cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/99zz75dn4c.1
title: Replication materials for “Upstream Intergenerational Transfers, Agricultural Technology Choice, and Conspicuous Consumption: Evidence from Rural Togo”

description: This repository contains the replication materials for the paper:
“Upstream Intergenerational Transfers, Agricultural Technology Choice, and Conspicuous Consumption: Evidence from Rural Togo”.

Contents:
- Stata do-files to clean the row data and reproduce tables and figures in the manuscript.
- Derived datasets.
-A read_me file

Data access:
The underlying microdata come from the LSMS Togo 2021–2022 survey and are available through the World Bank Microdata Library, subject to the provider’s terms of use. 

Embargo:
This dataset is under embargo until acceptance-publication of the associated article.
DOI: 10.35097/c5bsh0hv3y53s1pf
title: NRW school project 2011

description: On behalf of the State Chancellery of North Rhine-Westphalia, the Motor Test 1 (MT1) is used as an admission criterion for 5th grade at NRW sports schools under the leadership of the Research Center for Physical Education and Sports of Children and Young People. Since the 2007/08 school year, MT1 has been carried out at NRW sports schools (18 locations, 32 partner schools). The MT1 is equivalent to the German Motor Test. The goal at NRW sports schools is to create ideal conditions for students in grade 5 and above to get started in competitive sports. In grade 7, the MT1 is repeated along with four additional motor test tasks to assess the development of motor performance.
description: Querschnitt
description: Messung/Test
description: Zeitliches Forschungsdesign Querschnitt
description: Erhebungsverfahren Messung/Test
DOI: 10.17632/mjxwby94yw
title: ANUBHUTI: A COMPREHENSIVE CORPUS FOR SENTIMENT ANALYSIS IN BANGLA REGIONAL LANGUAGES

description: ANUBHUTI, a comprehensive dataset consisting of 2,500 sentences manually translated from standard Bangla into four major regional dialects—Mymensingh, Noakhali, Sylhet, and Chittagong. The dataset predominantly features political and religious content, reflecting the contemporary socio-political landscape of Bangladesh, alongside neutral texts to maintain balance. Each sentence is annotated using a dual annotation scheme: (i) multiclass thematic labeling categorizes sentences as Political, Religious, or Neutral, and (ii) multilabel emotion annotation assigns one or more emotions from Anger, Contempt, Disgust, Enjoyment, Fear, Sadness, and Surprise.
DOI: 10.17632/mjxwby94yw.3
title: ANUBHUTI: A COMPREHENSIVE CORPUS FOR SENTIMENT ANALYSIS IN BANGLA REGIONAL LANGUAGES

description: ANUBHUTI, a comprehensive dataset consisting of 2,500 sentences manually translated from standard Bangla into four major regional dialects—Mymensingh, Noakhali, Sylhet, and Chittagong. The dataset predominantly features political and religious content, reflecting the contemporary socio-political landscape of Bangladesh, alongside neutral texts to maintain balance. Each sentence is annotated using a dual annotation scheme: (i) multiclass thematic labeling categorizes sentences as Political, Religious, or Neutral, and (ii) multilabel emotion annotation assigns one or more emotions from Anger, Contempt, Disgust, Enjoyment, Fear, Sadness, and Surprise.
DOI: 10.15468/dl.7ywx4c
title: Occurrence Download

description: A dataset containing 218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Erigeron acris, Erigeron acris)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 218 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000376-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j85tpz
title: Occurrence Download

description: A dataset containing 6753 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eleutherodactylus coqui"
 ]
}

 The dataset includes 6753 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000375-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/y3btz6b27p
title: Replication Package for Cao et al. (Research Policy 2026)

description: This package contains the data and Stata replication codes for Cao, Siwei, Lei Zhen, and Brian Wright, 2026 "Distinguishing Hares and Tortoises in the Field: Applicants' anticipation of prediction of patent value flows" (Research Policy)
DOI: 10.17632/y3btz6b27p.1
title: Replication Package for Cao et al. (Research Policy 2026)

description: This package contains the data and Stata replication codes for Cao, Siwei, Lei Zhen, and Brian Wright, 2026 "Distinguishing Hares and Tortoises in the Field: Applicants' anticipation of prediction of patent value flows" (Research Policy)
DOI: 10.17632/crznfsztp9
title: Chattogram sent: A Multilingual Sentiment Dataset for Chattogram, Bengali , and English (Versions 2)

description: The Chattogram dialect (Chittangga), widely spoken in southeastern Bangladesh, is primarily an oral language with no standardized writing system. Despite its large speaker population, the dialect remains underrepresented in computational linguistics due to the scarcity of high-quality, manually curated digital resources. This dataset introduces a fully manual, native-curated multilingual sentiment corpus developed entirely by researchers who are native speakers of the Chattogram dialect.
​It consists of 4,451 parallel sentences aligned across five distinct columns: Standard Bangla, Chattogram dialect, English, Sentiment labels, and the Source of Data. The inclusion of the 'Source of Data' column provides essential context by categorizing each entry based on its origin, such as social media posts, regional drama scripts, and everyday conversations.
​The Chattogram dialect is predominantly spoken in Chattogram city, Cox’s Bazar, and the coastal regions of the Chittagong Hill Tracts, as well as nearby districts of southeastern Bangladesh. Given the oral nature of the dialect, all Chattogram sentences were phonetically transcribed into Bengali script. The dataset follows a translation-first pipeline: each Chattogram sentence was translated into Standard Bangla and then English by the same native speakers to maintain semantic fidelity and cross-lingual alignment.
​Sentiment annotation was performed after multilingual alignment, with each sentence categorized as Neutral, Negative, or Positive (Neutral: 1,969; Negative: 1,467; Positive: 1,015). The dataset represents the first high-quality benchmark for sentiment analysis in the Chattogram dialect, enabling researchers to develop low-resource NLP models, dialectal sentiment classifiers, and cross-lingual transformer-based systems. Its native-driven design ensures linguistic authenticity, cultural accuracy, and contextual relevance, providing a valuable resource for the computational study of underrepresented languages.
​By combining manual transcription, expert multilingual translation, source-based categorization, and careful sentiment annotation, this corpus supports both academic research and practical applications in natural language processing, multilingual AI systems, and digital preservation of oral language traditions.
DOI: 10.17632/crznfsztp9.1
title: Chattogram sent: A Multilingual Sentiment Dataset for Chattogram, Bengali , and English (Versions 2)

description: The Chattogram dialect (Chittangga), widely spoken in southeastern Bangladesh, is primarily an oral language with no standardized writing system. Despite its large speaker population, the dialect remains underrepresented in computational linguistics due to the scarcity of high-quality, manually curated digital resources. This dataset introduces a fully manual, native-curated multilingual sentiment corpus developed entirely by researchers who are native speakers of the Chattogram dialect.
​It consists of 4,451 parallel sentences aligned across five distinct columns: Standard Bangla, Chattogram dialect, English, Sentiment labels, and the Source of Data. The inclusion of the 'Source of Data' column provides essential context by categorizing each entry based on its origin, such as social media posts, regional drama scripts, and everyday conversations.
​The Chattogram dialect is predominantly spoken in Chattogram city, Cox’s Bazar, and the coastal regions of the Chittagong Hill Tracts, as well as nearby districts of southeastern Bangladesh. Given the oral nature of the dialect, all Chattogram sentences were phonetically transcribed into Bengali script. The dataset follows a translation-first pipeline: each Chattogram sentence was translated into Standard Bangla and then English by the same native speakers to maintain semantic fidelity and cross-lingual alignment.
​Sentiment annotation was performed after multilingual alignment, with each sentence categorized as Neutral, Negative, or Positive (Neutral: 1,969; Negative: 1,467; Positive: 1,015). The dataset represents the first high-quality benchmark for sentiment analysis in the Chattogram dialect, enabling researchers to develop low-resource NLP models, dialectal sentiment classifiers, and cross-lingual transformer-based systems. Its native-driven design ensures linguistic authenticity, cultural accuracy, and contextual relevance, providing a valuable resource for the computational study of underrepresented languages.
​By combining manual transcription, expert multilingual translation, source-based categorization, and careful sentiment annotation, this corpus supports both academic research and practical applications in natural language processing, multilingual AI systems, and digital preservation of oral language traditions.
DOI: 10.17632/hfpprnf8j7
title: Microplastic effects on zooplankton: meta-analysis dataset and code (48 studies; 1,468 effect sizes)

description: This dataset provides the extracted data used in our systematic review and meta-analysis on the effects of microplastics on zooplankton. It accompanies the manuscript “Meta-analysis Reveals Microplastics Pose High Risks to Zooplankton in a Warming World” (submitted to the Journal of Hazardous Materials).
The dataset is organized as three Excel files:
1) EffectSize_Dataset.xlsx
 Extracted observation-/effect-size–level dataset used for all meta-analyses (n = 1,468 observations from 48 studies). It contains study metadata and experimental descriptors (e.g., year, location, taxon/species, polymer, particle shape/size/color, exposure duration, temperature, feeding, etc.), concentration information (original and standardized units where applicable), endpoint category (growth/survival/reproduction/physiology), and effect-size statistics (effect size and corresponding variance/SE as used in the meta-analysis models).
2) Included_Studies.xlsx
 Full list of studies included after screening, with bibliographic information (author, year, title, etc.) and identifiers used to link to EffectSize_Dataset.xlsx.
3) Endpoint_Dictionary.xlsx
 A dictionary mapping the detailed response indicators reported in primary studies to the four endpoint categories used in the meta-analysis (growth, survival, reproduction, physiology).
Notes: Missing values are coded as blank/NA. Variable names and endpoint definitions follow the manuscript and supplementary tables/figures. When citing this dataset, please use the DOI assigned upon publication: DOI: [to be added].
DOI: 10.17632/hfpprnf8j7.1
title: Microplastic effects on zooplankton: meta-analysis dataset and code (48 studies; 1,468 effect sizes)

description: This dataset provides the extracted data used in our systematic review and meta-analysis on the effects of microplastics on zooplankton. It accompanies the manuscript “Meta-analysis Reveals Microplastics Pose High Risks to Zooplankton in a Warming World” (submitted to the Journal of Hazardous Materials).
The dataset is organized as three Excel files:
1) EffectSize_Dataset.xlsx
 Extracted observation-/effect-size–level dataset used for all meta-analyses (n = 1,468 observations from 48 studies). It contains study metadata and experimental descriptors (e.g., year, location, taxon/species, polymer, particle shape/size/color, exposure duration, temperature, feeding, etc.), concentration information (original and standardized units where applicable), endpoint category (growth/survival/reproduction/physiology), and effect-size statistics (effect size and corresponding variance/SE as used in the meta-analysis models).
2) Included_Studies.xlsx
 Full list of studies included after screening, with bibliographic information (author, year, title, etc.) and identifiers used to link to EffectSize_Dataset.xlsx.
3) Endpoint_Dictionary.xlsx
 A dictionary mapping the detailed response indicators reported in primary studies to the four endpoint categories used in the meta-analysis (growth, survival, reproduction, physiology).
Notes: Missing values are coded as blank/NA. Variable names and endpoint definitions follow the manuscript and supplementary tables/figures. When citing this dataset, please use the DOI assigned upon publication: DOI: [to be added].
DOI: 10.17632/znwwxghgff
title: Surface manifestations of internal solitary waves in the Western Arctic Ocean

description: The dataset includes the results of synthetic aperture radar (SAR) processing and identification of internal solitary waves (ISWs) in the Western Arctic Ocean in summer periods of 2007, 2011, 2016, 2018 and 2020.
The processed data include those acquired by the European Space Agency's Envisat Advanced SAR (ASAR) instrument in June-October 2007 and 2011, and by the contemporary Sentinel-1 A/B SAR-C missions in August-September 2018 and June-October 2020. In addition, L-band SAR images from the Japanese ALOS-2 PALSAR-2 instrument operated by the Japan Aerospace Exploration Agency (JAXA) were used for August-October 2016. Envisat ASAR data were obtained from ESA's rolling archive. These ASAR images were in Wide Swath mode with a spatial resolution of 150 m. In total, 369 ASAR images were analyzed: 159 from 2007 and 210 from 2011. Sentinel-1 A/B data were obtained from the Alaska Satellite Facility portal (https://search.asf.alaska.edu/). These consisted of high- and medium-resolution Ground Range Detected images captured in Interferometric Wide (IW) and Extra-Wide (EW) swath modes, with approximate spatial resolutions of 20 m and 90 m, respectively. A total of 2322 (694) S1A/B images acquired in June-October 2020 (August-September 2018) were analyzed. In addition, 36 ALOS-2 PALSAR-2 images acquired in August-October 2016 were also utilized. These L-band SAR images were acquired in ScanSAR nominal, Fine, and Ultra-fine modes, with spatial resolutions of 50 m, 12.5 m, and 5 m, respectively. Overall, 3421 SAR images were used in the analysis.
The dataset includes 2 mat files. The first, SAR-coverage.mat is the total SAR coverage of the study region by SAR data at 900x1200 grid. The second, isw_properties_gridded.mat includes parameters num_waves (total number of ISW detections), isw_probability (probability of ISW observations) and overlap (SAR coverage) interpolated to 29х49 horizontal grid (grid cell size is 0.5° in latitude and 1.5° in longitude) covering the region spanning 64.5-79.5° N, 110-185° W.
DOI: 10.17632/znwwxghgff.1
title: Surface manifestations of internal solitary waves in the Western Arctic Ocean

description: The dataset includes the results of synthetic aperture radar (SAR) processing and identification of internal solitary waves (ISWs) in the Western Arctic Ocean in summer periods of 2007, 2011, 2016, 2018 and 2020.
The processed data include those acquired by the European Space Agency's Envisat Advanced SAR (ASAR) instrument in June-October 2007 and 2011, and by the contemporary Sentinel-1 A/B SAR-C missions in August-September 2018 and June-October 2020. In addition, L-band SAR images from the Japanese ALOS-2 PALSAR-2 instrument operated by the Japan Aerospace Exploration Agency (JAXA) were used for August-October 2016. Envisat ASAR data were obtained from ESA's rolling archive. These ASAR images were in Wide Swath mode with a spatial resolution of 150 m. In total, 369 ASAR images were analyzed: 159 from 2007 and 210 from 2011. Sentinel-1 A/B data were obtained from the Alaska Satellite Facility portal (https://search.asf.alaska.edu/). These consisted of high- and medium-resolution Ground Range Detected images captured in Interferometric Wide (IW) and Extra-Wide (EW) swath modes, with approximate spatial resolutions of 20 m and 90 m, respectively. A total of 2322 (694) S1A/B images acquired in June-October 2020 (August-September 2018) were analyzed. In addition, 36 ALOS-2 PALSAR-2 images acquired in August-October 2016 were also utilized. These L-band SAR images were acquired in ScanSAR nominal, Fine, and Ultra-fine modes, with spatial resolutions of 50 m, 12.5 m, and 5 m, respectively. Overall, 3421 SAR images were used in the analysis.
The dataset includes 2 mat files. The first, SAR-coverage.mat is the total SAR coverage of the study region by SAR data at 900x1200 grid. The second, isw_properties_gridded.mat includes parameters num_waves (total number of ISW detections), isw_probability (probability of ISW observations) and overlap (SAR coverage) interpolated to 29х49 horizontal grid (grid cell size is 0.5° in latitude and 1.5° in longitude) covering the region spanning 64.5-79.5° N, 110-185° W.
DOI: 10.15468/dl.ydtg5f
title: Occurrence Download

description: A dataset containing 30203 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Esox lucius",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2019"
 ]
}

 The dataset includes 30203 records from 295 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000377-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.35097/vfatbt7z4tzx3qy5
title: NRW school project 2012

description: On behalf of the State Chancellery of North Rhine-Westphalia, the Motor Test 1 (MT1) is used as an admission criterion for 5th grade at NRW sports schools under the leadership of the Research Center for Physical Education and Sports of Children and Young People. Since the 2007/08 school year, MT1 has been carried out at NRW sports schools (18 locations, 32 partner schools). The MT1 is equivalent to the German Motor Test. The goal at NRW sports schools is to create ideal conditions for students in grade 5 and above to get started in competitive sports. In grade 7, the MT1 is repeated along with four additional motor test tasks to assess the development of motor performance.
description: Querschnitt
description: Messung/Test
description: Zeitliches Forschungsdesign Querschnitt
description: Erhebungsverfahren Messung/Test
DOI: 10.5517/ccdc.csd.cc2fc6mn
title: CCDC 2245101: Experimental Crystal Structure Determination

description: Related Article: Ulviye Acar Cevik, Hakan Ünver, Hayrani Eren Bostancı, Burak Tüzün, Nurten İrem Gedik, Ümit M. Kocyigit|2025|Z.Naturforsch.,C:J.Biosci.|80|705|doi:10.1515/znc-2024-0226
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fskld
title: CCDC 2257934: Experimental Crystal Structure Determination

description: Related Article: Xi Wang, Xieyi Jing, Gangfeng Tang, Dingwu Pan, Huadong Wang|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c05048
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fskmf
title: CCDC 2257935: Experimental Crystal Structure Determination

description: Related Article: Xi Wang, Xieyi Jing, Gangfeng Tang, Dingwu Pan, Huadong Wang|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c05048
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fskng
title: CCDC 2257936: Experimental Crystal Structure Determination

description: Related Article: Xi Wang, Xieyi Jing, Gangfeng Tang, Dingwu Pan, Huadong Wang|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c05048
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hdkbt
title: CCDC 2305976: Experimental Crystal Structure Determination

description: Related Article: Changmuk Kang, Seyong Kim, Woosong Han, Huijeong Ryu, Wooyong Seong, Jiyun Kim, Da-Ae Park, Seongwook Park, Kyungho Park, Hyun Min Park, Hyun Tae Kim, Chang Hee Lee, Sukwon Hong|2025|J. CO2 Utilization|91|103004|doi:10.1016/j.jcou.2024.103004
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jtz0c
title: CCDC 2348653: Experimental Crystal Structure Determination

description: Related Article: Shenshuai Wang, Yingjie Huang, Weiye Sun, Xufeng Lin
|2024|Antioxidants|13|894|doi:10.3390/antiox13080894
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jyjhj
title: CCDC 2352078: Experimental Crystal Structure Determination

description: Related Article: Md. Jobayer Ahmed, Md. Sohag Hasan, Md. Abdullah Al Mamun, Vladimir N. Nesterov, Shariff E. Kabir|2025|J.Mol.Struct.|1328|141290|doi:10.1016/j.molstruc.2024.141290
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.