cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18471496
title: Supplementary Material Culturally Responsive AI and the Reconfiguration of Professional Capital: Localising Educator Communities in a Global Algorithmic Age

description: This dataset provides the supplementary analytical materials supporting the study “Culturally Responsive AI and the Reconfiguration of Professional Capital: Localising Educator Communities in a Global Algorithmic Age.” The dataset documents the systematic methodological and analytical processes used to examine how artificial intelligence (AI) reshapes professional capital—conceptualised as human, social, and decisional capital—within educator communities across diverse cultural and institutional contexts.

The materials included in this dataset support transparency, methodological rigour, and reusability, offering structured documentation of the qualitative synthesis underpinning the study’s findings.

Contents of the Dataset





SM01 – Methodological Summary: A concise overview of the research design, search strategy, inclusion and exclusion criteria, and analytical procedures.




SM02 – PRISMA Flow Diagram: Documentation of the study identification, screening, eligibility, and inclusion processes following PRISMA guidelines.




SM03 – PICo Mapping: Mapping of Population, Phenomenon of Interest, and Context to guide research question formulation and study selection.




SM04 – Contextual & Professional Capital Mapping: Analytical mapping linking educational contexts with dimensions of professional capital (human, social, decisional).




SM05 – Hybrid Thematic Analysis (HTA): Thematic coding tables derived through inductive and deductive analysis informed by professional capital theory.




SM06 – CIMO Analysis (Professional Capital Lens): Context–Intervention–Mechanism–Outcome matrices illustrating how AI-mediated interventions reconfigure professional capital within educator communities.


SM07. Critical Appraisal of Studies on Culturally Responsive AI and Professional Capital


Methodological Context

The dataset is derived from a qualitative literature synthesis employing PRISMA-guided screening, Hybrid Thematic Analysis, and CIMO-based explanatory structuring. All materials are based on secondary analysis of published studies and were interpreted with attention to cultural, institutional, and socio-technical context.

Re-use Potential

The dataset can be reused for secondary analyses, comparative reviews, or as a methodological reference for scholars investigating professional capital, AI in education, and culturally responsive technological integration. Users are encouraged to cite both this dataset and the associated journal article when reusing the materials.

Ethical and Access Notes

No human participants were directly involved in the creation of this dataset. All materials are derived from publicly available sources and are shared in accordance with responsible open science principles.
DOI: 10.5281/zenodo.18471497
title: Supplementary Material Culturally Responsive AI and the Reconfiguration of Professional Capital: Localising Educator Communities in a Global Algorithmic Age

description: This dataset provides the supplementary analytical materials supporting the study “Culturally Responsive AI and the Reconfiguration of Professional Capital: Localising Educator Communities in a Global Algorithmic Age.” The dataset documents the systematic methodological and analytical processes used to examine how artificial intelligence (AI) reshapes professional capital—conceptualised as human, social, and decisional capital—within educator communities across diverse cultural and institutional contexts.

The materials included in this dataset support transparency, methodological rigour, and reusability, offering structured documentation of the qualitative synthesis underpinning the study’s findings.

Contents of the Dataset





SM01 – Methodological Summary: A concise overview of the research design, search strategy, inclusion and exclusion criteria, and analytical procedures.




SM02 – PRISMA Flow Diagram: Documentation of the study identification, screening, eligibility, and inclusion processes following PRISMA guidelines.




SM03 – PICo Mapping: Mapping of Population, Phenomenon of Interest, and Context to guide research question formulation and study selection.




SM04 – Contextual & Professional Capital Mapping: Analytical mapping linking educational contexts with dimensions of professional capital (human, social, decisional).




SM05 – Hybrid Thematic Analysis (HTA): Thematic coding tables derived through inductive and deductive analysis informed by professional capital theory.




SM06 – CIMO Analysis (Professional Capital Lens): Context–Intervention–Mechanism–Outcome matrices illustrating how AI-mediated interventions reconfigure professional capital within educator communities.


SM07. Critical Appraisal of Studies on Culturally Responsive AI and Professional Capital


Methodological Context

The dataset is derived from a qualitative literature synthesis employing PRISMA-guided screening, Hybrid Thematic Analysis, and CIMO-based explanatory structuring. All materials are based on secondary analysis of published studies and were interpreted with attention to cultural, institutional, and socio-technical context.

Re-use Potential

The dataset can be reused for secondary analyses, comparative reviews, or as a methodological reference for scholars investigating professional capital, AI in education, and culturally responsive technological integration. Users are encouraged to cite both this dataset and the associated journal article when reusing the materials.

Ethical and Access Notes

No human participants were directly involved in the creation of this dataset. All materials are derived from publicly available sources and are shared in accordance with responsible open science principles.
DOI: 10.5281/zenodo.17720132
title: Doppler Frequency Shifts Associated with the 29 July 2025 M8.8 Kamchatka Earthquake in Southwest China

description: The ionosonde data is provided in Ionosonde_data.xlsx.  

Doppler and seismic data are provided in MATLAB format.

seismNo1_0729_0731_LESH_BJT.mat contains seismic data recorded in local time (UTC+8).

You can find the date and the three-component seismic data described within the MATLAB cell structure.

The remaining three files contain HF Doppler data collected in China. The date information is included in the filenames.

The sampling interval for all HF Doppler data is 3 seconds.

Channel/station mapping:





s1max: JIYA_EBIA




s2max: LUQU_ZHYA




s3max: YILI_EBIA




s4max: SHLA_EBIA




s5max: SHLA_ZHYA




s6max: ANZH_ZHYA
DOI: 10.5281/zenodo.18495757
title: Doppler Frequency Shifts Associated with the 29 July 2025 M8.8 Kamchatka Earthquake in Southwest China

description: The ionosonde data is provided in Ionosonde_data.xlsx.  

Doppler and seismic data are provided in MATLAB format.

seismNo1_0729_0731_LESH_BJT.mat contains seismic data recorded in local time (UTC+8).

You can find the date and the three-component seismic data described within the MATLAB cell structure.

The remaining three files contain HF Doppler data collected in China. The date information is included in the filenames.

The sampling interval for all HF Doppler data is 3 seconds.

Channel/station mapping:





s1max: JIYA_EBIA




s2max: LUQU_ZHYA




s3max: YILI_EBIA




s4max: SHLA_EBIA




s5max: SHLA_ZHYA




s6max: ANZH_ZHYA
DOI: 10.15468/dl.a6rert
title: Occurrence Download

description: A dataset containing 167 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Polistes goeldii"
 ]
}

 The dataset includes 167 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014054-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q7cwfr
title: Occurrence Download

description: A dataset containing 1710 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Umbellularia californica",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1710 records from 96 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014055-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18495670
title: Street Network Characteristics at Signalised Intersections

description: This data is associated with a study that explored the influence of street network characteristics on vehicular delay at signalised intersections. The street network characteristics were derived from GIS analysis of OpenStreetMap and Google Earth road networks within a 1-square-mile buffer at 23 signalised intersections in the Lagos Metropolis. The data contains aggregate delay at 23 signalised intersections, along with 23 indicators that cover various aspects of road network characteristics such as connectivity, intersection and road density. 
description: The lengths of local, feeder, arterial and expressway are measured in metres, while the street density is in kilometres. Approach width is measured in metres. Aggregate Transport Score (ATS) is the aggregate of alpha index, gamma index, link-to-node ratio, connected node ratio, and grid tree proportion index (GTP Index).
DOI: 10.5281/zenodo.18495671
title: Street Network Characteristics at Signalised Intersections

description: This data is associated with a study that explored the influence of street network characteristics on vehicular delay at signalised intersections. The street network characteristics were derived from GIS analysis of OpenStreetMap and Google Earth road networks within a 1-square-mile buffer at 23 signalised intersections in the Lagos Metropolis. The data contains aggregate delay at 23 signalised intersections, along with 23 indicators that cover various aspects of road network characteristics such as connectivity, intersection and road density. 
description: The lengths of local, feeder, arterial and expressway are measured in metres, while the street density is in kilometres. Approach width is measured in metres. Aggregate Transport Score (ATS) is the aggregate of alpha index, gamma index, link-to-node ratio, connected node ratio, and grid tree proportion index (GTP Index).
DOI: 10.15468/dl.rmgexw
title: Occurrence Download

description: A dataset containing 95 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Ornithodoros turicata"
 ]
}

 The dataset includes 95 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014056-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18495190
title: The Reflexes of the Common Slovene Long Schwa Vowel and of the Short Schwa Vowel in Non-Final Syllables in the Prekmurje Dialect (SLA data)

description: This dataset contains dialect material illustrating the reflexes of the Common Slovene long schwa vowel and the short schwa vowel in non-final syllables in the Prekmurje dialect area. The data were collected through fieldwork for the Slovenian Linguistic Atlas (SLA, 1946–).

The dataset was produced within the framework of the MEZZANINE project, funded by the Slovenian Research and Innovation Agency (ARIS).
DOI: 10.5281/zenodo.18495189
title: The Reflexes of the Common Slovene Long Schwa Vowel and of the Short Schwa Vowel in Non-Final Syllables in the Prekmurje Dialect (SLA data)

description: This dataset contains dialect material illustrating the reflexes of the Common Slovene long schwa vowel and the short schwa vowel in non-final syllables in the Prekmurje dialect area. The data were collected through fieldwork for the Slovenian Linguistic Atlas (SLA, 1946–).

The dataset was produced within the framework of the MEZZANINE project, funded by the Slovenian Research and Innovation Agency (ARIS).
DOI: 10.25574/31050
title: Chandra X-ray Observatory ObsId 31050

description: How Large Stellar Flares Influence the Chemistry of Protoplanetary Disks
DOI: 10.5281/zenodo.18315657
title: Influence of hydrodynamics forces on the root development of vegetation cuttings- DataSet
DOI: 10.5281/zenodo.18315656
title: Influence of hydrodynamics forces on the root development of vegetation cuttings- DataSet
DOI: 10.15468/dl.ttjamv
title: Occurrence Download

description: A dataset containing 1034 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astictopterus jama"
 ]
}

 The dataset includes 1034 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014057-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18470948
title: MORE:MOloch-downscaled ERA5 REanalysis (MORE), Version 1 (1991–2020)

description: The MOloch-downscaled ERA5 Reanalysis (MORE) is a high-resolution convection-permitting reanalysis dataset over Italy and the Alpine region, produced through dynamical downscaling of ERA5 using the non-hydrostatic mesoscale model MOLOCH. MORE provides continuous hourly data from 1990 to the present at a spatial resolution of approximately 1.7 km

Version 1.0 release

The first release (v1.0) of MORE provides hourly near-surface (2 m) air temperature and precipitation fields for the period 1991–2020. Future releases will include additional atmospheric, soil, and surface variables, such as wind components, humidity, soil moisture and temperature, surface fluxes, cloud cover, and pressure-level fields.

Version 1.0 is archived on Zenodo under the present DOI. The complete dataset, including all variables, will be progressively released through the CNR internal repository and assigned a dedicated DOI once the data collection is fully consolidated.

File format and structure





Format: NetCDF (CF-compliant), compressed in .tar.gz archives




Grid: regular latitude–longitude (768 × 960 points)




Time dimension: unlimited, expressed as “hours since 1991-01-01 00:00:00” using the proleptic Gregorian calendar


File naming convention:  more_YYYY.tar.gz,  where YYYY indicates the year of the data contained in the archive


Spatial and temporal coverage





Horizontal resolution: ~1.7 km




Domain: Italy and Alpine region




Period: 1991 – 2020




Temporal resolution: hourly



Main dimensions



time (unlimited)

lon (768)

lat (960)

height, height_2 (surface reference levels, e.g., 2 m, 10 m)

depth, depth_2 (soil levels)

950, 850, 700, 500, 300 hPa (pressure levels, varying by variable)


Example of available variables in v1.0



Near-surface: 2 m temperature, precipitation


Full variable list in future releases



Near-surface: dewpoint, specific and relative humidity, 10 m wind components, maximum 10 m wind, surface pressure, snowfall, soil temperature and moisture, surface fluxes (sensible/latent heat, radiation), planetary boundary layer height, CAPE, CIN, lifted index

Clouds: total, low, medium, high cloud cover

Column-integrated: total water vapour, vertically integrated water vapour fluxes

Pressure levels: temperature, geopotential height, wind components, relative humidity, vertical velocity, potential vorticity, potential temperature


Funding

Financial support is acknowledged from Next Generation EU, Mission 4, Component 1, CUP B53D23006850006, project “unveilINg pasT Events foR dROught risk mitiGATION (INTERROGATION)”
DOI: 10.5281/zenodo.18470947
title: MORE:MOloch-downscaled ERA5 REanalysis (MORE), Version 1 (1991–2020)

description: The MOloch-downscaled ERA5 Reanalysis (MORE) is a high-resolution convection-permitting reanalysis dataset over Italy and the Alpine region, produced through dynamical downscaling of ERA5 using the non-hydrostatic mesoscale model MOLOCH. MORE provides continuous hourly data from 1990 to the present at a spatial resolution of approximately 1.7 km

Version 1.0 release

The first release (v1.0) of MORE provides hourly near-surface (2 m) air temperature and precipitation fields for the period 1991–2020. Future releases will include additional atmospheric, soil, and surface variables, such as wind components, humidity, soil moisture and temperature, surface fluxes, cloud cover, and pressure-level fields.

Version 1.0 is archived on Zenodo under the present DOI. The complete dataset, including all variables, will be progressively released through the CNR internal repository and assigned a dedicated DOI once the data collection is fully consolidated.

File format and structure





Format: NetCDF (CF-compliant), compressed in .tar.gz archives




Grid: regular latitude–longitude (768 × 960 points)




Time dimension: unlimited, expressed as “hours since 1991-01-01 00:00:00” using the proleptic Gregorian calendar


File naming convention:  more_YYYY.tar.gz,  where YYYY indicates the year of the data contained in the archive


Spatial and temporal coverage





Horizontal resolution: ~1.7 km




Domain: Italy and Alpine region




Period: 1991 – 2020




Temporal resolution: hourly



Main dimensions



time (unlimited)

lon (768)

lat (960)

height, height_2 (surface reference levels, e.g., 2 m, 10 m)

depth, depth_2 (soil levels)

950, 850, 700, 500, 300 hPa (pressure levels, varying by variable)


Example of available variables in v1.0



Near-surface: 2 m temperature, precipitation


Full variable list in future releases



Near-surface: dewpoint, specific and relative humidity, 10 m wind components, maximum 10 m wind, surface pressure, snowfall, soil temperature and moisture, surface fluxes (sensible/latent heat, radiation), planetary boundary layer height, CAPE, CIN, lifted index

Clouds: total, low, medium, high cloud cover

Column-integrated: total water vapour, vertically integrated water vapour fluxes

Pressure levels: temperature, geopotential height, wind components, relative humidity, vertical velocity, potential vorticity, potential temperature


Funding

Financial support is acknowledged from Next Generation EU, Mission 4, Component 1, CUP B53D23006850006, project “unveilINg pasT Events foR dROught risk mitiGATION (INTERROGATION)”
DOI: 10.5281/zenodo.18492694
title: RiceLeafDisease-RSOD Selfbuilt Dataset and RDD-DETR Model for Rice Leaf Disease Detection
DOI: 10.5281/zenodo.18492695
title: RiceLeafDisease-RSOD Selfbuilt Dataset and RDD-DETR Model for Rice Leaf Disease Detection
DOI: 10.15468/dl.p7an4m
title: Occurrence Download

description: A dataset containing 117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Urbanodendron verrucosum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 117 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014059-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/btxlqi4z
title: AIMEE dataset

description: The dataset used in this paper for identifying inhibitors against SARS-CoV-2 3CL protease.
DOI: 10.57702/y7hb2npx
title: NQ-OPEN

description: The dataset includes 3,610 NQ-OPEN, 3,300 NQA, and 3,300 Hotpot QA questions.
DOI: 10.57702/nz5bi7zt
title: Learning image and video compression through spatial-temporal energy compaction

description: A learning-based video compression method
DOI: 10.57702/3s79gl3t
title: Customer Service Dialogue Dataset

description: A customer service dialogue dataset with highly abstractive summaries.
DOI: 10.57702/j38wkaev
title: Graph U-Nets

description: Graph U-Nets for node classification and graph classification tasks
DOI: 10.57702/91bmeoxk
title: Lederman-Talmon Dataset

description: The dataset used in the paper is a dataset from Lederman and Talmon. It contains two figurines rotating at different speeds.
DOI: 10.57702/3uczt7v5
title: DGCNN

description: The DGCNN dataset is a 3D point cloud dataset used for object recognition and scene understanding.
DOI: 10.57702/1ti6c5c2
title: Berita Dataset

description: The Berita dataset consists of 50304 digital Indonesia news articles shared online through Twitter.
DOI: 10.57702/idl9z88w
title: CLOW

description: CLOW is a dataset collected via a mixed-reality interactive approach for continual learning about objects in the wild.
DOI: 10.57702/ei73x0zd
title: Conformal Off-Policy Prediction in Contextual Bandits

description: Most off-policy evaluation methods for contextual bandits have focused on the expected outcome of a policy, which is estimated via methods that at best provide only asymptotic guarantees. However, in many applications, the expectation may not be the best measure of performance as it does not capture the variability of the outcome. In addition, particularly in safety-critical settings, stronger guarantees than asymptotic correctness may be required. To address these limitations, we consider a novel application of conformal prediction to contextual bandits. Given data collected under a behavioral policy, we propose conformal off-policy prediction (COPP), which can output reliable predictive intervals for the outcome under a new target policy.
DOI: 10.57702/bjeikg6i
title: Global Trade Network Time Series

description: The dataset is a global trade network time series extracted from Correlates of War project, capturing information on annual bilateral trade flows among countries between 1870 and 2009.
DOI: 10.57702/vujtwdvn
title: Teapot dataset

description: The dataset used in the paper is a wide domain image dataset, and the authors propose a weakly semi-supervised method for disentangling using both labeled and unlabeled data.
DOI: 10.57702/h3tefxlj
title: POSEIDON float system data

description: Poseidon float system data
DOI: 10.57702/sx19imud
title: One-stage Visual Grounding

description: A fast and accurate one-stage approach to visual grounding
DOI: 10.57702/dpbzfhmj
title: Double Loop Iterative Algorithm for Imaging Through Strong Random Scattering Medium

description: A double loop iterative algorithm for restoring two targets whose total size is beyond the memory effect.
DOI: 10.57702/r7olbepc
title: DND

description: The dataset used in the paper for image denoising, consisting of 50 scenarios.
DOI: 10.57702/zamszdr8
title: Dailydialog-Eval

description: This dataset is used for dialogue response evaluation.
DOI: 10.57702/ad6vjds5
title: Sentinel-1 SAR Dataset for Airport Detection

description: A benchmark dataset for airport detection using Sentinel-1 SAR images.
DOI: 10.57702/aops6wiv
title: ModelScope text-to-video

description: The dataset used in the paper for text-to-video diffusion models
DOI: 10.57702/utaydqmz
title: Darcy Flow Dataset

description: The Darcy flow dataset is a 2D dataset of permeability fields K(ξ) and pressure distributions p(ξ) that satisfy the Darcy flow equations.
DOI: 10.57702/apco6ygu
title: mmMAGIC

description: The mmMAGIC dataset is a collection of mmWave channel measurements
DOI: 10.57702/kmf5117r
title: Mackey-Glass Chaotic System

description: The dataset used in the paper is a Mackey-Glass chaotic system, described by a delay-differential equation, which is augmented by an additive drive signal.
DOI: 10.57702/12md5zjg
title: PlaNet

description: The PlaNet dataset is a dataset for photo geolocation estimation.
DOI: 10.57702/2kkzgfcn
title: Linear Attention Based Deep Nonlocal Means Filtering for Multiplicative Noise Removal

description: Multiplicative noise widely exists in radar images, medical images and other important fields' images. The removal of multiplicative noise can help the application of various imaging systems in remote sensing, medical treatment and so on.
DOI: 10.57702/r5cio93n
title: Reddit Hate Detection Dataset

description: The Reddit Hate Detection Dataset is a collection of Reddit comments annotated for hate speech.