cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17341113
title: Source codes and model outputs of AWIESM-wiso

description: Model codes:


Instruction_AWIESM2_1_wiso.pdf: Instruction on how to download AWIESM-wiso and perform simulations.


codes_runscripts.tar.gz: Source codes, run-scripts and namelists required for AWIESM-wiso.


 


Model outputs:


pi_atmosphere_climatology_monthly.nc: Climatological monthly isotope and climate variables for our PI simulation


mh_atmosphere_climatology_monthly.nc: Climatological monthly isotope and climate variables for our MH simulation


pi_h2o16_ocean.nc:  Climatological monthly h2o16 tracer in the ocean at all depths for PI.


pi_h2o18_ocean.nc:  Climatological monthly h2o18 tracer in the ocean at all depths for PI.


mh_h2o16_ocean.nc:  Climatological monthly h2o16 tracer in the ocean at all depths for MH.


mh_h2o18_ocean.nc:  Climatological monthly h2o18 tracer in the ocean at all depths for MH.


mh_h2o18_ocean.nc:  Climatological monthly h2o18 tracer in the ocean at all depths for MH.


pi_isotope_atmos_3d.nc: Climatological monthly air temperature, specific humidity, isotope in vapor for all atmospheric levels for PI.


mh_isotope_atmos_3d.nc: Climatological monthly air temperature, specific humidity, isotope in vapor for all atmospheric levels for PI.
DOI: 10.5281/zenodo.7765336
title: Source codes and model outputs of AWIESM-wiso

description: Model codes:


Instruction_AWIESM2_1_wiso.pdf: Instruction on how to download AWIESM-wiso and perform simulations.


codes_runscripts.tar.gz: Source codes, run-scripts and namelists required for AWIESM-wiso.


 


Model outputs:


pi_atmosphere_climatology_monthly.nc: Climatological monthly isotope and climate variables for our PI simulation


mh_atmosphere_climatology_monthly.nc: Climatological monthly isotope and climate variables for our MH simulation


pi_h2o16_ocean.nc:  Climatological monthly h2o16 tracer in the ocean at all depths for PI.


pi_h2o18_ocean.nc:  Climatological monthly h2o18 tracer in the ocean at all depths for PI.


mh_h2o16_ocean.nc:  Climatological monthly h2o16 tracer in the ocean at all depths for MH.


mh_h2o18_ocean.nc:  Climatological monthly h2o18 tracer in the ocean at all depths for MH.


mh_h2o18_ocean.nc:  Climatological monthly h2o18 tracer in the ocean at all depths for MH.


pi_isotope_atmos_3d.nc: Climatological monthly air temperature, specific humidity, isotope in vapor for all atmospheric levels for PI.


mh_isotope_atmos_3d.nc: Climatological monthly air temperature, specific humidity, isotope in vapor for all atmospheric levels for PI.
DOI: 10.5281/zenodo.17340438
title: Survey Data on Audit Evidence Mix and KAM Disclosure in Algeria

description: This dataset comprises primary quantitative data collected through a cross-sectional survey of 297 practicing external auditors in Algeria. The study's target population included all officially registered external auditors in Algeria. Questionnaires were distributed using a mixed-mode strategy (electronic mail and in-person visits), with 297 complete and usable responses received from an initial distribution of approximately 850, yielding a 34.9% response rate.

The structured questionnaire, developed from an extensive literature review and previously validated scales, measures five latent constructs using a 5-point Likert scale (ranging from 1=Strongly Disagree to 5=Strongly Agree). These constructs are:





**Auditor-Generated Evidence (AGE):** Measured with 4 items.




**Externally-Sourced Evidence (ESE):** Measured with 4 items.




**Client-Provided Evidence Verification (CPEV):** Measured with 3 items.




**Key Audit Matter Disclosure Quality (KAMQ):** Measured with 3 items.




**Audit Report Quality (ARQ):** Measured with 4 items.



The dataset also includes demographic characteristics of the sample, such as Professional Role, Years of Professional Experience, Highest Educational Qualification, and Firm Size, as detailed in Table 1 of the associated manuscript. This data was utilized to test a mediation model via Partial Least Squares Structural Equation Modeling (PLS-SEM) and offers valuable empirical insights into how different audit evidence types contribute to KAM disclosure quality, which in turn affects overall audit report quality within an emerging market context. It supports research on audit quality, audit evidence, and KAMs.
description: Audit Quality, Audit Evidence, Key Audit Matters (KAMs), Audit Report Quality, Mediation Analysis, Emerging Markets, Algeria, Survey Data, PLS-SEM, Accounting, Auditing.
DOI: 10.5281/zenodo.17340439
title: Survey Data on Audit Evidence Mix and KAM Disclosure in Algeria

description: This dataset comprises primary quantitative data collected through a cross-sectional survey of 297 practicing external auditors in Algeria. The study's target population included all officially registered external auditors in Algeria. Questionnaires were distributed using a mixed-mode strategy (electronic mail and in-person visits), with 297 complete and usable responses received from an initial distribution of approximately 850, yielding a 34.9% response rate.

The structured questionnaire, developed from an extensive literature review and previously validated scales, measures five latent constructs using a 5-point Likert scale (ranging from 1=Strongly Disagree to 5=Strongly Agree). These constructs are:





**Auditor-Generated Evidence (AGE):** Measured with 4 items.




**Externally-Sourced Evidence (ESE):** Measured with 4 items.




**Client-Provided Evidence Verification (CPEV):** Measured with 3 items.




**Key Audit Matter Disclosure Quality (KAMQ):** Measured with 3 items.




**Audit Report Quality (ARQ):** Measured with 4 items.



The dataset also includes demographic characteristics of the sample, such as Professional Role, Years of Professional Experience, Highest Educational Qualification, and Firm Size, as detailed in Table 1 of the associated manuscript. This data was utilized to test a mediation model via Partial Least Squares Structural Equation Modeling (PLS-SEM) and offers valuable empirical insights into how different audit evidence types contribute to KAM disclosure quality, which in turn affects overall audit report quality within an emerging market context. It supports research on audit quality, audit evidence, and KAMs.
description: Audit Quality, Audit Evidence, Key Audit Matters (KAMs), Audit Report Quality, Mediation Analysis, Emerging Markets, Algeria, Survey Data, PLS-SEM, Accounting, Auditing.
DOI: 10.13140/rg.2.2.28674.95681
title: Pyroelectric Detector Identification Sentel DP1102 Transient Response 50s Sample Rate 0.01 s IR Emitter Voltage 0.5V Cooling
DOI: 10.25574/42039
title: Chandra X-ray Observatory ObsId 42039
DOI: 10.25574/42044
title: Chandra X-ray Observatory ObsId 42044
DOI: 10.5281/zenodo.13904007
title: Automated MESSENGER Plasma Region Classifications via Unsupervised Transfer Learning

description: This file contains the 1-minute resolution dataset (“labeled_sunside_data_3labels.csv”) for Toy-Edens et al.’s Automated Classification of MESSENGER Plasma Observations via Unsupervised Transfer Learning. The 1-minute resolution file contains the rolled up 1-minute epoch, features that go into clustering and post-cleaning methods, spacecraft positions (in MSO), total magnetic field, raw and cleaned clustering labels, and raw and cleaned transition name.

We ask that if you use any parts of the dataset that you cite Toy-Edens et al.’s Automated Classification of MESSENGER Plasma Observations via Unsupervised Transfer Learning (DOI: 10.3389/fspas.2025.1608091).

This work was supported by NASA grants 80NSSC19K0789 and 80NSSC22K0993.

 

The following tables detail the contents of the described files:

labeled_sunside_data_3labels.csv description






Column Name



Description





 Epoch



Epoch in datetime (YYYY-MM-DD HH:MM:SS)





 x_mso



x position of the spacecraft in MSO [km]





 y_mso



y position of the spacecraft in MSO [km]





 z_mso



z position of the spacecraft in MSO [km]





 btot_mso



Total magnetic field [nT]





 norm_Btot



Magnitude of the total magnetic field normalized to 150nT. See paper for more information





 ratio_max_width



Ratio of the width of the most prominent ion spectra peak (in number of energy channels) to max number of energy channels. See paper for more information





 ratio_high_low



Ratio of the mean of the log intensity of high energies in the ion spectra to the mean of the log intensity of low energies in the ion spectra. See paper for more information





 high_intensity



Boolean if there is a peak with a higher minimum intensity threshold. See paper for more information





 spectra_counts



A ratio of spectra bins with non-zero counts to all possible spectra bins (i.e. way to determine if too much missing spectra data). See paper for more information





 raw_named_label



Raw cluster assigned plasma region label (allowed values: magnetosheath, magnetosphere, solar wind)





intermediate_named_label



Cleaned cluster assigned plasma region label with only relabeling rules applied. See paper for more information





 named_label



Cleaned cluster assigned plasma region label with relabeling rules and post-processing applied (use these unless have a specific reason to use raw labels). See paper for more information





 raw_transition_name



Raw transition names (e.g. bow shock, magnetopause) based on "raw_named_label" cluster labels. See paper for more information





 transition_name



Cleaned transition names (e.g. bow shock, magnetopause) after removing likely transient transitions based on "named_label" cluster labels. See paper for more information
DOI: 10.5281/zenodo.15839733
title: Automated MESSENGER Plasma Region Classifications via Unsupervised Transfer Learning

description: This file contains the 1-minute resolution dataset (“labeled_sunside_data_3labels.csv”) for Toy-Edens et al.’s Automated Classification of MESSENGER Plasma Observations via Unsupervised Transfer Learning. The 1-minute resolution file contains the rolled up 1-minute epoch, features that go into clustering and post-cleaning methods, spacecraft positions (in MSO), total magnetic field, raw and cleaned clustering labels, and raw and cleaned transition name.

We ask that if you use any parts of the dataset that you cite Toy-Edens et al.’s Automated Classification of MESSENGER Plasma Observations via Unsupervised Transfer Learning (DOI: 10.3389/fspas.2025.1608091).

This work was supported by NASA grants 80NSSC19K0789 and 80NSSC22K0993.

 

The following tables detail the contents of the described files:

labeled_sunside_data_3labels.csv description






Column Name



Description





 Epoch



Epoch in datetime (YYYY-MM-DD HH:MM:SS)





 x_mso



x position of the spacecraft in MSO [km]





 y_mso



y position of the spacecraft in MSO [km]





 z_mso



z position of the spacecraft in MSO [km]





 btot_mso



Total magnetic field [nT]





 norm_Btot



Magnitude of the total magnetic field normalized to 150nT. See paper for more information





 ratio_max_width



Ratio of the width of the most prominent ion spectra peak (in number of energy channels) to max number of energy channels. See paper for more information





 ratio_high_low



Ratio of the mean of the log intensity of high energies in the ion spectra to the mean of the log intensity of low energies in the ion spectra. See paper for more information





 high_intensity



Boolean if there is a peak with a higher minimum intensity threshold. See paper for more information





 spectra_counts



A ratio of spectra bins with non-zero counts to all possible spectra bins (i.e. way to determine if too much missing spectra data). See paper for more information





 raw_named_label



Raw cluster assigned plasma region label (allowed values: magnetosheath, magnetosphere, solar wind)





intermediate_named_label



Cleaned cluster assigned plasma region label with only relabeling rules applied. See paper for more information





 named_label



Cleaned cluster assigned plasma region label with relabeling rules and post-processing applied (use these unless have a specific reason to use raw labels). See paper for more information





 raw_transition_name



Raw transition names (e.g. bow shock, magnetopause) based on "raw_named_label" cluster labels. See paper for more information





 transition_name



Cleaned transition names (e.g. bow shock, magnetopause) after removing likely transient transitions based on "named_label" cluster labels. See paper for more information
DOI: 10.5281/zenodo.17340494
title: PLANET4B Frame Analysis Dataset Pisa [UNIPI] 20251013

description: This dataset includes the data and files used to conduct a frame analysis about fashion and biodiversity in the Fashion case study of the Horizon Europe project PLANET4B (understanding Plural values, intersectionality, Leverage points, Attitudes, Norms, behaviour and social lEarning in Transformation for Biodiversity decision making). More specifically, it includes grey-literature documents (N=16), interviews (N=4), a QDPX project from Atlas.ti, and processed data (N=2). Additionally, the dataset includes a metada document (PLANET4B_Metadata-Frame-Analysis_Pisa_20251013_metadata.docx) with additional information about each of the files.

At the time of collection, all the contributors were researchers at the University of Pisa (UNIPI). The case study focused on understanding the relation between biodiversity loss and the textile, apparel, and fashion sector (TAF), and identifying leverage points and potential interventions to foster transformative change for biodiversity in the sector.
DOI: 10.15128/r1d504rk42h
title: Multi-state detection and spatial addressing in a microscope for ultracold molecules [dataset]

description: More details of how the lattice reconstruction algorithm works can be found in Mortlock's thesis: https://etheses.dur.ac.uk/15441/
description: Precise measurement of the particle number, spatial distribution and internal state is fundamental to all proposed experiments with ultracold molecules both in bulk gases and optical lattices. Here, we demonstrate in-situ detection of individual molecules in a bulk sample of 87Rb133Cs molecules. Extending techniques from atomic quantum gas microscopy, we pin the molecules in a deep two-dimensional optical lattice and, following dissociation, collect fluorescence from the constituent atoms using a high-numerical-aperture objective. This enables detection of individual molecules up to the resolution of the sub-micron lattice spacing. Our approach provides direct access to the density distribution of small samples of molecules, allowing us to obtain precise measurements of density-dependent collisional losses. Further, by mapping two internal states of the molecule to different atomic species, we demonstrate simultaneous detection of the position and rotational state of individual molecules. Finally, we implement local addressing of the sample using a focused beam to induce a spatially-dependent light shift on the rotational transitions of the molecules.
DOI: 10.3886/e209150v1-189246
title: Data and Code for: Economic Winners versus Losers and The Unequal Pandemic Recession

description: Replication package for "Economic Winners versus Losers and The Unequal Pandemic Recession"
DOI: 10.5281/zenodo.17341268
title: Glottography dataset derived from Rantanen et al. 2021 "Geographical database of the Uralic languages"

description: Cite the source of the dataset as:




Rantanen, T., Vesakoski, O., Ylikoski, J., & Tolvanen, H. (2021). Geographical database of the Uralic languages (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4784188
DOI: 10.3886/e238803
title: US Civil Aviation Accident Statistics

description: Summary statistics for US civil aviation accidents occurring from 2004 through 2023<br>
description: Aviation passengers injured in accidents.
DOI: 10.3886/e238803v1
title: US Civil Aviation Accident Statistics

description: Summary statistics for US civil aviation accidents occurring from 2004 through 2023<br>
description: Aviation passengers injured in accidents.
DOI: 10.5281/zenodo.17338108
title: PLANET4B Survey Belgium Students 20250214 v1 data

description: This data consists of feedback from students collected during the testing and validation process of the PLANET4B Biodiversity Engagement Course for Educators, developed as part of the PLANET4B Horizon Europe project. The feedback relates specifically to the design and classroom testing of a module on the fashion system’s impact on biodiversity. The module was delivered by a teacher in a secondary school in Belgium with students aged 15 - 16. The purpose of the testing was to gather feedback from teacher and students, to inform the format and content of the PLANET4B Biodiversity Engagement Course for Educators.
DOI: 10.5281/zenodo.17338109
title: PLANET4B Survey Belgium Students 20250214 v1 data

description: This data consists of feedback from students collected during the testing and validation process of the PLANET4B Biodiversity Engagement Course for Educators, developed as part of the PLANET4B Horizon Europe project. The feedback relates specifically to the design and classroom testing of a module on the fashion system’s impact on biodiversity. The module was delivered by a teacher in a secondary school in Belgium with students aged 15 - 16. The purpose of the testing was to gather feedback from teacher and students, to inform the format and content of the PLANET4B Biodiversity Engagement Course for Educators.
DOI: 10.5281/zenodo.16051970
title: Photographies de la campagne archéologique de 2025 de la villa du Monte Mompeo (Italie)

description: Tuile Zenodo conservant l'ensemble des photographies prises avec l'appareil photo du PAU par les étudiants présents durant la campagne 2025. 



Photographies de l'Openday : Visites guidées des responsables de la fouile (Mme Interdonato, M. Giletti). 

Photographies des unités stratigraphiques (US). 

Photographies de la "boîte à trésor" correspondant aux objets en fer, verre, et pigment. 

Photographies des éléments en marbre.

Photographies des fragments du sol du solarium.

Photographies des monnaies inventées en 2025.
DOI: 10.5281/zenodo.16051971
title: Photographies de la campagne archéologique de 2025 de la villa du Monte Mompeo (Italie)

description: Tuile Zenodo conservant l'ensemble des photographies prises avec l'appareil photo du PAU par les étudiants présents durant la campagne 2025. 



Photographies de l'Openday : Visites guidées des responsables de la fouile (Mme Interdonato, M. Giletti). 

Photographies des unités stratigraphiques (US). 

Photographies de la "boîte à trésor" correspondant aux objets en fer, verre, et pigment. 

Photographies des éléments en marbre.

Photographies des fragments du sol du solarium.

Photographies des monnaies inventées en 2025.
DOI: 10.5281/zenodo.17337931
title: PLANET4B Interview Belgium Teacher 20250220 v1 data

description: This data consists of feedback from a teacher received during the testing and validation process of the PLANET4B Biodiversity Engagement Course for Educators, developed as part of the PLANET4B Horizon Europe project. The feedback relates specifically to the design and classroom testing of a module on the fashion system’s impact on biodiversity. The module was delivered by a teacher in a secondary school in Belgium with students aged 15 - 16. The purpose of the testing was to gather feedback from teacher and students, to inform the format and content of the PLANET4B Biodiversity Engagement Course for Educators.
DOI: 10.5281/zenodo.17337932
title: PLANET4B Interview Belgium Teacher 20250220 v1 data

description: This data consists of feedback from a teacher received during the testing and validation process of the PLANET4B Biodiversity Engagement Course for Educators, developed as part of the PLANET4B Horizon Europe project. The feedback relates specifically to the design and classroom testing of a module on the fashion system’s impact on biodiversity. The module was delivered by a teacher in a secondary school in Belgium with students aged 15 - 16. The purpose of the testing was to gather feedback from teacher and students, to inform the format and content of the PLANET4B Biodiversity Engagement Course for Educators.
DOI: 10.5281/zenodo.17337497
title: PLANET4B Observation United Kingdom Students And Teacher 20250226 v1 data

description: These observations were collected during the testing and validation process of the PLANET4B Biodiversity Engagement Course for Educators, developed as part of the PLANET4B Horizon Europe project. The data relate specifically to the adaptation and classroom testing of the Pathbreak Biodiversity JENGA® game, a method designed within the PLANET4B project to engage learners with concepts of biodiversity, ecosystem fragility, and interdependence. The activity was implemented in a primary school in the United Kingdom with students aged 9 - 11 (Years 5 - 6). The purpose of the testing was to explore the suitability of the game for younger learners.
DOI: 10.5281/zenodo.17337498
title: PLANET4B Observation United Kingdom Students And Teacher 20250226 v1 data

description: These observations were collected during the testing and validation process of the PLANET4B Biodiversity Engagement Course for Educators, developed as part of the PLANET4B Horizon Europe project. The data relate specifically to the adaptation and classroom testing of the Pathbreak Biodiversity JENGA® game, a method designed within the PLANET4B project to engage learners with concepts of biodiversity, ecosystem fragility, and interdependence. The activity was implemented in a primary school in the United Kingdom with students aged 9 - 11 (Years 5 - 6). The purpose of the testing was to explore the suitability of the game for younger learners.
DOI: 10.5281/zenodo.14591085
title: Aircraft Efficiency Data from Lee et al. (2004)

description: File

Source




Aircraft Efficiency Data from IEA (2009).xlsx

Figure 2 in Lee et al. (2004)


Aircraft Efficiency Data Lee et al (2004).xlsx
Figure 7.2 in IEA (2009)




Data includes the performance metrics:



Energy Intensity [MJ/RPK] ("overall efficiency")


for commercial passenger aircraft introduced from 1955-2016.

Note:



This data was first used in the earlier publication Lee et al. (2001) in Figure 10. It is frequently reproduced, most prominently as Figure 7.2 in the 2009 IEA report Transport, Energy and CO2 (see file Figure 7-2 IEA (2009).pdf, reproduced under CC BY 4.0).

For a dataset using MJ/ASK ("Energy Use"), see Aircraft Efficiency Data from Babikian et al. (2002).
DOI: 10.5281/zenodo.17341138
title: Aircraft Efficiency Data from Lee et al. (2004)

description: File

Source




Aircraft Efficiency Data from IEA (2009).xlsx

Figure 2 in Lee et al. (2004)


Aircraft Efficiency Data Lee et al (2004).xlsx
Figure 7.2 in IEA (2009)




Data includes the performance metrics:



Energy Intensity [MJ/RPK] ("overall efficiency")


for commercial passenger aircraft introduced from 1955-2016.

Note:



This data was first used in the earlier publication Lee et al. (2001) in Figure 10. It is frequently reproduced, most prominently as Figure 7.2 in the 2009 IEA report Transport, Energy and CO2 (see file Figure 7-2 IEA (2009).pdf, reproduced under CC BY 4.0).

For a dataset using MJ/ASK ("Energy Use"), see Aircraft Efficiency Data from Babikian et al. (2002).