel registed map was then converted to a gridline registration using the function grdsample. Following this, the resulting netcdf file was read into the pyshtools software and expanded into spherical harmonics using the function SHCoeffs.expand(). The spherical harmonic functions were chosen to be "4pi" normalized and to exclude the Condon-Shortley phase factor of (-1)m. The units of the coefficients are meters.

The four files in this archive are



Mars_MOLA_shape_5759.bshc.gz

Mars_MOLA_shape_2879.bshc.gz

Mars_MOLA_shape_1439.bshc.gz

Mars_MOLA_shape_719.bshc.gz


The numbers 5759, 2879, 1439, and 719 in the filename refer to the maximum spherical harmonic degree of file, which corresponds to effective spatial resolutions of 64, 32, 16, and 8 pixels per degree, respectively. The files are stored in the binary "bshc" format as described in the pyshtools documentation and are furthermore compressed using gzip. The lower resolution models were generated by truncating the spherical harmonic coefficients of the highest resolution model.

These models supercede Spherical harmonic model of the shape of Mars: MarsTopo2600 and Spherical harmonic model of the shape of Mars: MarsTopo719.
DOI: 10.5281/zenodo.10820625
title: IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift Evaluation Dataset

description: The Chinese Acoustic Scene (CAS) 2023 dataset is a large-scale dataset that serves as a foundation for research related to environmental acoustic scenes. The dataset includes 10 common acoustic scenes, with a total duration of over 130 hours. Each audio clip is 10 seconds long with metadata about the recording location and timestamp. The dataset was collected by members of the Joint Laboratory of Environmental Sound Sensing at the School of Marine Science and Technology, Northwestern Polytechnical University. The data collection period spanned from April 2023 to September 2023, covering 22 different cities across China. The CAS 2023 dataset was collected using the XS-SN-2BE1 manufactured by Xi'an Lianfeng Acoustic Technologies Co., Ltd (https://www.lfxstek.com/).  

The ICME 2024 Semi-supervised Acoustic Scene Classification under Domain Shift challenge (https://2024.ieeeicme.org/grand-challenge-proposals/, https://ascchallenge.xshengyun.com/) dataset consists of development (https://zenodo.org/records/10616533) and evaluation datasets, all derived from the CAS 2023 dataset. The evaluation dataset includes 1,100 recordings, where data are selected from 12 cities, with 5 unseen cities specifically chosen to provide a more comprehensive evaluation of submissions under domain shift.

Baseline: https://github.com/JishengBai/ICME2024ASC

Acoustic scenes (10): Bus, Airport, Metro, Restaurant, Shopping mall, Public square, Urban park, Traffic street, Construction site, Bar
DOI: 10.5281/zenodo.10820626
title: IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift Evaluation Dataset

description: The Chinese Acoustic Scene (CAS) 2023 dataset is a large-scale dataset that serves as a foundation for research related to environmental acoustic scenes. The dataset includes 10 common acoustic scenes, with a total duration of over 130 hours. Each audio clip is 10 seconds long with metadata about the recording location and timestamp. The dataset was collected by members of the Joint Laboratory of Environmental Sound Sensing at the School of Marine Science and Technology, Northwestern Polytechnical University. The data collection period spanned from April 2023 to September 2023, covering 22 different cities across China. The CAS 2023 dataset was collected using the XS-SN-2BE1 manufactured by Xi'an Lianfeng Acoustic Technologies Co., Ltd (https://www.lfxstek.com/).  

The ICME 2024 Semi-supervised Acoustic Scene Classification under Domain Shift challenge (https://2024.ieeeicme.org/grand-challenge-proposals/, https://ascchallenge.xshengyun.com/) dataset consists of development (https://zenodo.org/records/10616533) and evaluation datasets, all derived from the CAS 2023 dataset. The evaluation dataset includes 1,100 recordings, where data are selected from 12 cities, with 5 unseen cities specifically chosen to provide a more comprehensive evaluation of submissions under domain shift.

Baseline: https://github.com/JishengBai/ICME2024ASC

Acoustic scenes (10): Bus, Airport, Metro, Restaurant, Shopping mall, Public square, Urban park, Traffic street, Construction site, Bar
DOI: 10.5281/zenodo.10601198
title: Multi-dimensional author profiling by business roles

description: This dataset contains the data used in the paper "Multidimensional Author Profiling for Social Business Intelligence", more specifically, the gold standard (GS) and silver standard (SS) created for training and validating text classifiers for business profiling of social network users.

The GS dataset is a CSV file with the following columns:







screen-name, user-id, verified-user (boolean), multi-level-label, manual-verification, textual-description, followers (int), friends (int), source (not used)



The attribute "multi-level label" contains label represeting the user business profile, regarding the three perspectives: role, colective-vs-individual, and on-domain ones. The attribute "manual-verification" is a second pass from experts to validate the assigned label.

 

The SS dataset is a "|"-separated text file with the following columns:







screen-name|user-id|verified-user|multi-level-label|textual-description

 




The SS dataset is generated with an unsupervised method through an initial seed of bigrams. Therefore, the dataset can contain wrong and incomplete labels, hence the name silver standard (SS).

 

As data is captured from Twitter, we can only relase it under restricted conditions.
DOI: 10.5281/zenodo.10601199
title: Multi-dimensional author profiling by business roles

description: This dataset contains the data used in the paper "Multidimensional Author Profiling for Social Business Intelligence", more specifically, the gold standard (GS) and silver standard (SS) created for training and validating text classifiers for business profiling of social network users.

The GS dataset is a CSV file with the following columns:







screen-name, user-id, verified-user (boolean), multi-level-label, manual-verification, textual-description, followers (int), friends (int), source (not used)



The attribute "multi-level label" contains label represeting the user business profile, regarding the three perspectives: role, colective-vs-individual, and on-domain ones. The attribute "manual-verification" is a second pass from experts to validate the assigned label.

 

The SS dataset is a "|"-separated text file with the following columns:







screen-name|user-id|verified-user|multi-level-label|textual-description

 




The SS dataset is generated with an unsupervised method through an initial seed of bigrams. Therefore, the dataset can contain wrong and incomplete labels, hence the name silver standard (SS).

 

As data is captured from Twitter, we can only relase it under restricted conditions.
DOI: 10.5281/zenodo.10820506
title: GRIST MCS data

description: AS IS
DOI: 10.5281/zenodo.10820507
title: GRIST MCS data

description: AS IS
DOI: 10.5281/zenodo.10423689
title: Daily GNSS time series of La Palma 2021 eruption

description: Time series form GNSS station in La Palma (Canary Island, Spain) during 2021 eruption (19/09/2021-13/12/2021). The daily neu time series have been computed in a Double Diference method using Bernese v.5.2 software as describe in the references.
DOI: 10.5281/zenodo.10821412
title: Daily GNSS time series of La Palma 2021 eruption

description: Time series form GNSS station in La Palma (Canary Island, Spain) during 2021 eruption (19/09/2021-21/01/2022). The daily neu time series have been computed in a Double Diference method using Bernese v.5.2 software as describe in the references.
DOI: 10.5281/zenodo.10118898
title: CZ DEMO

description: The file contains data on KPIs from CZ demonstration projects.
DOI: 10.5281/zenodo.10823057
title: Geomagnetic field data at Jicamarca and Piura on 23 March 2023

description: The H-component of the geomagnetic field at Jicamarca (JICA, equator) and Piura (PIUR, off-equator) stations on 23 March 2023.
DOI: 10.5281/zenodo.10821688
title: Excel mapping tool for 2023 avian influenza data reporting

description: Data collection is an important task of the European Food Safety Authority (EFSA) and a fundamental component of risk assessment (Articles 22 and 23 of Regulation (EC) No 178/2002). EFSA receives a large volume of data from Member States (MSs) that is used in support of its risk assessment mission.

Council Directive 2005/94/EC and Commission Decision 2010/367/EU lay down the guidelines for monitoring and reporting avian influenza surveillance data on poultry and wild birds by European Union (EU) MSs. EFSA has been assigned the task of collating, validating, analysing, and summarising in an annual report the results from the avian influenza surveillance programmes in poultry and wild birds. For the reporting of data, EFSA provides a Data Collection Framework that allows data providers to submit data in eXtensible Markup Language (XML) format through a web interface or a web service. Here, a data model describing the format, and the content requested when submitting data through the DCF, is provided.

The data model supports the reporting of laboratory testing results for avian influenza in both wild birds, and poultry. The use of this reporting standard ensures that reported results are comparable between reporting countries. Data reported in this format will be used to generate epidemiological updates on the avian influenza surveillance testing carry out in Europe, and to provide scientific advice to the European Commission.
description: EU; xls; zoonoses_support@efsa.europa.eu
DOI: 10.5281/zenodo.10821689
title: Excel mapping tool for 2023 avian influenza data reporting

description: Data collection is an important task of the European Food Safety Authority (EFSA) and a fundamental component of risk assessment (Articles 22 and 23 of Regulation (EC) No 178/2002). EFSA receives a large volume of data from Member States (MSs) that is used in support of its risk assessment mission.

Council Directive 2005/94/EC and Commission Decision 2010/367/EU lay down the guidelines for monitoring and reporting avian influenza surveillance data on poultry and wild birds by European Union (EU) MSs. EFSA has been assigned the task of collating, validating, analysing, and summarising in an annual report the results from the avian influenza surveillance programmes in poultry and wild birds. For the reporting of data, EFSA provides a Data Collection Framework that allows data providers to submit data in eXtensible Markup Language (XML) format through a web interface or a web service. Here, a data model describing the format, and the content requested when submitting data through the DCF, is provided.

The data model supports the reporting of laboratory testing results for avian influenza in both wild birds, and poultry. The use of this reporting standard ensures that reported results are comparable between reporting countries. Data reported in this format will be used to generate epidemiological updates on the avian influenza surveillance testing carry out in Europe, and to provide scientific advice to the European Commission.
description: EU; xls; zoonoses_support@efsa.europa.eu
DOI: 10.25919/dkt1-ep54
title: Parkes observations for project P276 semester 2008APRS_02

description: Timing of multibeam pulsar discoveries
DOI: 10.25919/keqk-xx06
title: Parkes observations for project P276 semester 2008APRS_01

description: Timing of multibeam pulsar discoveries
DOI: 10.25919/sgt1-bp80
title: Parkes observations for project P276 semester 2008APRS_03

description: Timing of multibeam pulsar discoveries
DOI: 10.25919/28mf-bm22
title: Parkes observations for project P276 semester 2007OCTS_01

description: Timing of multibeam pulsar discoveries
DOI: 10.25919/0d9v-dz67
title: Parkes observations for project P276 semester 2007APRS_02

description: Timing of multibeam pulsar discoveries
DOI: 10.25919/qy0q-y462
title: Parkes observations for project P276 semester 2007APRS_01

description: Timing of multibeam pulsar discoveries
DOI: 10.5281/zenodo.8103759
title: thgie/critical-reading-vice: Initial Release

description: These scripts accompanied a case study of distant reading the source code of the VICE emulator. More information on the study can be found via https://phd.thgie.ch/notes/vice.html. A resulting article is to be published in 2024.